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R Software Module

rwasp_decomposeloess.wasp

Title produced by software

Decomposition by Loess

Date of computation

Wed, 21 Dec 2011 06:45:20 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/21/t13244679367c4hug6t0d96dvz.htm/, Retrieved Tue, 07 May 2024 22:29:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158530, Retrieved Tue, 07 May 2024 22:29:20 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

118

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Univariate Data Series] [web traffic] [2010-10-19 15:13:07] [b98453cac15ba1066b407e146608df68]
- RMP   [Variance Reduction Matrix] [Traffic] [2010-11-29 09:57:15] [b98453cac15ba1066b407e146608df68]
- RM      [Standard Deviation-Mean Plot] [Traffic] [2010-11-29 11:05:08] [b98453cac15ba1066b407e146608df68]
- RMP       [ARIMA Forecasting] [Traffic] [2010-11-29 21:10:32] [b98453cac15ba1066b407e146608df68]
- R PD        [ARIMA Forecasting] [] [2011-12-06 10:39:07] [aba4febe8a2e49e81bdc61a6c01f5c21]
-   PD          [ARIMA Forecasting] [] [2011-12-20 15:47:34] [aba4febe8a2e49e81bdc61a6c01f5c21]
- R               [ARIMA Forecasting] [ARIMA Forecasting CV] [2011-12-20 15:48:10] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RMPD              [ARIMA Backward Selection] [paper arima backw...] [2011-12-21 10:36:30] [aba4febe8a2e49e81bdc61a6c01f5c21]
- RM D                  [Decomposition by Loess] [Paper Decompositi...] [2011-12-21 11:45:20] [3627de22d386f4cb93d383ef7c1ade7f] [Current]

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Dataseries X:

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Histogram

Boxplots

3.7
3
2.7
2.5
2.2
2.9
3.1
3
2.8
2.5
1.9
1.9
1.8
2
2.6
2.5
2.5
1.6
1.4
0.8
1.1
1.3
1.2
1.3
1.1
1.3
1.2
1.6
1.7
1.5
0.9
1.5
1.4
1.6
1.7
1.4
1.8
1.7
1.4
1.2
1
1.7
2.4
2
2.1
2
1.8
2.7
2.3
1.9
2
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
2.9
3.1
3.5
3.6
4.4
4.1
5.1
5.8
5.9
5.4
5.5
4.8
3.2
2.7
2.1
1.9
0.6
0.7
-0.2
-1
-1.7
-0.7
-1
-0.9
0
0.3
0.8
0.8
1.9
2.1
2.5
2.7
2.4
2.4
2.9
3.1
3
3.4
3.7
3.5
3.5
3.3
3.1
3.4
4
3.4
3.4
3.4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158530&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158530&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158530&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Seasonal Decomposition by Loess - Parameters
Component	Window	Degree	Jump
Seasonal	1321	0	133
Trend	19	1	2
Low-pass	13	1	2

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Parameters \tabularnewline
Component & Window & Degree & Jump \tabularnewline
Seasonal & 1321 & 0 & 133 \tabularnewline
Trend & 19 & 1 & 2 \tabularnewline
Low-pass & 13 & 1 & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158530&T=1

[TABLE]
[ROW][C]Seasonal Decomposition by Loess - Parameters[/C][/ROW]
[ROW][C]Component[/C][C]Window[/C][C]Degree[/C][C]Jump[/C][/ROW]
[ROW][C]Seasonal[/C][C]1321[/C][C]0[/C][C]133[/C][/ROW]
[ROW][C]Trend[/C][C]19[/C][C]1[/C][C]2[/C][/ROW]
[ROW][C]Low-pass[/C][C]13[/C][C]1[/C][C]2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158530&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158530&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Seasonal Decomposition by Loess - Parameters
Component	Window	Degree	Jump
Seasonal	1321	0	133
Trend	19	1	2
Low-pass	13	1	2

