Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_decomposeloess.wasp

Title produced by software

Decomposition by Loess

Date of computation

Mon, 12 Nov 2012 10:02:13 -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/2012/Nov/12/t1352732539rm0g0vcf5vh90zf.htm/, Retrieved Sun, 28 Apr 2024 23:20:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=187993, Retrieved Sun, 28 Apr 2024 23:20:01 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Decomposition by Loess] [] [2012-11-12 14:28:58] [7a4d181f6fb11b759aaa32fc654b70bc]
- R P           [Decomposition by Loess] [] [2012-11-12 14:59:01] [7a4d181f6fb11b759aaa32fc654b70bc]
- R                 [Decomposition by Loess] [] [2012-11-12 15:02:13] [e76020e6634a79924d88182923277ec4] [Current]
- RMP                 [Classical Decomposition] [] [2012-11-12 15:32:35] [7a4d181f6fb11b759aaa32fc654b70bc] 
- R P                   [Classical Decomposition] [] [2012-11-12 15:52:55] [7a4d181f6fb11b759aaa32fc654b70bc] 

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187993&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187993&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187993&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	4 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Seasonal Decomposition by Loess - Parameters
Component	Window	Degree	Jump
Seasonal	751	0	76
Trend	11	1	2
Low-pass	7	1	1

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Parameters \tabularnewline
Component & Window & Degree & Jump \tabularnewline
Seasonal & 751 & 0 & 76 \tabularnewline
Trend & 11 & 1 & 2 \tabularnewline
Low-pass & 7 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187993&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]751[/C][C]0[/C][C]76[/C][/ROW]
[ROW][C]Trend[/C][C]11[/C][C]1[/C][C]2[/C][/ROW]
[ROW][C]Low-pass[/C][C]7[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187993&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187993&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	751	0	76
Trend	11	1	2
Low-pass	7	1	1

Seasonal Decomposition by Loess - Time Series Components
t	Observed	Fitted	Seasonal	Trend	Remainder
1	9700	10009.4125168222	52.1688095727502	9338.41867360501	309.412516822236
2	9081	9082.6576853216	-270.651560258269	9349.99387493667	1.65768532160291
3	9084	8915.89927959583	-109.468355864149	9361.56907626832	-168.100720404169
4	9743	9768.43176462172	327.463428436556	9390.10480694172	25.4317646217241
5	8587	7937.36951277889	-182.010050394014	9418.64053761512	-649.630487221108
6	9731	9790.63566698778	182.497919715837	9488.86641329638	59.6356669877823
7	9563	9514.73890144961	52.1688095727502	9559.09228897764	-48.2610985503889
8	9998	10628.6432570022	-270.651560258269	9638.00830325608	630.643257002186
9	9437	9266.54403832962	-109.468355864149	9716.92431753453	-170.455961670377
10	10038	10068.9836299535	327.463428436556	9679.55294160998	30.9836299534654
11	9918	10375.8284847086	-182.010050394014	9642.18156568543	457.828484708582
12	9252	8774.02015818712	182.497919715837	9547.48192209704	-477.979841812878
13	9737	9969.0489119186	52.1688095727502	9452.78227850865	232.048911918602
14	9035	8982.56170084463	-270.651560258269	9358.08985941364	-52.4382991553684
15	9133	9112.07091554552	-109.468355864149	9263.39744031863	-20.9290844544776
16	9487	9422.34788574634	327.463428436556	9224.18868581711	-64.6521142536621
17	8700	8397.03011907843	-182.010050394014	9184.97993131558	-302.96988092157
18	9627	9873.65505407779	182.497919715837	9197.84702620637	246.655054077792
19	8947	8631.11706933009	52.1688095727502	9210.71412109716	-315.882930669906
20	9283	9559.25542270526	-270.651560258269	9277.39613755301	276.255422705257
21	8829	8423.39020185528	-109.468355864149	9344.07815400887	-405.60979814472
22	9947	10204.5511440451	327.463428436556	9361.98542751836	257.551144045085
23	9628	10058.1173493662	-182.010050394014	9379.89270102785	430.117349366164