Seasonal Decomposition by Loess - Time Series Components
t	Observed	Fitted	Seasonal	Trend	Remainder
1	3.7	4.29088093253315	-0.0168920261911527	3.126011093658	0.590880932533152
2	3	2.95031895721795	0.00266462091348478	3.04701642186856	-0.0496810427820455
3	2.7	2.4097571696995	0.0222210802213765	2.96802175007912	-0.290242830300497
4	2.5	2.0894505207865	0.0231982529212557	2.88735122629225	-0.410549479213501
5	2.2	1.56005311580216	0.0332661816924701	2.80668070250537	-0.63994688419784
6	2.9	3.03665621374774	0.0397558279070061	2.72358795834526	0.136656213747738
7	3.1	3.5223501554032	0.0371546304116564	2.64049521418514	0.422350155403202
8	3	3.40260752552303	0.0324807609173898	2.56491171355958	0.402607525523029
9	2.8	3.11013773698466	0.00053405008131601	2.48932821293402	0.310137736984665
10	2.5	2.57203475377633	-0.0165741770362897	2.44453942325996	0.0720347537763275
11	1.9	1.47938638975002	-0.0791370233359205	2.39975063358591	-0.420613610249985
12	1.9	1.55619018392186	-0.0786721849409586	2.3224820010191	-0.343809816078139
13	1.8	1.37167865773886	-0.0168920261911527	2.24521336845229	-0.428321342261136
14	2	1.87367512307076	0.00266462091348478	2.12366025601575	-0.126324876929238
15	2.6	3.17567177619941	0.0222210802213765	2.00210714357922	0.575671776199408
16	2.5	3.07927211654679	0.0231982529212557	1.89752963053195	0.579272116546792
17	2.5	3.17378170082284	0.0332661816924701	1.79295211748469	0.673781700822841
18	1.6	1.44963174838331	0.0397558279070061	1.71061242370968	-0.150368251616689
19	1.4	1.13457263965367	0.0371546304116564	1.62827272993468	-0.265427360346333
20	0.8	0.0258985125379623	0.0324807609173898	1.54162072654465	-0.774101487462038
21	1.1	0.744497226764065	0.00053405008131601	1.45496872315462	-0.355502773235935
22	1.3	1.22754906449417	-0.0165741770362897	1.38902511254212	-0.0724509355058292
23	1.2	1.1560555214063	-0.0791370233359205	1.32308150192962	-0.0439444785936978
24	1.3	1.37207445395562	-0.0786721849409586	1.30659773098534	0.072074453955618
25	1.1	0.92677806615009	-0.0168920261911527	1.29011396004106	-0.17322193384991
26	1.3	1.29047606612266	0.00266462091348478	1.30685931296386	-0.00952393387734163
27	1.2	1.05417425389197	0.0222210802213765	1.32360466588665	-0.145825746108027
28	1.6	1.82820741913905	0.0231982529212557	1.34859432793969	0.228207419139054
29	1.7	1.9931498283148	0.0332661816924701	1.37358398999273	0.293149828314801
30	1.5	1.5548169137375	0.0397558279070061	1.40542725835549	0.0548169137375036
31	0.9	0.325574842870092	0.0371546304116564	1.43727052671825	-0.574425157129908
32	1.5	1.50617055170742	0.0324807609173898	1.46134868737519	0.00617055170741554
33	1.4	1.31403910188655	0.00053405008131601	1.48542684803214	-0.0859608981134534
34	1.6	1.73013159081381	-0.0165741770362897	1.48644258622248	0.130131590813805
35	1.7	1.99167869892309	-0.0791370233359205	1.48745832441283	0.291678698923088
36	1.4	1.37469793006561	-0.0786721849409586	1.50397425487535	-0.0253020699343884
37	1.8	2.09640184085329	-0.0168920261911527	1.52049018533786	0.296401840853291
38	1.7	1.83403477585637	0.00266462091348478	1.56330060323014	0.134034775856372
39	1.4	1.1716678986562	0.0222210802213765	1.60611102112242	-0.2283321013438
40	1.2	0.725458065731011	0.0231982529212557	1.65134368134773	-0.474541934268989
41	1	0.270157476734486	0.0332661816924701	1.69657634157304	-0.729842523265514
42	1.7	1.60688206593166	0.0397558279070061	1.75336210616133	-0.0931179340683357
43	2.4	2.95269749883873	0.0371546304116564	1.81014787074961	0.552697498838729
44	2	2.08998917805259	0.0324807609173898	1.87753006103002	0.0899891780525908
45	2.1	2.25455369860826	0.00053405008131601	1.94491225131042	0.15455369860826
46	2	1.99587400339382	-0.0165741770362897	2.02070017364247	-0.00412599660618485
47	1.8	1.5826489273614	-0.0791370233359205	2.09648809597452	-0.217351072638604
48	2.7	3.32406615726232	-0.0786721849409586	2.15460602767863	0.624066157262324
49	2.3	2.40416806680841	-0.0168920261911527	2.21272395938274	0.104168066808408
50	1.9	1.53921456028979	0.00266462091348478	2.25812081879672	-0.360785439710209
51	2	1.67426124156792	0.0222210802213765	2.3035176782107	-0.325738758432079
52	2.3	2.22039425868989	0.0231982529212557	2.35640748838885	-0.0796057413101057
53	2.8	3.15743651974053	0.0332661816924701	2.409297298567	0.357436519740532
54	2.4	2.30859208309138	0.0397558279070061	2.45165208900161	-0.0914079169086159
55	2.3	2.06883849015212	0.0371546304116564	2.49400687943622	-0.231161509847879
56	2.7	2.8346033328601	0.0324807609173898	2.53291590622251	0.134603332860099
57	2.7	2.82764101690988	0.00053405008131601	2.5718249330088	0.127641016909884
58	2.9	3.2202158146073	-0.0165741770362897	2.59635836242899	0.320215814607299
59	3	3.45824523148674	-0.0791370233359205	2.62089179184918	0.45824523148674
60	2.2	1.85310279436382	-0.0786721849409586	2.62556939057714	-0.34689720563618
61	2.3	1.98664503688605	-0.0168920261911527	2.6302469893051	-0.313354963113945
62	2.8	2.98056153669232	0.00266462091348478	2.6167738423942	0.180561536692315
63	2.8	2.97447822429532	0.0222210802213765	2.6033006954833	0.174478224295322
64	2.8	3.01151738688313	0.0231982529212557	2.56528436019562	0.211517386883128
65	2.2	1.8394657933996	0.0332661816924701	2.52726802490793	-0.3605342066004
66	2.6	2.6851450909383	0.0397558279070061	2.47509908115469	0.0851450909383011
67	2.8	3.13991523218689	0.0371546304116564	2.42293013740146	0.339915232186887
68	2.5	2.60801801297964	0.0324807609173898	2.35950122610297	0.108018012979636
69	2.4	2.50339363511419	0.00053405008131601	2.29607231480449	0.103393635114193
70	2.3	2.3934068442769	-0.0165741770362897	2.22316733275939	0.093406844276902
71	1.9	1.72887467262164	-0.0791370233359205	2.15026235071428	-0.171125327378364
72	1.7	1.40978779596017	-0.0786721849409586	2.06888438898079	-0.290212204039828
73	2	2.02938559894386	-0.0168920261911527	1.98750642724729	0.0293855989438625
74	2.1	2.30084689530088	0.00266462091348478	1.89648848378564	0.200846895300879
75	1.7	1.57230837945464	0.0222210802213765	1.80547054032398	-0.127691620545359
76	1.8	1.83933300963266	0.0231982529212557	1.73746873744609	0.0393330096326565
77	1.8	1.89726688373934	0.0332661816924701	1.66946693456819	0.0972668837393369
78	1.8	1.89065482275474	0.0397558279070061	1.66958934933826	0.090654822754735
79	1.3	0.893133605480019	0.0371546304116564	1.66971176410832	-0.406866394519981
80	1.3	0.812470106797464	0.0324807609173898	1.75504913228515	-0.487529893202536
81	1.3	0.759079449456716	0.00053405008131601	1.84038650046197	-0.540920550543284
82	1.2	0.404076783602577	-0.0165741770362897	2.01249739343371	-0.795923216397423
83	1.4	0.694528736930462	-0.0791370233359205	2.18460828640546	-0.705471263069537
84	2.2	2.03243854523193	-0.0786721849409586	2.44623363970903	-0.167561454768073
85	2.9	3.10903303317855	-0.0168920261911527	2.7078589930126	0.209033033178548
86	3.1	3.14146852748663	0.00266462091348478	3.05586685159988	0.0414685274866349
87	3.5	3.57390420959147	0.0222210802213765	3.40387471018716	0.0739042095914684
88	3.6	3.42473868113781	0.0231982529212557	3.75206306594093	-0.175261318862185
89	4.4	4.66648239661283	0.0332661816924701	4.1002514216947	0.266482396612826
90	4.1	3.84440347651073	0.0397558279070061	4.31584069558226	-0.255596523489269
91	5.1	5.63141540011852	0.0371546304116564	4.53142996946982	0.531415400118523
92	5.8	7.02589704033855	0.0324807609173898	4.54162219874406	1.22589704033855
93	5.9	7.24765152190038	0.00053405008131601	4.5518144280183	1.34765152190038
94	5.4	6.45513225415962	-0.0165741770362897	4.36144192287667	1.05513225415962
95	5.5	6.90806760560088	-0.0791370233359205	4.17106941773504	1.40806760560088
96	4.8	5.89135238013707	-0.0786721849409586	3.78731980480388	1.09135238013707
97	3.2	3.01332183431842	-0.0168920261911527	3.40357019187273	-0.186678165681577
98	2.7	2.53781710242236	0.00266462091348478	2.85951827666416	-0.162182897577643
99	2.1	1.86231255832304	0.0222210802213765	2.31546636145559	-0.237687441676963
100	1.9	2.025717901055	0.0231982529212557	1.75108384602375	0.125717901054999
101	0.6	-0.019967512284374	0.0332661816924701	1.1867013305919	-0.619967512284374
102	0.7	0.605153184616915	0.0397558279070061	0.755090987476078	-0.0948468153830845
103	-0.2	-0.760635274771909	0.0371546304116564	0.323480644360253	-0.560635274771909
104	-1	-2.12945452989095	0.0324807609173898	0.0969737689735608	-1.12945452989095
105	-1.7	-3.27100094366818	0.00053405008131601	-0.129533106413131	-1.57100094366818
106	-0.7	-1.22625316349196	-0.0165741770362897	-0.157172659471749	-0.526253163491962
107	-1	-1.73605076413371	-0.0791370233359205	-0.184812212530366	-0.736050764133713
108	-0.9	-1.70086480982594	-0.0786721849409586	-0.020463005233099	-0.800864809825943
109	0	-0.126994175873016	-0.0168920261911527	0.143886202064168	-0.126994175873016
110	0.3	0.160701366716683	0.00266462091348478	0.436634012369832	-0.139298633283317
111	0.8	0.848397097103128	0.0222210802213765	0.729381822675496	0.0483970971031276
112	0.8	0.523736477662981	0.0231982529212557	1.05306526941576	-0.276263522337019
113	1.9	2.3899851021515	0.0332661816924701	1.37674871615603	0.489985102151499
114	2.1	2.48812307687592	0.0397558279070061	1.67212109521708	0.388123076875919
115	2.5	2.99535189531022	0.0371546304116564	1.96749347427812	0.495351895310223
116	2.7	3.15036447293197	0.0324807609173898	2.21715476615064	0.45036447293197
117	2.4	2.33264989189552	0.00053405008131601	2.46681605802316	-0.0673501081044754
118	2.4	2.16323795174238	-0.0165741770362897	2.65333622529391	-0.236762048257622
119	2.9	3.03928063077126	-0.0791370233359205	2.83985639256466	0.139280630771256
120	3.1	3.32348475866903	-0.0786721849409586	2.95518742627193	0.223484758669029
121	3	2.94637356621196	-0.0168920261911527	3.07051845997919	-0.0536264337880419
122	3.4	3.64363085286487	0.00266462091348478	3.15370452622164	0.243630852864872
123	3.7	4.14088832731453	0.0222210802213765	3.23689059246409	0.440888327314533
124	3.5	3.69045418361946	0.0231982529212557	3.28634756345928	0.19045418361946
125	3.5	3.63092928385305	0.0332661816924701	3.33580453445448	0.130929283853054
126	3.3	3.18219291811638	0.0397558279070061	3.37805125397661	-0.117807081883616
127	3.1	2.7425473960896	0.0371546304116564	3.42029797349874	-0.357452603910399
128	3.4	3.31017392796558	0.0324807609173898	3.45734531111703	-0.0898260720344202
129	4	4.50507330118337	0.00053405008131601	3.49439264873532	0.505073301183367
130	3.4	3.28829976340083	-0.0165741770362897	3.52827441363546	-0.11170023659917
131	3.4	3.31698084480032	-0.0791370233359205	3.5621561785356	-0.0830191551996822
132	3.4	3.28473946089004	-0.0786721849409586	3.59393272405092	-0.115260539109961

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 3.7 & 4.29088093253315 & -0.0168920261911527 & 3.126011093658 & 0.590880932533152 \tabularnewline
2 & 3 & 2.95031895721795 & 0.00266462091348478 & 3.04701642186856 & -0.0496810427820455 \tabularnewline
3 & 2.7 & 2.4097571696995 & 0.0222210802213765 & 2.96802175007912 & -0.290242830300497 \tabularnewline
4 & 2.5 & 2.0894505207865 & 0.0231982529212557 & 2.88735122629225 & -0.410549479213501 \tabularnewline
5 & 2.2 & 1.56005311580216 & 0.0332661816924701 & 2.80668070250537 & -0.63994688419784 \tabularnewline
6 & 2.9 & 3.03665621374774 & 0.0397558279070061 & 2.72358795834526 & 0.136656213747738 \tabularnewline
7 & 3.1 & 3.5223501554032 & 0.0371546304116564 & 2.64049521418514 & 0.422350155403202 \tabularnewline
8 & 3 & 3.40260752552303 & 0.0324807609173898 & 2.56491171355958 & 0.402607525523029 \tabularnewline
9 & 2.8 & 3.11013773698466 & 0.00053405008131601 & 2.48932821293402 & 0.310137736984665 \tabularnewline
10 & 2.5 & 2.57203475377633 & -0.0165741770362897 & 2.44453942325996 & 0.0720347537763275 \tabularnewline
11 & 1.9 & 1.47938638975002 & -0.0791370233359205 & 2.39975063358591 & -0.420613610249985 \tabularnewline
12 & 1.9 & 1.55619018392186 & -0.0786721849409586 & 2.3224820010191 & -0.343809816078139 \tabularnewline
13 & 1.8 & 1.37167865773886 & -0.0168920261911527 & 2.24521336845229 & -0.428321342261136 \tabularnewline
14 & 2 & 1.87367512307076 & 0.00266462091348478 & 2.12366025601575 & -0.126324876929238 \tabularnewline
15 & 2.6 & 3.17567177619941 & 0.0222210802213765 & 2.00210714357922 & 0.575671776199408 \tabularnewline
16 & 2.5 & 3.07927211654679 & 0.0231982529212557 & 1.89752963053195 & 0.579272116546792 \tabularnewline
17 & 2.5 & 3.17378170082284 & 0.0332661816924701 & 1.79295211748469 & 0.673781700822841 \tabularnewline
18 & 1.6 & 1.44963174838331 & 0.0397558279070061 & 1.71061242370968 & -0.150368251616689 \tabularnewline
19 & 1.4 & 1.13457263965367 & 0.0371546304116564 & 1.62827272993468 & -0.265427360346333 \tabularnewline
20 & 0.8 & 0.0258985125379623 & 0.0324807609173898 & 1.54162072654465 & -0.774101487462038 \tabularnewline
21 & 1.1 & 0.744497226764065 & 0.00053405008131601 & 1.45496872315462 & -0.355502773235935 \tabularnewline
22 & 1.3 & 1.22754906449417 & -0.0165741770362897 & 1.38902511254212 & -0.0724509355058292 \tabularnewline
23 & 1.2 & 1.1560555214063 & -0.0791370233359205 & 1.32308150192962 & -0.0439444785936978 \tabularnewline
24 & 1.3 & 1.37207445395562 & -0.0786721849409586 & 1.30659773098534 & 0.072074453955618 \tabularnewline
25 & 1.1 & 0.92677806615009 & -0.0168920261911527 & 1.29011396004106 & -0.17322193384991 \tabularnewline
26 & 1.3 & 1.29047606612266 & 0.00266462091348478 & 1.30685931296386 & -0.00952393387734163 \tabularnewline
27 & 1.2 & 1.05417425389197 & 0.0222210802213765 & 1.32360466588665 & -0.145825746108027 \tabularnewline
28 & 1.6 & 1.82820741913905 & 0.0231982529212557 & 1.34859432793969 & 0.228207419139054 \tabularnewline
29 & 1.7 & 1.9931498283148 & 0.0332661816924701 & 1.37358398999273 & 0.293149828314801 \tabularnewline
30 & 1.5 & 1.5548169137375 & 0.0397558279070061 & 1.40542725835549 & 0.0548169137375036 \tabularnewline
31 & 0.9 & 0.325574842870092 & 0.0371546304116564 & 1.43727052671825 & -0.574425157129908 \tabularnewline
32 & 1.5 & 1.50617055170742 & 0.0324807609173898 & 1.46134868737519 & 0.00617055170741554 \tabularnewline
33 & 1.4 & 1.31403910188655 & 0.00053405008131601 & 1.48542684803214 & -0.0859608981134534 \tabularnewline
34 & 1.6 & 1.73013159081381 & -0.0165741770362897 & 1.48644258622248 & 0.130131590813805 \tabularnewline
35 & 1.7 & 1.99167869892309 & -0.0791370233359205 & 1.48745832441283 & 0.291678698923088 \tabularnewline
36 & 1.4 & 1.37469793006561 & -0.0786721849409586 & 1.50397425487535 & -0.0253020699343884 \tabularnewline
37 & 1.8 & 2.09640184085329 & -0.0168920261911527 & 1.52049018533786 & 0.296401840853291 \tabularnewline
38 & 1.7 & 1.83403477585637 & 0.00266462091348478 & 1.56330060323014 & 0.134034775856372 \tabularnewline
39 & 1.4 & 1.1716678986562 & 0.0222210802213765 & 1.60611102112242 & -0.2283321013438 \tabularnewline
40 & 1.2 & 0.725458065731011 & 0.0231982529212557 & 1.65134368134773 & -0.474541934268989 \tabularnewline
41 & 1 & 0.270157476734486 & 0.0332661816924701 & 1.69657634157304 & -0.729842523265514 \tabularnewline
42 & 1.7 & 1.60688206593166 & 0.0397558279070061 & 1.75336210616133 & -0.0931179340683357 \tabularnewline
43 & 2.4 & 2.95269749883873 & 0.0371546304116564 & 1.81014787074961 & 0.552697498838729 \tabularnewline
44 & 2 & 2.08998917805259 & 0.0324807609173898 & 1.87753006103002 & 0.0899891780525908 \tabularnewline
45 & 2.1 & 2.25455369860826 & 0.00053405008131601 & 1.94491225131042 & 0.15455369860826 \tabularnewline
46 & 2 & 1.99587400339382 & -0.0165741770362897 & 2.02070017364247 & -0.00412599660618485 \tabularnewline
47 & 1.8 & 1.5826489273614 & -0.0791370233359205 & 2.09648809597452 & -0.217351072638604 \tabularnewline
48 & 2.7 & 3.32406615726232 & -0.0786721849409586 & 2.15460602767863 & 0.624066157262324 \tabularnewline
49 & 2.3 & 2.40416806680841 & -0.0168920261911527 & 2.21272395938274 & 0.104168066808408 \tabularnewline
50 & 1.9 & 1.53921456028979 & 0.00266462091348478 & 2.25812081879672 & -0.360785439710209 \tabularnewline
51 & 2 & 1.67426124156792 & 0.0222210802213765 & 2.3035176782107 & -0.325738758432079 \tabularnewline
52 & 2.3 & 2.22039425868989 & 0.0231982529212557 & 2.35640748838885 & -0.0796057413101057 \tabularnewline
53 & 2.8 & 3.15743651974053 & 0.0332661816924701 & 2.409297298567 & 0.357436519740532 \tabularnewline
54 & 2.4 & 2.30859208309138 & 0.0397558279070061 & 2.45165208900161 & -0.0914079169086159 \tabularnewline
55 & 2.3 & 2.06883849015212 & 0.0371546304116564 & 2.49400687943622 & -0.231161509847879 \tabularnewline
56 & 2.7 & 2.8346033328601 & 0.0324807609173898 & 2.53291590622251 & 0.134603332860099 \tabularnewline
57 & 2.7 & 2.82764101690988 & 0.00053405008131601 & 2.5718249330088 & 0.127641016909884 \tabularnewline
58 & 2.9 & 3.2202158146073 & -0.0165741770362897 & 2.59635836242899 & 0.320215814607299 \tabularnewline
59 & 3 & 3.45824523148674 & -0.0791370233359205 & 2.62089179184918 & 0.45824523148674 \tabularnewline
60 & 2.2 & 1.85310279436382 & -0.0786721849409586 & 2.62556939057714 & -0.34689720563618 \tabularnewline
61 & 2.3 & 1.98664503688605 & -0.0168920261911527 & 2.6302469893051 & -0.313354963113945 \tabularnewline
62 & 2.8 & 2.98056153669232 & 0.00266462091348478 & 2.6167738423942 & 0.180561536692315 \tabularnewline
63 & 2.8 & 2.97447822429532 & 0.0222210802213765 & 2.6033006954833 & 0.174478224295322 \tabularnewline
64 & 2.8 & 3.01151738688313 & 0.0231982529212557 & 2.56528436019562 & 0.211517386883128 \tabularnewline
65 & 2.2 & 1.8394657933996 & 0.0332661816924701 & 2.52726802490793 & -0.3605342066004 \tabularnewline
66 & 2.6 & 2.6851450909383 & 0.0397558279070061 & 2.47509908115469 & 0.0851450909383011 \tabularnewline
67 & 2.8 & 3.13991523218689 & 0.0371546304116564 & 2.42293013740146 & 0.339915232186887 \tabularnewline
68 & 2.5 & 2.60801801297964 & 0.0324807609173898 & 2.35950122610297 & 0.108018012979636 \tabularnewline
69 & 2.4 & 2.50339363511419 & 0.00053405008131601 & 2.29607231480449 & 0.103393635114193 \tabularnewline
70 & 2.3 & 2.3934068442769 & -0.0165741770362897 & 2.22316733275939 & 0.093406844276902 \tabularnewline
71 & 1.9 & 1.72887467262164 & -0.0791370233359205 & 2.15026235071428 & -0.171125327378364 \tabularnewline
72 & 1.7 & 1.40978779596017 & -0.0786721849409586 & 2.06888438898079 & -0.290212204039828 \tabularnewline
73 & 2 & 2.02938559894386 & -0.0168920261911527 & 1.98750642724729 & 0.0293855989438625 \tabularnewline
74 & 2.1 & 2.30084689530088 & 0.00266462091348478 & 1.89648848378564 & 0.200846895300879 \tabularnewline
75 & 1.7 & 1.57230837945464 & 0.0222210802213765 & 1.80547054032398 & -0.127691620545359 \tabularnewline
76 & 1.8 & 1.83933300963266 & 0.0231982529212557 & 1.73746873744609 & 0.0393330096326565 \tabularnewline
77 & 1.8 & 1.89726688373934 & 0.0332661816924701 & 1.66946693456819 & 0.0972668837393369 \tabularnewline
78 & 1.8 & 1.89065482275474 & 0.0397558279070061 & 1.66958934933826 & 0.090654822754735 \tabularnewline
79 & 1.3 & 0.893133605480019 & 0.0371546304116564 & 1.66971176410832 & -0.406866394519981 \tabularnewline
80 & 1.3 & 0.812470106797464 & 0.0324807609173898 & 1.75504913228515 & -0.487529893202536 \tabularnewline
81 & 1.3 & 0.759079449456716 & 0.00053405008131601 & 1.84038650046197 & -0.540920550543284 \tabularnewline
82 & 1.2 & 0.404076783602577 & -0.0165741770362897 & 2.01249739343371 & -0.795923216397423 \tabularnewline
83 & 1.4 & 0.694528736930462 & -0.0791370233359205 & 2.18460828640546 & -0.705471263069537 \tabularnewline
84 & 2.2 & 2.03243854523193 & -0.0786721849409586 & 2.44623363970903 & -0.167561454768073 \tabularnewline
85 & 2.9 & 3.10903303317855 & -0.0168920261911527 & 2.7078589930126 & 0.209033033178548 \tabularnewline
86 & 3.1 & 3.14146852748663 & 0.00266462091348478 & 3.05586685159988 & 0.0414685274866349 \tabularnewline
87 & 3.5 & 3.57390420959147 & 0.0222210802213765 & 3.40387471018716 & 0.0739042095914684 \tabularnewline
88 & 3.6 & 3.42473868113781 & 0.0231982529212557 & 3.75206306594093 & -0.175261318862185 \tabularnewline
89 & 4.4 & 4.66648239661283 & 0.0332661816924701 & 4.1002514216947 & 0.266482396612826 \tabularnewline
90 & 4.1 & 3.84440347651073 & 0.0397558279070061 & 4.31584069558226 & -0.255596523489269 \tabularnewline
91 & 5.1 & 5.63141540011852 & 0.0371546304116564 & 4.53142996946982 & 0.531415400118523 \tabularnewline
92 & 5.8 & 7.02589704033855 & 0.0324807609173898 & 4.54162219874406 & 1.22589704033855 \tabularnewline
93 & 5.9 & 7.24765152190038 & 0.00053405008131601 & 4.5518144280183 & 1.34765152190038 \tabularnewline
94 & 5.4 & 6.45513225415962 & -0.0165741770362897 & 4.36144192287667 & 1.05513225415962 \tabularnewline
95 & 5.5 & 6.90806760560088 & -0.0791370233359205 & 4.17106941773504 & 1.40806760560088 \tabularnewline
96 & 4.8 & 5.89135238013707 & -0.0786721849409586 & 3.78731980480388 & 1.09135238013707 \tabularnewline
97 & 3.2 & 3.01332183431842 & -0.0168920261911527 & 3.40357019187273 & -0.186678165681577 \tabularnewline
98 & 2.7 & 2.53781710242236 & 0.00266462091348478 & 2.85951827666416 & -0.162182897577643 \tabularnewline
99 & 2.1 & 1.86231255832304 & 0.0222210802213765 & 2.31546636145559 & -0.237687441676963 \tabularnewline
100 & 1.9 & 2.025717901055 & 0.0231982529212557 & 1.75108384602375 & 0.125717901054999 \tabularnewline
101 & 0.6 & -0.019967512284374 & 0.0332661816924701 & 1.1867013305919 & -0.619967512284374 \tabularnewline
102 & 0.7 & 0.605153184616915 & 0.0397558279070061 & 0.755090987476078 & -0.0948468153830845 \tabularnewline
103 & -0.2 & -0.760635274771909 & 0.0371546304116564 & 0.323480644360253 & -0.560635274771909 \tabularnewline
104 & -1 & -2.12945452989095 & 0.0324807609173898 & 0.0969737689735608 & -1.12945452989095 \tabularnewline
105 & -1.7 & -3.27100094366818 & 0.00053405008131601 & -0.129533106413131 & -1.57100094366818 \tabularnewline
106 & -0.7 & -1.22625316349196 & -0.0165741770362897 & -0.157172659471749 & -0.526253163491962 \tabularnewline
107 & -1 & -1.73605076413371 & -0.0791370233359205 & -0.184812212530366 & -0.736050764133713 \tabularnewline
108 & -0.9 & -1.70086480982594 & -0.0786721849409586 & -0.020463005233099 & -0.800864809825943 \tabularnewline
109 & 0 & -0.126994175873016 & -0.0168920261911527 & 0.143886202064168 & -0.126994175873016 \tabularnewline
110 & 0.3 & 0.160701366716683 & 0.00266462091348478 & 0.436634012369832 & -0.139298633283317 \tabularnewline
111 & 0.8 & 0.848397097103128 & 0.0222210802213765 & 0.729381822675496 & 0.0483970971031276 \tabularnewline
112 & 0.8 & 0.523736477662981 & 0.0231982529212557 & 1.05306526941576 & -0.276263522337019 \tabularnewline
113 & 1.9 & 2.3899851021515 & 0.0332661816924701 & 1.37674871615603 & 0.489985102151499 \tabularnewline
114 & 2.1 & 2.48812307687592 & 0.0397558279070061 & 1.67212109521708 & 0.388123076875919 \tabularnewline
115 & 2.5 & 2.99535189531022 & 0.0371546304116564 & 1.96749347427812 & 0.495351895310223 \tabularnewline
116 & 2.7 & 3.15036447293197 & 0.0324807609173898 & 2.21715476615064 & 0.45036447293197 \tabularnewline
117 & 2.4 & 2.33264989189552 & 0.00053405008131601 & 2.46681605802316 & -0.0673501081044754 \tabularnewline
118 & 2.4 & 2.16323795174238 & -0.0165741770362897 & 2.65333622529391 & -0.236762048257622 \tabularnewline
119 & 2.9 & 3.03928063077126 & -0.0791370233359205 & 2.83985639256466 & 0.139280630771256 \tabularnewline
120 & 3.1 & 3.32348475866903 & -0.0786721849409586 & 2.95518742627193 & 0.223484758669029 \tabularnewline
121 & 3 & 2.94637356621196 & -0.0168920261911527 & 3.07051845997919 & -0.0536264337880419 \tabularnewline
122 & 3.4 & 3.64363085286487 & 0.00266462091348478 & 3.15370452622164 & 0.243630852864872 \tabularnewline
123 & 3.7 & 4.14088832731453 & 0.0222210802213765 & 3.23689059246409 & 0.440888327314533 \tabularnewline
124 & 3.5 & 3.69045418361946 & 0.0231982529212557 & 3.28634756345928 & 0.19045418361946 \tabularnewline
125 & 3.5 & 3.63092928385305 & 0.0332661816924701 & 3.33580453445448 & 0.130929283853054 \tabularnewline
126 & 3.3 & 3.18219291811638 & 0.0397558279070061 & 3.37805125397661 & -0.117807081883616 \tabularnewline
127 & 3.1 & 2.7425473960896 & 0.0371546304116564 & 3.42029797349874 & -0.357452603910399 \tabularnewline
128 & 3.4 & 3.31017392796558 & 0.0324807609173898 & 3.45734531111703 & -0.0898260720344202 \tabularnewline
129 & 4 & 4.50507330118337 & 0.00053405008131601 & 3.49439264873532 & 0.505073301183367 \tabularnewline
130 & 3.4 & 3.28829976340083 & -0.0165741770362897 & 3.52827441363546 & -0.11170023659917 \tabularnewline
131 & 3.4 & 3.31698084480032 & -0.0791370233359205 & 3.5621561785356 & -0.0830191551996822 \tabularnewline
132 & 3.4 & 3.28473946089004 & -0.0786721849409586 & 3.59393272405092 & -0.115260539109961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158530&T=2