24	9318	9099.20781157755	182.497919715837	9354.29426870662	-218.792188422454
25	9605	9829.13535404187	52.1688095727502	9328.69583638538	224.135354041868
26	8640	8307.66748022911	-270.651560258269	9242.98408002916	-332.332519770891
27	9214	9380.19603219121	-109.468355864149	9157.27232367294	166.196032191212
28	9567	9656.28708895251	327.463428436556	9150.24948261093	89.2870889525129
29	8547	8132.78340884509	-182.010050394014	9143.22664154892	-414.216591154911
30	9185	8983.6738567326	182.497919715837	9203.82822355156	-201.326143267399
31	9470	9623.40138487305	52.1688095727502	9264.4298055542	153.401384873052
32	9123	9152.67239907504	-270.651560258269	9363.97916118323	29.6723990750379
33	9278	9201.93983905188	-109.468355864149	9463.52851681226	-76.0601609481164
34	10170	10534.9234523124	327.463428436556	9477.61311925109	364.923452312358
35	9434	9558.31232870411	-182.010050394014	9491.69772168991	124.312328704107
36	9655	9662.02249343573	182.497919715837	9465.47958684843	7.02249343573021
37	9429	9366.56973842029	52.1688095727502	9439.26145200696	-62.430261579706
38	8739	8352.05723092249	-270.651560258269	9396.59432933578	-386.942769077512
39	9552	9859.54114919954	-109.468355864149	9353.9272066646	307.541149199544
40	9687	9695.54094781109	327.463428436556	9350.99562375235	8.5409478110887
41	9019	8871.94600955391	-182.010050394014	9348.0640408401	-147.053990446089
42	9672	9750.95855175642	182.497919715837	9410.54352852774	78.9585517564246
43	9206	8886.80817421188	52.1688095727502	9473.02301621537	-319.191825788124
44	9069	8824.13069706809	-270.651560258269	9584.52086319018	-244.869302931911
45	9788	9989.44964569916	-109.468355864149	9696.01871016499	201.44964569916
46	10312	10540.8059992638	327.463428436556	9755.73057229965	228.80599926379
47	10105	10576.5676159597	-182.010050394014	9815.44243443432	471.567615959695
48	9863	9744.77420501589	182.497919715837	9798.72787526828	-118.225794984113
49	9656	9477.81787432502	52.1688095727502	9782.01331610223	-178.182125674983
50	9295	9150.41005834231	-270.651560258269	9710.24150191596	-144.589941657687
51	9946	10362.9986681345	-109.468355864149	9638.46968772968	416.998668134471
52	9701	9415.05229854673	327.463428436556	9659.48427301672	-285.947701453273
53	9049	8599.51119209026	-182.010050394014	9680.49885830376	-449.488807909742
54	10190	10471.0331893282	182.497919715837	9726.46889095599	281.033189328173
55	9706	9587.39226681903	52.1688095727502	9772.43892360822	-118.607733180974
56	9765	9931.65213684186	-270.651560258269	9868.99942341641	166.652136841858
57	9893	9929.90843263955	-109.468355864149	9965.5599232246	36.9084326395496
58	9994	9679.55731216093	327.463428436556	9980.97925940251	-314.442687839071
59	10433	11051.6114548136	-182.010050394014	9996.39859558043	618.611454813583
60	10073	10000.3758739415	182.497919715837	9963.12620634267	-72.6241260585066
61	10112	10241.9773733223	52.1688095727502	9929.85381710491	129.977373322345
62	9266	8940.50307948323	-270.651560258269	9862.14848077504	-325.496920516769
63	9820	9955.02521141898	-109.468355864149	9794.44314444517	135.025211418977
64	10097	10049.5032210833	327.463428436556	9817.03335048015	-47.4967789167058
65	9115	8572.38649387888	-182.010050394014	9839.62355651513	-542.613506121115
66	10411	10707.6753861052	182.497919715837	9931.82669417899	296.675386105173
67	9678	9279.8013585844	52.1688095727502	10024.0298318429	-398.1986414156
68	10408	10937.7724070502	-270.651560258269	10148.8791532081	529.77240705021
69	10153	10141.7398812909	-109.468355864149	10273.7284745733	-11.2601187091204
70	10368	10109.0218176703	327.463428436556	10299.5147538931	-258.978182329698
71	10581	11018.709017181	-182.010050394014	10325.301033213	437.709017180998
72	10597	10749.4648900049	182.497919715837	10262.0371902793	152.464890004861
73	10680	11109.0578430817	52.1688095727502	10198.7733473456	429.057843081664
74	9738	9624.52262190154	-270.651560258269	10122.1289383567	-113.47737809846
75	9556	9175.98382649628	-109.468355864149	10045.4845293679	-380.016173503724

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 9700 & 10009.4125168222 & 52.1688095727502 & 9338.41867360501 & 309.412516822236 \tabularnewline
2 & 9081 & 9082.6576853216 & -270.651560258269 & 9349.99387493667 & 1.65768532160291 \tabularnewline
3 & 9084 & 8915.89927959583 & -109.468355864149 & 9361.56907626832 & -168.100720404169 \tabularnewline
4 & 9743 & 9768.43176462172 & 327.463428436556 & 9390.10480694172 & 25.4317646217241 \tabularnewline
5 & 8587 & 7937.36951277889 & -182.010050394014 & 9418.64053761512 & -649.630487221108 \tabularnewline
6 & 9731 & 9790.63566698778 & 182.497919715837 & 9488.86641329638 & 59.6356669877823 \tabularnewline
7 & 9563 & 9514.73890144961 & 52.1688095727502 & 9559.09228897764 & -48.2610985503889 \tabularnewline
8 & 9998 & 10628.6432570022 & -270.651560258269 & 9638.00830325608 & 630.643257002186 \tabularnewline
9 & 9437 & 9266.54403832962 & -109.468355864149 & 9716.92431753453 & -170.455961670377 \tabularnewline
10 & 10038 & 10068.9836299535 & 327.463428436556 & 9679.55294160998 & 30.9836299534654 \tabularnewline
11 & 9918 & 10375.8284847086 & -182.010050394014 & 9642.18156568543 & 457.828484708582 \tabularnewline
12 & 9252 & 8774.02015818712 & 182.497919715837 & 9547.48192209704 & -477.979841812878 \tabularnewline
13 & 9737 & 9969.0489119186 & 52.1688095727502 & 9452.78227850865 & 232.048911918602 \tabularnewline
14 & 9035 & 8982.56170084463 & -270.651560258269 & 9358.08985941364 & -52.4382991553684 \tabularnewline
15 & 9133 & 9112.07091554552 & -109.468355864149 & 9263.39744031863 & -20.9290844544776 \tabularnewline
16 & 9487 & 9422.34788574634 & 327.463428436556 & 9224.18868581711 & -64.6521142536621 \tabularnewline
17 & 8700 & 8397.03011907843 & -182.010050394014 & 9184.97993131558 & -302.96988092157 \tabularnewline
18 & 9627 & 9873.65505407779 & 182.497919715837 & 9197.84702620637 & 246.655054077792 \tabularnewline
19 & 8947 & 8631.11706933009 & 52.1688095727502 & 9210.71412109716 & -315.882930669906 \tabularnewline
20 & 9283 & 9559.25542270526 & -270.651560258269 & 9277.39613755301 & 276.255422705257 \tabularnewline
21 & 8829 & 8423.39020185528 & -109.468355864149 & 9344.07815400887 & -405.60979814472 \tabularnewline
22 & 9947 & 10204.5511440451 & 327.463428436556 & 9361.98542751836 & 257.551144045085 \tabularnewline
23 & 9628 & 10058.1173493662 & -182.010050394014 & 9379.89270102785 & 430.117349366164 \tabularnewline
24 & 9318 & 9099.20781157755 & 182.497919715837 & 9354.29426870662 & -218.792188422454 \tabularnewline
25 & 9605 & 9829.13535404187 & 52.1688095727502 & 9328.69583638538 & 224.135354041868 \tabularnewline
26 & 8640 & 8307.66748022911 & -270.651560258269 & 9242.98408002916 & -332.332519770891 \tabularnewline
27 & 9214 & 9380.19603219121 & -109.468355864149 & 9157.27232367294 & 166.196032191212 \tabularnewline
28 & 9567 & 9656.28708895251 & 327.463428436556 & 9150.24948261093 & 89.2870889525129 \tabularnewline
29 & 8547 & 8132.78340884509 & -182.010050394014 & 9143.22664154892 & -414.216591154911 \tabularnewline
30 & 9185 & 8983.6738567326 & 182.497919715837 & 9203.82822355156 & -201.326143267399 \tabularnewline
31 & 9470 & 9623.40138487305 & 52.1688095727502 & 9264.4298055542 & 153.401384873052 \tabularnewline
32 & 9123 & 9152.67239907504 & -270.651560258269 & 9363.97916118323 & 29.6723990750379 \tabularnewline
33 & 9278 & 9201.93983905188 & -109.468355864149 & 9463.52851681226 & -76.0601609481164 \tabularnewline
34 & 10170 & 10534.9234523124 & 327.463428436556 & 9477.61311925109 & 364.923452312358 \tabularnewline
35 & 9434 & 9558.31232870411 & -182.010050394014 & 9491.69772168991 & 124.312328704107 \tabularnewline
36 & 9655 & 9662.02249343573 & 182.497919715837 & 9465.47958684843 & 7.02249343573021 \tabularnewline
37 & 9429 & 9366.56973842029 & 52.1688095727502 & 9439.26145200696 & -62.430261579706 \tabularnewline