[TABLE]
[ROW][C]Seasonal Decomposition by Loess - Time Series Components[/C][/ROW]
[ROW][C]t[/C][C]Observed[/C][C]Fitted[/C][C]Seasonal[/C][C]Trend[/C][C]Remainder[/C][/ROW]
[ROW][C]1[/C][C]3.7[/C][C]4.29088093253315[/C][C]-0.0168920261911527[/C][C]3.126011093658[/C][C]0.590880932533152[/C][/ROW]
[ROW][C]2[/C][C]3[/C][C]2.95031895721795[/C][C]0.00266462091348478[/C][C]3.04701642186856[/C][C]-0.0496810427820455[/C][/ROW]
[ROW][C]3[/C][C]2.7[/C][C]2.4097571696995[/C][C]0.0222210802213765[/C][C]2.96802175007912[/C][C]-0.290242830300497[/C][/ROW]
[ROW][C]4[/C][C]2.5[/C][C]2.0894505207865[/C][C]0.0231982529212557[/C][C]2.88735122629225[/C][C]-0.410549479213501[/C][/ROW]
[ROW][C]5[/C][C]2.2[/C][C]1.56005311580216[/C][C]0.0332661816924701[/C][C]2.80668070250537[/C][C]-0.63994688419784[/C][/ROW]
[ROW][C]6[/C][C]2.9[/C][C]3.03665621374774[/C][C]0.0397558279070061[/C][C]2.72358795834526[/C][C]0.136656213747738[/C][/ROW]
[ROW][C]7[/C][C]3.1[/C][C]3.5223501554032[/C][C]0.0371546304116564[/C][C]2.64049521418514[/C][C]0.422350155403202[/C][/ROW]
[ROW][C]8[/C][C]3[/C][C]3.40260752552303[/C][C]0.0324807609173898[/C][C]2.56491171355958[/C][C]0.402607525523029[/C][/ROW]
[ROW][C]9[/C][C]2.8[/C][C]3.11013773698466[/C][C]0.00053405008131601[/C][C]2.48932821293402[/C][C]0.310137736984665[/C][/ROW]
[ROW][C]10[/C][C]2.5[/C][C]2.57203475377633[/C][C]-0.0165741770362897[/C][C]2.44453942325996[/C][C]0.0720347537763275[/C][/ROW]
[ROW][C]11[/C][C]1.9[/C][C]1.47938638975002[/C][C]-0.0791370233359205[/C][C]2.39975063358591[/C][C]-0.420613610249985[/C][/ROW]
[ROW][C]12[/C][C]1.9[/C][C]1.55619018392186[/C][C]-0.0786721849409586[/C][C]2.3224820010191[/C][C]-0.343809816078139[/C][/ROW]
[ROW][C]13[/C][C]1.8[/C][C]1.37167865773886[/C][C]-0.0168920261911527[/C][C]2.24521336845229[/C][C]-0.428321342261136[/C][/ROW]
[ROW][C]14[/C][C]2[/C][C]1.87367512307076[/C][C]0.00266462091348478[/C][C]2.12366025601575[/C][C]-0.126324876929238[/C][/ROW]
[ROW][C]15[/C][C]2.6[/C][C]3.17567177619941[/C][C]0.0222210802213765[/C][C]2.00210714357922[/C][C]0.575671776199408[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]3.07927211654679[/C][C]0.0231982529212557[/C][C]1.89752963053195[/C][C]0.579272116546792[/C][/ROW]
[ROW][C]17[/C][C]2.5[/C][C]3.17378170082284[/C][C]0.0332661816924701[/C][C]1.79295211748469[/C][C]0.673781700822841[/C][/ROW]
[ROW][C]18[/C][C]1.6[/C][C]1.44963174838331[/C][C]0.0397558279070061[/C][C]1.71061242370968[/C][C]-0.150368251616689[/C][/ROW]
[ROW][C]19[/C][C]1.4[/C][C]1.13457263965367[/C][C]0.0371546304116564[/C][C]1.62827272993468[/C][C]-0.265427360346333[/C][/ROW]
[ROW][C]20[/C][C]0.8[/C][C]0.0258985125379623[/C][C]0.0324807609173898[/C][C]1.54162072654465[/C][C]-0.774101487462038[/C][/ROW]
[ROW][C]21[/C][C]1.1[/C][C]0.744497226764065[/C][C]0.00053405008131601[/C][C]1.45496872315462[/C][C]-0.355502773235935[/C][/ROW]
[ROW][C]22[/C][C]1.3[/C][C]1.22754906449417[/C][C]-0.0165741770362897[/C][C]1.38902511254212[/C][C]-0.0724509355058292[/C][/ROW]
[ROW][C]23[/C][C]1.2[/C][C]1.1560555214063[/C][C]-0.0791370233359205[/C][C]1.32308150192962[/C][C]-0.0439444785936978[/C][/ROW]
[ROW][C]24[/C][C]1.3[/C][C]1.37207445395562[/C][C]-0.0786721849409586[/C][C]1.30659773098534[/C][C]0.072074453955618[/C][/ROW]
[ROW][C]25[/C][C]1.1[/C][C]0.92677806615009[/C][C]-0.0168920261911527[/C][C]1.29011396004106[/C][C]-0.17322193384991[/C][/ROW]
[ROW][C]26[/C][C]1.3[/C][C]1.29047606612266[/C][C]0.00266462091348478[/C][C]1.30685931296386[/C][C]-0.00952393387734163[/C][/ROW]
[ROW][C]27[/C][C]1.2[/C][C]1.05417425389197[/C][C]0.0222210802213765[/C][C]1.32360466588665[/C][C]-0.145825746108027[/C][/ROW]
[ROW][C]28[/C][C]1.6[/C][C]1.82820741913905[/C][C]0.0231982529212557[/C][C]1.34859432793969[/C][C]0.228207419139054[/C][/ROW]
[ROW][C]29[/C][C]1.7[/C][C]1.9931498283148[/C][C]0.0332661816924701[/C][C]1.37358398999273[/C][C]0.293149828314801[/C][/ROW]
[ROW][C]30[/C][C]1.5[/C][C]1.5548169137375[/C][C]0.0397558279070061[/C][C]1.40542725835549[/C][C]0.0548169137375036[/C][/ROW]
[ROW][C]31[/C][C]0.9[/C][C]0.325574842870092[/C][C]0.0371546304116564[/C][C]1.43727052671825[/C][C]-0.574425157129908[/C][/ROW]
[ROW][C]32[/C][C]1.5[/C][C]1.50617055170742[/C][C]0.0324807609173898[/C][C]1.46134868737519[/C][C]0.00617055170741554[/C][/ROW]
[ROW][C]33[/C][C]1.4[/C][C]1.31403910188655[/C][C]0.00053405008131601[/C][C]1.48542684803214[/C][C]-0.0859608981134534[/C][/ROW]
[ROW][C]34[/C][C]1.6[/C][C]1.73013159081381[/C][C]-0.0165741770362897[/C][C]1.48644258622248[/C][C]0.130131590813805[/C][/ROW]
[ROW][C]35[/C][C]1.7[/C][C]1.99167869892309[/C][C]-0.0791370233359205[/C][C]1.48745832441283[/C][C]0.291678698923088[/C][/ROW]
[ROW][C]36[/C][C]1.4[/C][C]1.37469793006561[/C][C]-0.0786721849409586[/C][C]1.50397425487535[/C][C]-0.0253020699343884[/C][/ROW]
[ROW][C]37[/C][C]1.8[/C][C]2.09640184085329[/C][C]-0.0168920261911527[/C][C]1.52049018533786[/C][C]0.296401840853291[/C][/ROW]
[ROW][C]38[/C][C]1.7[/C][C]1.83403477585637[/C][C]0.00266462091348478[/C][C]1.56330060323014[/C][C]0.134034775856372[/C][/ROW]
[ROW][C]39[/C][C]1.4[/C][C]1.1716678986562[/C][C]0.0222210802213765[/C][C]1.60611102112242[/C][C]-0.2283321013438[/C][/ROW]
[ROW][C]40[/C][C]1.2[/C][C]0.725458065731011[/C][C]0.0231982529212557[/C][C]1.65134368134773[/C][C]-0.474541934268989[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.270157476734486[/C][C]0.0332661816924701[/C][C]1.69657634157304[/C][C]-0.729842523265514[/C][/ROW]
[ROW][C]42[/C][C]1.7[/C][C]1.60688206593166[/C][C]0.0397558279070061[/C][C]1.75336210616133[/C][C]-0.0931179340683357[/C][/ROW]
[ROW][C]43[/C][C]2.4[/C][C]2.95269749883873[/C][C]0.0371546304116564[/C][C]1.81014787074961[/C][C]0.552697498838729[/C][/ROW]
[ROW][C]44[/C][C]2[/C][C]2.08998917805259[/C][C]0.0324807609173898[/C][C]1.87753006103002[/C][C]0.0899891780525908[/C][/ROW]
[ROW][C]45[/C][C]2.1[/C][C]2.25455369860826[/C][C]0.00053405008131601[/C][C]1.94491225131042[/C][C]0.15455369860826[/C][/ROW]
[ROW][C]46[/C][C]2[/C][C]1.99587400339382[/C][C]-0.0165741770362897[/C][C]2.02070017364247[/C][C]-0.00412599660618485[/C][/ROW]
[ROW][C]47[/C][C]1.8[/C][C]1.5826489273614[/C][C]-0.0791370233359205[/C][C]2.09648809597452[/C][C]-0.217351072638604[/C][/ROW]
[ROW][C]48[/C][C]2.7[/C][C]3.32406615726232[/C][C]-0.0786721849409586[/C][C]2.15460602767863[/C][C]0.624066157262324[/C][/ROW]
[ROW][C]49[/C][C]2.3[/C][C]2.40416806680841[/C][C]-0.0168920261911527[/C][C]2.21272395938274[/C][C]0.104168066808408[/C][/ROW]
[ROW][C]50[/C][C]1.9[/C][C]1.53921456028979[/C][C]0.00266462091348478[/C][C]2.25812081879672[/C][C]-0.360785439710209[/C][/ROW]
[ROW][C]51[/C][C]2[/C][C]1.67426124156792[/C][C]0.0222210802213765[/C][C]2.3035176782107[/C][C]-0.325738758432079[/C][/ROW]
[ROW][C]52[/C][C]2.3[/C][C]2.22039425868989[/C][C]0.0231982529212557[/C][C]2.35640748838885[/C][C]-0.0796057413101057[/C][/ROW]
[ROW][C]53[/C][C]2.8[/C][C]3.15743651974053[/C][C]0.0332661816924701[/C][C]2.409297298567[/C][C]0.357436519740532[/C][/ROW]
[ROW][C]54[/C][C]2.4[/C][C]2.30859208309138[/C][C]0.0397558279070061[/C][C]2.45165208900161[/C][C]-0.0914079169086159[/C][/ROW]
[ROW][C]55[/C][C]2.3[/C][C]2.06883849015212[/C][C]0.0371546304116564[/C][C]2.49400687943622[/C][C]-0.231161509847879[/C][/ROW]
[ROW][C]56[/C][C]2.7[/C][C]2.8346033328601[/C][C]0.0324807609173898[/C][C]2.53291590622251[/C][C]0.134603332860099[/C][/ROW]
[ROW][C]57[/C][C]2.7[/C][C]2.82764101690988[/C][C]0.00053405008131601[/C][C]2.5718249330088[/C][C]0.127641016909884[/C][/ROW]
[ROW][C]58[/C][C]2.9[/C][C]3.2202158146073[/C][C]-0.0165741770362897[/C][C]2.59635836242899[/C][C]0.320215814607299[/C][/ROW]
[ROW][C]59[/C][C]3[/C][C]3.45824523148674[/C][C]-0.0791370233359205[/C][C]2.62089179184918[/C][C]0.45824523148674[/C][/ROW]
[ROW][C]60[/C][C]2.2[/C][C]1.85310279436382[/C][C]-0.0786721849409586[/C][C]2.62556939057714[/C][C]-0.34689720563618[/C][/ROW]
[ROW][C]61[/C][C]2.3[/C][C]1.98664503688605[/C][C]-0.0168920261911527[/C][C]2.6302469893051[/C][C]-0.313354963113945[/C][/ROW]
[ROW][C]62[/C][C]2.8[/C][C]2.98056153669232[/C][C]0.00266462091348478[/C][C]2.6167738423942[/C][C]0.180561536692315[/C][/ROW]
[ROW][C]63[/C][C]2.8[/C][C]2.97447822429532[/C][C]0.0222210802213765[/C][C]2.6033006954833[/C][C]0.174478224295322[/C][/ROW]
[ROW][C]64[/C][C]2.8[/C][C]3.01151738688313[/C][C]0.0231982529212557[/C][C]2.56528436019562[/C][C]0.211517386883128[/C][/ROW]
[ROW][C]65[/C][C]2.2[/C][C]1.8394657933996[/C][C]0.0332661816924701[/C][C]2.52726802490793[/C][C]-0.3605342066004[/C][/ROW]
[ROW][C]66[/C][C]2.6[/C][C]2.6851450909383[/C][C]0.0397558279070061[/C][C]2.47509908115469[/C][C]0.0851450909383011[/C][/ROW]
[ROW][C]67[/C][C]2.8[/C][C]3.13991523218689[/C][C]0.0371546304116564[/C][C]2.42293013740146[/C][C]0.339915232186887[/C][/ROW]
[ROW][C]68[/C][C]2.5[/C][C]2.60801801297964[/C][C]0.0324807609173898[/C][C]2.35950122610297[/C][C]0.108018012979636[/C][/ROW]
[ROW][C]69[/C][C]2.4[/C][C]2.50339363511419[/C][C]0.00053405008131601[/C][C]2.29607231480449[/C][C]0.103393635114193[/C][/ROW]
[ROW][C]70[/C][C]2.3[/C][C]2.3934068442769[/C][C]-0.0165741770362897[/C][C]2.22316733275939[/C][C]0.093406844276902[/C][/ROW]
[ROW][C]71[/C][C]1.9[/C][C]1.72887467262164[/C][C]-0.0791370233359205[/C][C]2.15026235071428[/C][C]-0.171125327378364[/C][/ROW]
[ROW][C]72[/C][C]1.7[/C][C]1.40978779596017[/C][C]-0.0786721849409586[/C][C]2.06888438898079[/C][C]-0.290212204039828[/C][/ROW]
[ROW][C]73[/C][C]2[/C][C]2.02938559894386[/C][C]-0.0168920261911527[/C][C]1.98750642724729[/C][C]0.0293855989438625[/C][/ROW]
[ROW][C]74[/C][C]2.1[/C][C]2.30084689530088[/C][C]0.00266462091348478[/C][C]1.89648848378564[/C][C]0.200846895300879[/C][/ROW]
[ROW][C]75[/C][C]1.7[/C][C]1.57230837945464[/C][C]0.0222210802213765[/C][C]1.80547054032398[/C][C]-0.127691620545359[/C][/ROW]
[ROW][C]76[/C][C]1.8[/C][C]1.83933300963266[/C][C]0.0231982529212557[/C][C]1.73746873744609[/C][C]0.0393330096326565[/C][/ROW]
[ROW][C]77[/C][C]1.8[/C][C]1.89726688373934[/C][C]0.0332661816924701[/C][C]1.66946693456819[/C][C]0.0972668837393369[/C][/ROW]
[ROW][C]78[/C][C]1.8[/C][C]1.89065482275474[/C][C]0.0397558279070061[/C][C]1.66958934933826[/C][C]0.090654822754735[/C][/ROW]
[ROW][C]79[/C][C]1.3[/C][C]0.893133605480019[/C][C]0.0371546304116564[/C][C]1.66971176410832[/C][C]-0.406866394519981[/C][/ROW]
[ROW][C]80[/C][C]1.3[/C][C]0.812470106797464[/C][C]0.0324807609173898[/C][C]1.75504913228515[/C][C]-0.487529893202536[/C][/ROW]
[ROW][C]81[/C][C]1.3[/C][C]0.759079449456716[/C][C]0.00053405008131601[/C][C]1.84038650046197[/C][C]-0.540920550543284[/C][/ROW]
[ROW][C]82[/C][C]1.2[/C][C]0.404076783602577[/C][C]-0.0165741770362897[/C][C]2.01249739343371[/C][C]-0.795923216397423[/C][/ROW]
[ROW][C]83[/C][C]1.4[/C][C]0.694528736930462[/C][C]-0.0791370233359205[/C][C]2.18460828640546[/C][C]-0.705471263069537[/C][/ROW]
[ROW][C]84[/C][C]2.2[/C][C]2.03243854523193[/C][C]-0.0786721849409586[/C][C]2.44623363970903[/C][C]-0.167561454768073[/C][/ROW]
[ROW][C]85[/C][C]2.9[/C][C]3.10903303317855[/C][C]-0.0168920261911527[/C][C]2.7078589930126[/C][C]0.209033033178548[/C][/ROW]
[ROW][C]86[/C][C]3.1[/C][C]3.14146852748663[/C][C]0.00266462091348478[/C][C]3.05586685159988[/C][C]0.0414685274866349[/C][/ROW]
[ROW][C]87[/C][C]3.5[/C][C]3.57390420959147[/C][C]0.0222210802213765[/C][C]3.40387471018716[/C][C]0.0739042095914684[/C][/ROW]
[ROW][C]88[/C][C]3.6[/C][C]3.42473868113781[/C][C]0.0231982529212557[/C][C]3.75206306594093[/C][C]-0.175261318862185[/C][/ROW]
[ROW][C]89[/C][C]4.4[/C][C]4.66648239661283[/C][C]0.0332661816924701[/C][C]4.1002514216947[/C][C]0.266482396612826[/C][/ROW]
[ROW][C]90[/C][C]4.1[/C][C]3.84440347651073[/C][C]0.0397558279070061[/C][C]4.31584069558226[/C][C]-0.255596523489269[/C][/ROW]
[ROW][C]91[/C][C]5.1[/C][C]5.63141540011852[/C][C]0.0371546304116564[/C][C]4.53142996946982[/C][C]0.531415400118523[/C][/ROW]
[ROW][C]92[/C][C]5.8[/C][C]7.02589704033855[/C][C]0.0324807609173898[/C][C]4.54162219874406[/C][C]1.22589704033855[/C][/ROW]
[ROW][C]93[/C][C]5.9[/C][C]7.24765152190038[/C][C]0.00053405008131601[/C][C]4.5518144280183[/C][C]1.34765152190038[/C][/ROW]
[ROW][C]94[/C][C]5.4[/C][C]6.45513225415962[/C][C]-0.0165741770362897[/C][C]4.36144192287667[/C][C]1.05513225415962[/C][/ROW]
[ROW][C]95[/C][C]5.5[/C][C]6.90806760560088[/C][C]-0.0791370233359205[/C][C]4.17106941773504[/C][C]1.40806760560088[/C][/ROW]
[ROW][C]96[/C][C]4.8[/C][C]5.89135238013707[/C][C]-0.0786721849409586[/C][C]3.78731980480388[/C][C]1.09135238013707[/C][/ROW]
[ROW][C]97[/C][C]3.2[/C][C]3.01332183431842[/C][C]-0.0168920261911527[/C][C]3.40357019187273[/C][C]-0.186678165681577[/C][/ROW]
[ROW][C]98[/C][C]2.7[/C][C]2.53781710242236[/C][C]0.00266462091348478[/C][C]2.85951827666416[/C][C]-0.162182897577643[/C][/ROW]
[ROW][C]99[/C][C]2.1[/C][C]1.86231255832304[/C][C]0.0222210802213765[/C][C]2.31546636145559[/C][C]-0.237687441676963[/C][/ROW]
[ROW][C]100[/C][C]1.9[/C][C]2.025717901055[/C][C]0.0231982529212557[/C][C]1.75108384602375[/C][C]0.125717901054999[/C][/ROW]
[ROW][C]101[/C][C]0.6[/C][C]-0.019967512284374[/C][C]0.0332661816924701[/C][C]1.1867013305919[/C][C]-0.619967512284374[/C][/ROW]
[ROW][C]102[/C][C]0.7[/C][C]0.605153184616915[/C][C]0.0397558279070061[/C][C]0.755090987476078[/C][C]-0.0948468153830845[/C][/ROW]
[ROW][C]103[/C][C]-0.2[/C][C]-0.760635274771909[/C][C]0.0371546304116564[/C][C]0.323480644360253[/C][C]-0.560635274771909[/C][/ROW]
[ROW][C]104[/C][C]-1[/C][C]-2.12945452989095[/C][C]0.0324807609173898[/C][C]0.0969737689735608[/C][C]-1.12945452989095[/C][/ROW]
[ROW][C]105[/C][C]-1.7[/C][C]-3.27100094366818[/C][C]0.00053405008131601[/C][C]-0.129533106413131[/C][C]-1.57100094366818[/C][/ROW]
[ROW][C]106[/C][C]-0.7[/C][C]-1.22625316349196[/C][C]-0.0165741770362897[/C][C]-0.157172659471749[/C][C]-0.526253163491962[/C][/ROW]
[ROW][C]107[/C][C]-1[/C][C]-1.73605076413371[/C][C]-0.0791370233359205[/C][C]-0.184812212530366[/C][C]-0.736050764133713[/C][/ROW]