38 & 8739 & 8352.05723092249 & -270.651560258269 & 9396.59432933578 & -386.942769077512 \tabularnewline
39 & 9552 & 9859.54114919954 & -109.468355864149 & 9353.9272066646 & 307.541149199544 \tabularnewline
40 & 9687 & 9695.54094781109 & 327.463428436556 & 9350.99562375235 & 8.5409478110887 \tabularnewline
41 & 9019 & 8871.94600955391 & -182.010050394014 & 9348.0640408401 & -147.053990446089 \tabularnewline
42 & 9672 & 9750.95855175642 & 182.497919715837 & 9410.54352852774 & 78.9585517564246 \tabularnewline
43 & 9206 & 8886.80817421188 & 52.1688095727502 & 9473.02301621537 & -319.191825788124 \tabularnewline
44 & 9069 & 8824.13069706809 & -270.651560258269 & 9584.52086319018 & -244.869302931911 \tabularnewline
45 & 9788 & 9989.44964569916 & -109.468355864149 & 9696.01871016499 & 201.44964569916 \tabularnewline
46 & 10312 & 10540.8059992638 & 327.463428436556 & 9755.73057229965 & 228.80599926379 \tabularnewline
47 & 10105 & 10576.5676159597 & -182.010050394014 & 9815.44243443432 & 471.567615959695 \tabularnewline
48 & 9863 & 9744.77420501589 & 182.497919715837 & 9798.72787526828 & -118.225794984113 \tabularnewline
49 & 9656 & 9477.81787432502 & 52.1688095727502 & 9782.01331610223 & -178.182125674983 \tabularnewline
50 & 9295 & 9150.41005834231 & -270.651560258269 & 9710.24150191596 & -144.589941657687 \tabularnewline
51 & 9946 & 10362.9986681345 & -109.468355864149 & 9638.46968772968 & 416.998668134471 \tabularnewline
52 & 9701 & 9415.05229854673 & 327.463428436556 & 9659.48427301672 & -285.947701453273 \tabularnewline
53 & 9049 & 8599.51119209026 & -182.010050394014 & 9680.49885830376 & -449.488807909742 \tabularnewline
54 & 10190 & 10471.0331893282 & 182.497919715837 & 9726.46889095599 & 281.033189328173 \tabularnewline
55 & 9706 & 9587.39226681903 & 52.1688095727502 & 9772.43892360822 & -118.607733180974 \tabularnewline
56 & 9765 & 9931.65213684186 & -270.651560258269 & 9868.99942341641 & 166.652136841858 \tabularnewline
57 & 9893 & 9929.90843263955 & -109.468355864149 & 9965.5599232246 & 36.9084326395496 \tabularnewline
58 & 9994 & 9679.55731216093 & 327.463428436556 & 9980.97925940251 & -314.442687839071 \tabularnewline
59 & 10433 & 11051.6114548136 & -182.010050394014 & 9996.39859558043 & 618.611454813583 \tabularnewline
60 & 10073 & 10000.3758739415 & 182.497919715837 & 9963.12620634267 & -72.6241260585066 \tabularnewline
61 & 10112 & 10241.9773733223 & 52.1688095727502 & 9929.85381710491 & 129.977373322345 \tabularnewline
62 & 9266 & 8940.50307948323 & -270.651560258269 & 9862.14848077504 & -325.496920516769 \tabularnewline
63 & 9820 & 9955.02521141898 & -109.468355864149 & 9794.44314444517 & 135.025211418977 \tabularnewline
64 & 10097 & 10049.5032210833 & 327.463428436556 & 9817.03335048015 & -47.4967789167058 \tabularnewline
65 & 9115 & 8572.38649387888 & -182.010050394014 & 9839.62355651513 & -542.613506121115 \tabularnewline
66 & 10411 & 10707.6753861052 & 182.497919715837 & 9931.82669417899 & 296.675386105173 \tabularnewline
67 & 9678 & 9279.8013585844 & 52.1688095727502 & 10024.0298318429 & -398.1986414156 \tabularnewline
68 & 10408 & 10937.7724070502 & -270.651560258269 & 10148.8791532081 & 529.77240705021 \tabularnewline
69 & 10153 & 10141.7398812909 & -109.468355864149 & 10273.7284745733 & -11.2601187091204 \tabularnewline
70 & 10368 & 10109.0218176703 & 327.463428436556 & 10299.5147538931 & -258.978182329698 \tabularnewline
71 & 10581 & 11018.709017181 & -182.010050394014 & 10325.301033213 & 437.709017180998 \tabularnewline
72 & 10597 & 10749.4648900049 & 182.497919715837 & 10262.0371902793 & 152.464890004861 \tabularnewline
73 & 10680 & 11109.0578430817 & 52.1688095727502 & 10198.7733473456 & 429.057843081664 \tabularnewline
74 & 9738 & 9624.52262190154 & -270.651560258269 & 10122.1289383567 & -113.47737809846 \tabularnewline