[ROW][C]108[/C][C]-0.9[/C][C]-1.70086480982594[/C][C]-0.0786721849409586[/C][C]-0.020463005233099[/C][C]-0.800864809825943[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]-0.126994175873016[/C][C]-0.0168920261911527[/C][C]0.143886202064168[/C][C]-0.126994175873016[/C][/ROW]
[ROW][C]110[/C][C]0.3[/C][C]0.160701366716683[/C][C]0.00266462091348478[/C][C]0.436634012369832[/C][C]-0.139298633283317[/C][/ROW]
[ROW][C]111[/C][C]0.8[/C][C]0.848397097103128[/C][C]0.0222210802213765[/C][C]0.729381822675496[/C][C]0.0483970971031276[/C][/ROW]
[ROW][C]112[/C][C]0.8[/C][C]0.523736477662981[/C][C]0.0231982529212557[/C][C]1.05306526941576[/C][C]-0.276263522337019[/C][/ROW]
[ROW][C]113[/C][C]1.9[/C][C]2.3899851021515[/C][C]0.0332661816924701[/C][C]1.37674871615603[/C][C]0.489985102151499[/C][/ROW]
[ROW][C]114[/C][C]2.1[/C][C]2.48812307687592[/C][C]0.0397558279070061[/C][C]1.67212109521708[/C][C]0.388123076875919[/C][/ROW]
[ROW][C]115[/C][C]2.5[/C][C]2.99535189531022[/C][C]0.0371546304116564[/C][C]1.96749347427812[/C][C]0.495351895310223[/C][/ROW]
[ROW][C]116[/C][C]2.7[/C][C]3.15036447293197[/C][C]0.0324807609173898[/C][C]2.21715476615064[/C][C]0.45036447293197[/C][/ROW]
[ROW][C]117[/C][C]2.4[/C][C]2.33264989189552[/C][C]0.00053405008131601[/C][C]2.46681605802316[/C][C]-0.0673501081044754[/C][/ROW]
[ROW][C]118[/C][C]2.4[/C][C]2.16323795174238[/C][C]-0.0165741770362897[/C][C]2.65333622529391[/C][C]-0.236762048257622[/C][/ROW]
[ROW][C]119[/C][C]2.9[/C][C]3.03928063077126[/C][C]-0.0791370233359205[/C][C]2.83985639256466[/C][C]0.139280630771256[/C][/ROW]
[ROW][C]120[/C][C]3.1[/C][C]3.32348475866903[/C][C]-0.0786721849409586[/C][C]2.95518742627193[/C][C]0.223484758669029[/C][/ROW]
[ROW][C]121[/C][C]3[/C][C]2.94637356621196[/C][C]-0.0168920261911527[/C][C]3.07051845997919[/C][C]-0.0536264337880419[/C][/ROW]
[ROW][C]122[/C][C]3.4[/C][C]3.64363085286487[/C][C]0.00266462091348478[/C][C]3.15370452622164[/C][C]0.243630852864872[/C][/ROW]
[ROW][C]123[/C][C]3.7[/C][C]4.14088832731453[/C][C]0.0222210802213765[/C][C]3.23689059246409[/C][C]0.440888327314533[/C][/ROW]
[ROW][C]124[/C][C]3.5[/C][C]3.69045418361946[/C][C]0.0231982529212557[/C][C]3.28634756345928[/C][C]0.19045418361946[/C][/ROW]
[ROW][C]125[/C][C]3.5[/C][C]3.63092928385305[/C][C]0.0332661816924701[/C][C]3.33580453445448[/C][C]0.130929283853054[/C][/ROW]
[ROW][C]126[/C][C]3.3[/C][C]3.18219291811638[/C][C]0.0397558279070061[/C][C]3.37805125397661[/C][C]-0.117807081883616[/C][/ROW]
[ROW][C]127[/C][C]3.1[/C][C]2.7425473960896[/C][C]0.0371546304116564[/C][C]3.42029797349874[/C][C]-0.357452603910399[/C][/ROW]
[ROW][C]128[/C][C]3.4[/C][C]3.31017392796558[/C][C]0.0324807609173898[/C][C]3.45734531111703[/C][C]-0.0898260720344202[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]4.50507330118337[/C][C]0.00053405008131601[/C][C]3.49439264873532[/C][C]0.505073301183367[/C][/ROW]
[ROW][C]130[/C][C]3.4[/C][C]3.28829976340083[/C][C]-0.0165741770362897[/C][C]3.52827441363546[/C][C]-0.11170023659917[/C][/ROW]
[ROW][C]131[/C][C]3.4[/C][C]3.31698084480032[/C][C]-0.0791370233359205[/C][C]3.5621561785356[/C][C]-0.0830191551996822[/C][/ROW]
[ROW][C]132[/C][C]3.4[/C][C]3.28473946089004[/C][C]-0.0786721849409586[/C][C]3.59393272405092[/C][C]-0.115260539109961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158530&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158530&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Seasonal Decomposition by Loess - Time Series Components
t	Observed	Fitted	Seasonal	Trend	Remainder
1	3.7	4.29088093253315	-0.0168920261911527	3.126011093658	0.590880932533152
2	3	2.95031895721795	0.00266462091348478	3.04701642186856	-0.0496810427820455
3	2.7	2.4097571696995	0.0222210802213765	2.96802175007912	-0.290242830300497
4	2.5	2.0894505207865	0.0231982529212557	2.88735122629225	-0.410549479213501
5	2.2	1.56005311580216	0.0332661816924701	2.80668070250537	-0.63994688419784
6	2.9	3.03665621374774	0.0397558279070061	2.72358795834526	0.136656213747738
7	3.1	3.5223501554032	0.0371546304116564	2.64049521418514	0.422350155403202
8	3	3.40260752552303	0.0324807609173898	2.56491171355958	0.402607525523029
9	2.8	3.11013773698466	0.00053405008131601	2.48932821293402	0.310137736984665
10	2.5	2.57203475377633	-0.0165741770362897	2.44453942325996	0.0720347537763275
11	1.9	1.47938638975002	-0.0791370233359205	2.39975063358591	-0.420613610249985
12	1.9	1.55619018392186	-0.0786721849409586	2.3224820010191	-0.343809816078139
13	1.8	1.37167865773886	-0.0168920261911527	2.24521336845229	-0.428321342261136
14	2	1.87367512307076	0.00266462091348478	2.12366025601575	-0.126324876929238
15	2.6	3.17567177619941	0.0222210802213765	2.00210714357922	0.575671776199408
16	2.5	3.07927211654679	0.0231982529212557	1.89752963053195	0.579272116546792
17	2.5	3.17378170082284	0.0332661816924701	1.79295211748469	0.673781700822841
18	1.6	1.44963174838331	0.0397558279070061	1.71061242370968	-0.150368251616689
19	1.4	1.13457263965367	0.0371546304116564	1.62827272993468	-0.265427360346333
20	0.8	0.0258985125379623	0.0324807609173898	1.54162072654465	-0.774101487462038
21	1.1	0.744497226764065	0.00053405008131601	1.45496872315462	-0.355502773235935
22	1.3	1.22754906449417	-0.0165741770362897	1.38902511254212	-0.0724509355058292
23	1.2	1.1560555214063	-0.0791370233359205	1.32308150192962	-0.0439444785936978
24	1.3	1.37207445395562	-0.0786721849409586	1.30659773098534	0.072074453955618
25	1.1	0.92677806615009	-0.0168920261911527	1.29011396004106	-0.17322193384991
26	1.3	1.29047606612266	0.00266462091348478	1.30685931296386	-0.00952393387734163
27	1.2	1.05417425389197	0.0222210802213765	1.32360466588665	-0.145825746108027
28	1.6	1.82820741913905	0.0231982529212557	1.34859432793969	0.228207419139054
29	1.7	1.9931498283148	0.0332661816924701	1.37358398999273	0.293149828314801
30	1.5	1.5548169137375	0.0397558279070061	1.40542725835549	0.0548169137375036
31	0.9	0.325574842870092	0.0371546304116564	1.43727052671825	-0.574425157129908
32	1.5	1.50617055170742	0.0324807609173898	1.46134868737519	0.00617055170741554
33	1.4	1.31403910188655	0.00053405008131601	1.48542684803214	-0.0859608981134534
34	1.6	1.73013159081381	-0.0165741770362897	1.48644258622248	0.130131590813805
35	1.7	1.99167869892309	-0.0791370233359205	1.48745832441283	0.291678698923088
36	1.4	1.37469793006561	-0.0786721849409586	1.50397425487535	-0.0253020699343884
37	1.8	2.09640184085329	-0.0168920261911527	1.52049018533786	0.296401840853291
38	1.7	1.83403477585637	0.00266462091348478	1.56330060323014	0.134034775856372
39	1.4	1.1716678986562	0.0222210802213765	1.60611102112242	-0.2283321013438
40	1.2	0.725458065731011	0.0231982529212557	1.65134368134773	-0.474541934268989
41	1	0.270157476734486	0.0332661816924701	1.69657634157304	-0.729842523265514
42	1.7	1.60688206593166	0.0397558279070061	1.75336210616133	-0.0931179340683357
43	2.4	2.95269749883873	0.0371546304116564	1.81014787074961	0.552697498838729
44	2	2.08998917805259	0.0324807609173898	1.87753006103002	0.0899891780525908
45	2.1	2.25455369860826	0.00053405008131601	1.94491225131042	0.15455369860826