75 & 9556 & 9175.98382649628 & -109.468355864149 & 10045.4845293679 & -380.016173503724 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187993&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]9700[/C][C]10009.4125168222[/C][C]52.1688095727502[/C][C]9338.41867360501[/C][C]309.412516822236[/C][/ROW]
[ROW][C]2[/C][C]9081[/C][C]9082.6576853216[/C][C]-270.651560258269[/C][C]9349.99387493667[/C][C]1.65768532160291[/C][/ROW]
[ROW][C]3[/C][C]9084[/C][C]8915.89927959583[/C][C]-109.468355864149[/C][C]9361.56907626832[/C][C]-168.100720404169[/C][/ROW]
[ROW][C]4[/C][C]9743[/C][C]9768.43176462172[/C][C]327.463428436556[/C][C]9390.10480694172[/C][C]25.4317646217241[/C][/ROW]
[ROW][C]5[/C][C]8587[/C][C]7937.36951277889[/C][C]-182.010050394014[/C][C]9418.64053761512[/C][C]-649.630487221108[/C][/ROW]
[ROW][C]6[/C][C]9731[/C][C]9790.63566698778[/C][C]182.497919715837[/C][C]9488.86641329638[/C][C]59.6356669877823[/C][/ROW]
[ROW][C]7[/C][C]9563[/C][C]9514.73890144961[/C][C]52.1688095727502[/C][C]9559.09228897764[/C][C]-48.2610985503889[/C][/ROW]
[ROW][C]8[/C][C]9998[/C][C]10628.6432570022[/C][C]-270.651560258269[/C][C]9638.00830325608[/C][C]630.643257002186[/C][/ROW]
[ROW][C]9[/C][C]9437[/C][C]9266.54403832962[/C][C]-109.468355864149[/C][C]9716.92431753453[/C][C]-170.455961670377[/C][/ROW]
[ROW][C]10[/C][C]10038[/C][C]10068.9836299535[/C][C]327.463428436556[/C][C]9679.55294160998[/C][C]30.9836299534654[/C][/ROW]
[ROW][C]11[/C][C]9918[/C][C]10375.8284847086[/C][C]-182.010050394014[/C][C]9642.18156568543[/C][C]457.828484708582[/C][/ROW]
[ROW][C]12[/C][C]9252[/C][C]8774.02015818712[/C][C]182.497919715837[/C][C]9547.48192209704[/C][C]-477.979841812878[/C][/ROW]
[ROW][C]13[/C][C]9737[/C][C]9969.0489119186[/C][C]52.1688095727502[/C][C]9452.78227850865[/C][C]232.048911918602[/C][/ROW]
[ROW][C]14[/C][C]9035[/C][C]8982.56170084463[/C][C]-270.651560258269[/C][C]9358.08985941364[/C][C]-52.4382991553684[/C][/ROW]
[ROW][C]15[/C][C]9133[/C][C]9112.07091554552[/C][C]-109.468355864149[/C][C]9263.39744031863[/C][C]-20.9290844544776[/C][/ROW]
[ROW][C]16[/C][C]9487[/C][C]9422.34788574634[/C][C]327.463428436556[/C][C]9224.18868581711[/C][C]-64.6521142536621[/C][/ROW]
[ROW][C]17[/C][C]8700[/C][C]8397.03011907843[/C][C]-182.010050394014[/C][C]9184.97993131558[/C][C]-302.96988092157[/C][/ROW]
[ROW][C]18[/C][C]9627[/C][C]9873.65505407779[/C][C]182.497919715837[/C][C]9197.84702620637[/C][C]246.655054077792[/C][/ROW]
[ROW][C]19[/C][C]8947[/C][C]8631.11706933009[/C][C]52.1688095727502[/C][C]9210.71412109716[/C][C]-315.882930669906[/C][/ROW]
[ROW][C]20[/C][C]9283[/C][C]9559.25542270526[/C][C]-270.651560258269[/C][C]9277.39613755301[/C][C]276.255422705257[/C][/ROW]
[ROW][C]21[/C][C]8829[/C][C]8423.39020185528[/C][C]-109.468355864149[/C][C]9344.07815400887[/C][C]-405.60979814472[/C][/ROW]
[ROW][C]22[/C][C]9947[/C][C]10204.5511440451[/C][C]327.463428436556[/C][C]9361.98542751836[/C][C]257.551144045085[/C][/ROW]
[ROW][C]23[/C][C]9628[/C][C]10058.1173493662[/C][C]-182.010050394014[/C][C]9379.89270102785[/C][C]430.117349366164[/C][/ROW]
[ROW][C]24[/C][C]9318[/C][C]9099.20781157755[/C][C]182.497919715837[/C][C]9354.29426870662[/C][C]-218.792188422454[/C][/ROW]
[ROW][C]25[/C][C]9605[/C][C]9829.13535404187[/C][C]52.1688095727502[/C][C]9328.69583638538[/C][C]224.135354041868[/C][/ROW]
[ROW][C]26[/C][C]8640[/C][C]8307.66748022911[/C][C]-270.651560258269[/C][C]9242.98408002916[/C][C]-332.332519770891[/C][/ROW]
[ROW][C]27[/C][C]9214[/C][C]9380.19603219121[/C][C]-109.468355864149[/C][C]9157.27232367294[/C][C]166.196032191212[/C][/ROW]
[ROW][C]28[/C][C]9567[/C][C]9656.28708895251[/C][C]327.463428436556[/C][C]9150.24948261093[/C][C]89.2870889525129[/C][/ROW]
[ROW][C]29[/C][C]8547[/C][C]8132.78340884509[/C][C]-182.010050394014[/C][C]9143.22664154892[/C][C]-414.216591154911[/C][/ROW]
[ROW][C]30[/C][C]9185[/C][C]8983.6738567326[/C][C]182.497919715837[/C][C]9203.82822355156[/C][C]-201.326143267399[/C][/ROW]