46	2	1.99587400339382	-0.0165741770362897	2.02070017364247	-0.00412599660618485
47	1.8	1.5826489273614	-0.0791370233359205	2.09648809597452	-0.217351072638604
48	2.7	3.32406615726232	-0.0786721849409586	2.15460602767863	0.624066157262324
49	2.3	2.40416806680841	-0.0168920261911527	2.21272395938274	0.104168066808408
50	1.9	1.53921456028979	0.00266462091348478	2.25812081879672	-0.360785439710209
51	2	1.67426124156792	0.0222210802213765	2.3035176782107	-0.325738758432079
52	2.3	2.22039425868989	0.0231982529212557	2.35640748838885	-0.0796057413101057
53	2.8	3.15743651974053	0.0332661816924701	2.409297298567	0.357436519740532
54	2.4	2.30859208309138	0.0397558279070061	2.45165208900161	-0.0914079169086159
55	2.3	2.06883849015212	0.0371546304116564	2.49400687943622	-0.231161509847879
56	2.7	2.8346033328601	0.0324807609173898	2.53291590622251	0.134603332860099
57	2.7	2.82764101690988	0.00053405008131601	2.5718249330088	0.127641016909884
58	2.9	3.2202158146073	-0.0165741770362897	2.59635836242899	0.320215814607299
59	3	3.45824523148674	-0.0791370233359205	2.62089179184918	0.45824523148674
60	2.2	1.85310279436382	-0.0786721849409586	2.62556939057714	-0.34689720563618
61	2.3	1.98664503688605	-0.0168920261911527	2.6302469893051	-0.313354963113945
62	2.8	2.98056153669232	0.00266462091348478	2.6167738423942	0.180561536692315
63	2.8	2.97447822429532	0.0222210802213765	2.6033006954833	0.174478224295322
64	2.8	3.01151738688313	0.0231982529212557	2.56528436019562	0.211517386883128
65	2.2	1.8394657933996	0.0332661816924701	2.52726802490793	-0.3605342066004
66	2.6	2.6851450909383	0.0397558279070061	2.47509908115469	0.0851450909383011
67	2.8	3.13991523218689	0.0371546304116564	2.42293013740146	0.339915232186887
68	2.5	2.60801801297964	0.0324807609173898	2.35950122610297	0.108018012979636
69	2.4	2.50339363511419	0.00053405008131601	2.29607231480449	0.103393635114193
70	2.3	2.3934068442769	-0.0165741770362897	2.22316733275939	0.093406844276902
71	1.9	1.72887467262164	-0.0791370233359205	2.15026235071428	-0.171125327378364
72	1.7	1.40978779596017	-0.0786721849409586	2.06888438898079	-0.290212204039828
73	2	2.02938559894386	-0.0168920261911527	1.98750642724729	0.0293855989438625
74	2.1	2.30084689530088	0.00266462091348478	1.89648848378564	0.200846895300879
75	1.7	1.57230837945464	0.0222210802213765	1.80547054032398	-0.127691620545359
76	1.8	1.83933300963266	0.0231982529212557	1.73746873744609	0.0393330096326565
77	1.8	1.89726688373934	0.0332661816924701	1.66946693456819	0.0972668837393369
78	1.8	1.89065482275474	0.0397558279070061	1.66958934933826	0.090654822754735
79	1.3	0.893133605480019	0.0371546304116564	1.66971176410832	-0.406866394519981
80	1.3	0.812470106797464	0.0324807609173898	1.75504913228515	-0.487529893202536
81	1.3	0.759079449456716	0.00053405008131601	1.84038650046197	-0.540920550543284
82	1.2	0.404076783602577	-0.0165741770362897	2.01249739343371	-0.795923216397423
83	1.4	0.694528736930462	-0.0791370233359205	2.18460828640546	-0.705471263069537
84	2.2	2.03243854523193	-0.0786721849409586	2.44623363970903	-0.167561454768073
85	2.9	3.10903303317855	-0.0168920261911527	2.7078589930126	0.209033033178548
86	3.1	3.14146852748663	0.00266462091348478	3.05586685159988	0.0414685274866349
87	3.5	3.57390420959147	0.0222210802213765	3.40387471018716	0.0739042095914684
88	3.6	3.42473868113781	0.0231982529212557	3.75206306594093	-0.175261318862185
89	4.4	4.66648239661283	0.0332661816924701	4.1002514216947	0.266482396612826
90	4.1	3.84440347651073	0.0397558279070061	4.31584069558226	-0.255596523489269
91	5.1	5.63141540011852	0.0371546304116564	4.53142996946982	0.531415400118523
92	5.8	7.02589704033855	0.0324807609173898	4.54162219874406	1.22589704033855
93	5.9	7.24765152190038	0.00053405008131601	4.5518144280183	1.34765152190038
94	5.4	6.45513225415962	-0.0165741770362897	4.36144192287667	1.05513225415962
95	5.5	6.90806760560088	-0.0791370233359205	4.17106941773504	1.40806760560088
96	4.8	5.89135238013707	-0.0786721849409586	3.78731980480388	1.09135238013707
97	3.2	3.01332183431842	-0.0168920261911527	3.40357019187273	-0.186678165681577
98	2.7	2.53781710242236	0.00266462091348478	2.85951827666416	-0.162182897577643
99	2.1	1.86231255832304	0.0222210802213765	2.31546636145559	-0.237687441676963
100	1.9	2.025717901055	0.0231982529212557	1.75108384602375	0.125717901054999
101	0.6	-0.019967512284374	0.0332661816924701	1.1867013305919	-0.619967512284374
102	0.7	0.605153184616915	0.0397558279070061	0.755090987476078	-0.0948468153830845
103	-0.2	-0.760635274771909	0.0371546304116564	0.323480644360253	-0.560635274771909
104	-1	-2.12945452989095	0.0324807609173898	0.0969737689735608	-1.12945452989095
105	-1.7	-3.27100094366818	0.00053405008131601	-0.129533106413131	-1.57100094366818
106	-0.7	-1.22625316349196	-0.0165741770362897	-0.157172659471749	-0.526253163491962
107	-1	-1.73605076413371	-0.0791370233359205	-0.184812212530366	-0.736050764133713
108	-0.9	-1.70086480982594	-0.0786721849409586	-0.020463005233099	-0.800864809825943
109	0	-0.126994175873016	-0.0168920261911527	0.143886202064168	-0.126994175873016
110	0.3	0.160701366716683	0.00266462091348478	0.436634012369832	-0.139298633283317
111	0.8	0.848397097103128	0.0222210802213765	0.729381822675496	0.0483970971031276
112	0.8	0.523736477662981	0.0231982529212557	1.05306526941576	-0.276263522337019
113	1.9	2.3899851021515	0.0332661816924701	1.37674871615603	0.489985102151499
114	2.1	2.48812307687592	0.0397558279070061	1.67212109521708	0.388123076875919
115	2.5	2.99535189531022	0.0371546304116564	1.96749347427812	0.495351895310223
116	2.7	3.15036447293197	0.0324807609173898	2.21715476615064	0.45036447293197
117	2.4	2.33264989189552	0.00053405008131601	2.46681605802316	-0.0673501081044754
118	2.4	2.16323795174238	-0.0165741770362897	2.65333622529391	-0.236762048257622
119	2.9	3.03928063077126	-0.0791370233359205	2.83985639256466	0.139280630771256
120	3.1	3.32348475866903	-0.0786721849409586	2.95518742627193	0.223484758669029
121	3	2.94637356621196	-0.0168920261911527	3.07051845997919	-0.0536264337880419
122	3.4	3.64363085286487	0.00266462091348478	3.15370452622164	0.243630852864872
123	3.7	4.14088832731453	0.0222210802213765	3.23689059246409	0.440888327314533
124	3.5	3.69045418361946	0.0231982529212557	3.28634756345928	0.19045418361946
125	3.5	3.63092928385305	0.0332661816924701	3.33580453445448	0.130929283853054
126	3.3	3.18219291811638	0.0397558279070061	3.37805125397661	-0.117807081883616
127	3.1	2.7425473960896	0.0371546304116564	3.42029797349874	-0.357452603910399
128	3.4	3.31017392796558	0.0324807609173898	3.45734531111703	-0.0898260720344202
129	4	4.50507330118337	0.00053405008131601	3.49439264873532	0.505073301183367
130	3.4	3.28829976340083	-0.0165741770362897	3.52827441363546	-0.11170023659917
131	3.4	3.31698084480032	-0.0791370233359205	3.5621561785356	-0.0830191551996822
132	3.4	3.28473946089004	-0.0786721849409586	3.59393272405092	-0.115260539109961