[ROW][C]31[/C][C]9470[/C][C]9623.40138487305[/C][C]52.1688095727502[/C][C]9264.4298055542[/C][C]153.401384873052[/C][/ROW]
[ROW][C]32[/C][C]9123[/C][C]9152.67239907504[/C][C]-270.651560258269[/C][C]9363.97916118323[/C][C]29.6723990750379[/C][/ROW]
[ROW][C]33[/C][C]9278[/C][C]9201.93983905188[/C][C]-109.468355864149[/C][C]9463.52851681226[/C][C]-76.0601609481164[/C][/ROW]
[ROW][C]34[/C][C]10170[/C][C]10534.9234523124[/C][C]327.463428436556[/C][C]9477.61311925109[/C][C]364.923452312358[/C][/ROW]
[ROW][C]35[/C][C]9434[/C][C]9558.31232870411[/C][C]-182.010050394014[/C][C]9491.69772168991[/C][C]124.312328704107[/C][/ROW]
[ROW][C]36[/C][C]9655[/C][C]9662.02249343573[/C][C]182.497919715837[/C][C]9465.47958684843[/C][C]7.02249343573021[/C][/ROW]
[ROW][C]37[/C][C]9429[/C][C]9366.56973842029[/C][C]52.1688095727502[/C][C]9439.26145200696[/C][C]-62.430261579706[/C][/ROW]
[ROW][C]38[/C][C]8739[/C][C]8352.05723092249[/C][C]-270.651560258269[/C][C]9396.59432933578[/C][C]-386.942769077512[/C][/ROW]
[ROW][C]39[/C][C]9552[/C][C]9859.54114919954[/C][C]-109.468355864149[/C][C]9353.9272066646[/C][C]307.541149199544[/C][/ROW]
[ROW][C]40[/C][C]9687[/C][C]9695.54094781109[/C][C]327.463428436556[/C][C]9350.99562375235[/C][C]8.5409478110887[/C][/ROW]
[ROW][C]41[/C][C]9019[/C][C]8871.94600955391[/C][C]-182.010050394014[/C][C]9348.0640408401[/C][C]-147.053990446089[/C][/ROW]
[ROW][C]42[/C][C]9672[/C][C]9750.95855175642[/C][C]182.497919715837[/C][C]9410.54352852774[/C][C]78.9585517564246[/C][/ROW]
[ROW][C]43[/C][C]9206[/C][C]8886.80817421188[/C][C]52.1688095727502[/C][C]9473.02301621537[/C][C]-319.191825788124[/C][/ROW]
[ROW][C]44[/C][C]9069[/C][C]8824.13069706809[/C][C]-270.651560258269[/C][C]9584.52086319018[/C][C]-244.869302931911[/C][/ROW]
[ROW][C]45[/C][C]9788[/C][C]9989.44964569916[/C][C]-109.468355864149[/C][C]9696.01871016499[/C][C]201.44964569916[/C][/ROW]
[ROW][C]46[/C][C]10312[/C][C]10540.8059992638[/C][C]327.463428436556[/C][C]9755.73057229965[/C][C]228.80599926379[/C][/ROW]
[ROW][C]47[/C][C]10105[/C][C]10576.5676159597[/C][C]-182.010050394014[/C][C]9815.44243443432[/C][C]471.567615959695[/C][/ROW]
[ROW][C]48[/C][C]9863[/C][C]9744.77420501589[/C][C]182.497919715837[/C][C]9798.72787526828[/C][C]-118.225794984113[/C][/ROW]
[ROW][C]49[/C][C]9656[/C][C]9477.81787432502[/C][C]52.1688095727502[/C][C]9782.01331610223[/C][C]-178.182125674983[/C][/ROW]
[ROW][C]50[/C][C]9295[/C][C]9150.41005834231[/C][C]-270.651560258269[/C][C]9710.24150191596[/C][C]-144.589941657687[/C][/ROW]
[ROW][C]51[/C][C]9946[/C][C]10362.9986681345[/C][C]-109.468355864149[/C][C]9638.46968772968[/C][C]416.998668134471[/C][/ROW]
[ROW][C]52[/C][C]9701[/C][C]9415.05229854673[/C][C]327.463428436556[/C][C]9659.48427301672[/C][C]-285.947701453273[/C][/ROW]
[ROW][C]53[/C][C]9049[/C][C]8599.51119209026[/C][C]-182.010050394014[/C][C]9680.49885830376[/C][C]-449.488807909742[/C][/ROW]
[ROW][C]54[/C][C]10190[/C][C]10471.0331893282[/C][C]182.497919715837[/C][C]9726.46889095599[/C][C]281.033189328173[/C][/ROW]
[ROW][C]55[/C][C]9706[/C][C]9587.39226681903[/C][C]52.1688095727502[/C][C]9772.43892360822[/C][C]-118.607733180974[/C][/ROW]
[ROW][C]56[/C][C]9765[/C][C]9931.65213684186[/C][C]-270.651560258269[/C][C]9868.99942341641[/C][C]166.652136841858[/C][/ROW]
[ROW][C]57[/C][C]9893[/C][C]9929.90843263955[/C][C]-109.468355864149[/C][C]9965.5599232246[/C][C]36.9084326395496[/C][/ROW]
[ROW][C]58[/C][C]9994[/C][C]9679.55731216093[/C][C]327.463428436556[/C][C]9980.97925940251[/C][C]-314.442687839071[/C][/ROW]
[ROW][C]59[/C][C]10433[/C][C]11051.6114548136[/C][C]-182.010050394014[/C][C]9996.39859558043[/C][C]618.611454813583[/C][/ROW]
[ROW][C]60[/C][C]10073[/C][C]10000.3758739415[/C][C]182.497919715837[/C][C]9963.12620634267[/C][C]-72.6241260585066[/C][/ROW]
[ROW][C]61[/C][C]10112[/C][C]10241.9773733223[/C][C]52.1688095727502[/C][C]9929.85381710491[/C][C]129.977373322345[/C][/ROW]
[ROW][C]62[/C][C]9266[/C][C]8940.50307948323[/C][C]-270.651560258269[/C][C]9862.14848077504[/C][C]-325.496920516769[/C][/ROW]
[ROW][C]63[/C][C]9820[/C][C]9955.02521141898[/C][C]-109.468355864149[/C][C]9794.44314444517[/C][C]135.025211418977[/C][/ROW]
[ROW][C]64[/C][C]10097[/C][C]10049.5032210833[/C][C]327.463428436556[/C][C]9817.03335048015[/C][C]-47.4967789167058[/C][/ROW]
[ROW][C]65[/C][C]9115[/C][C]8572.38649387888[/C][C]-182.010050394014[/C][C]9839.62355651513[/C][C]-542.613506121115[/C][/ROW]
[ROW][C]66[/C][C]10411[/C][C]10707.6753861052[/C][C]182.497919715837[/C][C]9931.82669417899[/C][C]296.675386105173[/C][/ROW]
[ROW][C]67[/C][C]9678[/C][C]9279.8013585844[/C][C]52.1688095727502[/C][C]10024.0298318429[/C][C]-398.1986414156[/C][/ROW]
[ROW][C]68[/C][C]10408[/C][C]10937.7724070502[/C][C]-270.651560258269[/C][C]10148.8791532081[/C][C]529.77240705021[/C][/ROW]
[ROW][C]69[/C][C]10153[/C][C]10141.7398812909[/C][C]-109.468355864149[/C][C]10273.7284745733[/C][C]-11.2601187091204[/C][/ROW]
[ROW][C]70[/C][C]10368[/C][C]10109.0218176703[/C][C]327.463428436556[/C][C]10299.5147538931[/C][C]-258.978182329698[/C][/ROW]
[ROW][C]71[/C][C]10581[/C][C]11018.709017181[/C][C]-182.010050394014[/C][C]10325.301033213[/C][C]437.709017180998[/C][/ROW]
[ROW][C]72[/C][C]10597[/C][C]10749.4648900049[/C][C]182.497919715837[/C][C]10262.0371902793[/C][C]152.464890004861[/C][/ROW]
[ROW][C]73[/C][C]10680[/C][C]11109.0578430817[/C][C]52.1688095727502[/C][C]10198.7733473456[/C][C]429.057843081664[/C][/ROW]
[ROW][C]74[/C][C]9738[/C][C]9624.52262190154[/C][C]-270.651560258269[/C][C]10122.1289383567[/C][C]-113.47737809846[/C][/ROW]
[ROW][C]75[/C][C]9556[/C][C]9175.98382649628[/C][C]-109.468355864149[/C][C]10045.4845293679[/C][C]-380.016173503724[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187993&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187993&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	9700	10009.4125168222	52.1688095727502	9338.41867360501	309.412516822236
2	9081	9082.6576853216	-270.651560258269	9349.99387493667	1.65768532160291
3	9084	8915.89927959583	-109.468355864149	9361.56907626832	-168.100720404169
4	9743	9768.43176462172	327.463428436556	9390.10480694172	25.4317646217241
5	8587	7937.36951277889	-182.010050394014	9418.64053761512	-649.630487221108
6	9731	9790.63566698778	182.497919715837	9488.86641329638	59.6356669877823
7	9563	9514.73890144961	52.1688095727502	9559.09228897764	-48.2610985503889
8	9998	10628.6432570022	-270.651560258269	9638.00830325608	630.643257002186
9	9437	9266.54403832962	-109.468355864149	9716.92431753453	-170.455961670377
10	10038	10068.9836299535	327.463428436556	9679.55294160998	30.9836299534654
11	9918	10375.8284847086	-182.010050394014	9642.18156568543	457.828484708582
12	9252	8774.02015818712	182.497919715837	9547.48192209704	-477.979841812878
13	9737	9969.0489119186	52.1688095727502	9452.78227850865	232.048911918602
14	9035	8982.56170084463	-270.651560258269	9358.08985941364	-52.4382991553684
15	9133	9112.07091554552	-109.468355864149	9263.39744031863	-20.9290844544776
16	9487	9422.34788574634	327.463428436556	9224.18868581711	-64.6521142536621
17	8700	8397.03011907843	-182.010050394014	9184.97993131558	-302.96988092157
18	9627	9873.65505407779	182.497919715837	9197.84702620637	246.655054077792
19	8947	8631.11706933009	52.1688095727502	9210.71412109716	-315.882930669906
20	9283	9559.25542270526	-270.651560258269	9277.39613755301	276.255422705257
21	8829	8423.39020185528	-109.468355864149	9344.07815400887	-405.60979814472
22	9947	10204.5511440451	327.463428436556	9361.98542751836	257.551144045085
23	9628	10058.1173493662	-182.010050394014	9379.89270102785	430.117349366164
24	9318	9099.20781157755	182.497919715837	9354.29426870662	-218.792188422454
25	9605	9829.13535404187	52.1688095727502	9328.69583638538	224.135354041868
26	8640	8307.66748022911	-270.651560258269	9242.98408002916	-332.332519770891
27	9214	9380.19603219121	-109.468355864149	9157.27232367294	166.196032191212