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ; par2 = periodic ; par3 = 0 ; par4 = ; par5 = 1 ; par6 = ; par7 = 1 ; par8 = FALSE ;

R code (references can be found in the software module):

par1 <- as.numeric(par1) #seasonal period
if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
par3 <- as.numeric(par3) #s.degree
if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
par5 <- as.numeric(par5)#t.degree
if (par6 != '') par6 <- as.numeric(par6)#l.window
par7 <- as.numeric(par7)#l.degree
if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
nx <- length(x)
x <- ts(x,frequency=par1)
if (par6 != '') {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
} else {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
}
m$time.series
m$win
m$deg
m$jump
m$inner
m$outer
bitmap(file='test1.png')
plot(m,main=main)
dev.off()
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Component',header=TRUE)
a<-table.element(a,'Window',header=TRUE)
a<-table.element(a,'Degree',header=TRUE)
a<-table.element(a,'Jump',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,m$win['s'])
a<-table.element(a,m$deg['s'])
a<-table.element(a,m$jump['s'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,m$win['t'])
a<-table.element(a,m$deg['t'])
a<-table.element(a,m$jump['t'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Low-pass',header=TRUE)
a<-table.element(a,m$win['l'])
a<-table.element(a,m$deg['l'])
a<-table.element(a,m$jump['l'])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Fitted',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Remainder',header=TRUE)
a<-table.row.end(a)
for (i in 1:nx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]+m$time.series[i,'remainder'])
a<-table.element(a,m$time.series[i,'seasonal'])
a<-table.element(a,m$time.series[i,'trend'])
a<-table.element(a,m$time.series[i,'remainder'])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code