28	9567	9656.28708895251	327.463428436556	9150.24948261093	89.2870889525129
29	8547	8132.78340884509	-182.010050394014	9143.22664154892	-414.216591154911
30	9185	8983.6738567326	182.497919715837	9203.82822355156	-201.326143267399
31	9470	9623.40138487305	52.1688095727502	9264.4298055542	153.401384873052
32	9123	9152.67239907504	-270.651560258269	9363.97916118323	29.6723990750379
33	9278	9201.93983905188	-109.468355864149	9463.52851681226	-76.0601609481164
34	10170	10534.9234523124	327.463428436556	9477.61311925109	364.923452312358
35	9434	9558.31232870411	-182.010050394014	9491.69772168991	124.312328704107
36	9655	9662.02249343573	182.497919715837	9465.47958684843	7.02249343573021
37	9429	9366.56973842029	52.1688095727502	9439.26145200696	-62.430261579706
38	8739	8352.05723092249	-270.651560258269	9396.59432933578	-386.942769077512
39	9552	9859.54114919954	-109.468355864149	9353.9272066646	307.541149199544
40	9687	9695.54094781109	327.463428436556	9350.99562375235	8.5409478110887
41	9019	8871.94600955391	-182.010050394014	9348.0640408401	-147.053990446089
42	9672	9750.95855175642	182.497919715837	9410.54352852774	78.9585517564246
43	9206	8886.80817421188	52.1688095727502	9473.02301621537	-319.191825788124
44	9069	8824.13069706809	-270.651560258269	9584.52086319018	-244.869302931911
45	9788	9989.44964569916	-109.468355864149	9696.01871016499	201.44964569916
46	10312	10540.8059992638	327.463428436556	9755.73057229965	228.80599926379
47	10105	10576.5676159597	-182.010050394014	9815.44243443432	471.567615959695
48	9863	9744.77420501589	182.497919715837	9798.72787526828	-118.225794984113
49	9656	9477.81787432502	52.1688095727502	9782.01331610223	-178.182125674983
50	9295	9150.41005834231	-270.651560258269	9710.24150191596	-144.589941657687
51	9946	10362.9986681345	-109.468355864149	9638.46968772968	416.998668134471
52	9701	9415.05229854673	327.463428436556	9659.48427301672	-285.947701453273
53	9049	8599.51119209026	-182.010050394014	9680.49885830376	-449.488807909742
54	10190	10471.0331893282	182.497919715837	9726.46889095599	281.033189328173
55	9706	9587.39226681903	52.1688095727502	9772.43892360822	-118.607733180974
56	9765	9931.65213684186	-270.651560258269	9868.99942341641	166.652136841858
57	9893	9929.90843263955	-109.468355864149	9965.5599232246	36.9084326395496
58	9994	9679.55731216093	327.463428436556	9980.97925940251	-314.442687839071
59	10433	11051.6114548136	-182.010050394014	9996.39859558043	618.611454813583
60	10073	10000.3758739415	182.497919715837	9963.12620634267	-72.6241260585066
61	10112	10241.9773733223	52.1688095727502	9929.85381710491	129.977373322345
62	9266	8940.50307948323	-270.651560258269	9862.14848077504	-325.496920516769
63	9820	9955.02521141898	-109.468355864149	9794.44314444517	135.025211418977
64	10097	10049.5032210833	327.463428436556	9817.03335048015	-47.4967789167058
65	9115	8572.38649387888	-182.010050394014	9839.62355651513	-542.613506121115
66	10411	10707.6753861052	182.497919715837	9931.82669417899	296.675386105173
67	9678	9279.8013585844	52.1688095727502	10024.0298318429	-398.1986414156
68	10408	10937.7724070502	-270.651560258269	10148.8791532081	529.77240705021
69	10153	10141.7398812909	-109.468355864149	10273.7284745733	-11.2601187091204
70	10368	10109.0218176703	327.463428436556	10299.5147538931	-258.978182329698
71	10581	11018.709017181	-182.010050394014	10325.301033213	437.709017180998
72	10597	10749.4648900049	182.497919715837	10262.0371902793	152.464890004861
73	10680	11109.0578430817	52.1688095727502	10198.7733473456	429.057843081664
74	9738	9624.52262190154	-270.651560258269	10122.1289383567	-113.47737809846
75	9556	9175.98382649628	-109.468355864149	10045.4845293679	-380.016173503724

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 = 6 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;

Parameters (R input):

par1 = 6 ; 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