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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 14 Dec 2011 13:05:55 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/14/t1323885996fddj2ym0yhx0q5v.htm/, Retrieved Wed, 01 May 2024 14:02:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155169, Retrieved Wed, 01 May 2024 14:02:20 +0000

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User-defined keywords

KDGP2W92

Estimated Impact

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

-       [Classical Decomposition] [Additief model ei...] [2011-12-14 18:05:55] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- R PD    [Classical Decomposition] [] [2011-12-16 19:43:00] [74be16979710d4c4e7c6647856088456] 

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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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155169&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155169&T=0

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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	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	105.71	NA	NA	0.41026041666666	NA
2	105.82	NA	NA	0.526302083333321	NA
3	105.82	NA	NA	0.302864583333332	NA
4	105.72	NA	NA	0.335468750000001	NA
5	105.76	NA	NA	-0.24921875	NA
6	105.8	NA	NA	-0.0991145833333276	NA
7	105.09	105.050885416667	105.443333333333	-0.392447916666664	0.0391145833333439
8	105.06	105.120572916667	105.394166666667	-0.273593749999995	-0.0605729166666578
9	105.16	105.03515625	105.3275	-0.292343750000003	0.124843750000011
10	105.2	105.022135416667	105.238333333333	-0.216197916666661	0.177864583333346
11	105.21	105.03765625	105.11875	-0.08109375	0.17234375000001
12	105.23	105.017864583333	104.98875	0.0291145833333362	0.212135416666683
13	105.19	105.313177083333	104.902916666667	0.41026041666666	-0.123177083333317
14	105.16	105.37921875	104.852916666667	0.526302083333321	-0.219218749999982
15	104.88	105.10578125	104.802916666667	0.302864583333332	-0.225781249999983
16	104.52	105.087552083333	104.752083333333	0.335468750000001	-0.567552083333339
17	104.09	104.451614583333	104.700833333333	-0.24921875	-0.361614583333321
18	104.35	104.554635416667	104.65375	-0.0991145833333276	-0.204635416666662
19	104.48	104.217552083333	104.61	-0.392447916666664	0.262447916666702
20	104.47	104.295572916667	104.569166666667	-0.273593749999995	0.174427083333356
21	104.55	104.26015625	104.5525	-0.292343750000003	0.289843750000003
22	104.59	104.360052083333	104.57625	-0.216197916666661	0.229947916666674
23	104.59	104.50265625	104.58375	-0.08109375	0.0873437500000023
24	104.72	104.57578125	104.546666666667	0.0291145833333362	0.144218750000007
25	104.65	104.905677083333	104.495416666667	0.41026041666666	-0.255677083333325
26	104.72	104.985052083333	104.45875	0.526302083333321	-0.26505208333333
27	104.92	104.722447916667	104.419583333333	0.302864583333332	0.197552083333349
28	105.05	104.690885416667	104.355416666667	0.335468750000001	0.359114583333351
29	103.74	104.04953125	104.29875	-0.24921875	-0.309531249999992
30	103.81	104.14671875	104.245833333333	-0.0991145833333276	-0.336718749999989
31	103.79	103.835052083333	104.2275	-0.392447916666664	-0.0450520833333172
32	104.28	103.97515625	104.24875	-0.273593749999995	0.304843749999989
33	103.8	103.92265625	104.215	-0.292343750000003	-0.122656250000006
34	103.8	103.91796875	104.134166666667	-0.216197916666661	-0.117968750000003
35	104.02	103.994322916667	104.075416666667	-0.08109375	0.0256770833333064
36	104.02	104.057447916667	104.028333333333	0.0291145833333362	-0.037447916666693
37	104.91	104.335260416667	103.925	0.41026041666666	0.574739583333326
38	104.97	104.271302083333	103.745	0.526302083333321	0.69869791666666
39	103.86	103.867447916667	103.564583333333	0.302864583333332	-0.00744791666666345
40	104.17	103.737552083333	103.402083333333	0.335468750000001	0.432447916666661
41	103.21	102.976197916667	103.225416666667	-0.24921875	0.23380208333333
42	103.21	102.94046875	103.039583333333	-0.0991145833333276	0.26953125
43	101.91	102.43671875	102.829166666667	-0.392447916666664	-0.526718750000015
44	101.84	102.321822916667	102.595416666667	-0.273593749999995	-0.481822916666673
45	101.91	102.11765625	102.41	-0.292343750000003	-0.207656249999999
46	101.79	102.03296875	102.249166666667	-0.216197916666661	-0.242968749999989
47	101.79	102.028072916667	102.109166666667	-0.08109375	-0.238072916666653
48	101.79	102.041197916667	102.012083333333	0.0291145833333362	-0.251197916666641
49	102.09	102.368177083333	101.957916666667	0.41026041666666	-0.278177083333318
50	102.18	102.47671875	101.950416666667	0.526302083333321	-0.296718749999982
51	102.2	102.246614583333	101.94375	0.302864583333332	-0.0466145833333371
52	101.97	102.276302083333	101.940833333333	0.335468750000001	-0.306302083333321
53	102.05	101.694947916667	101.944166666667	-0.24921875	0.355052083333334
54	102.04	101.85046875	101.949583333333	-0.0991145833333276	0.18953125000003
55	101.78	101.55296875	101.945416666667	-0.392447916666664	0.22703125000001
56	101.79	NA	NA	-0.273593749999995	NA
57	101.8	NA	NA	-0.292343750000003	NA
58	101.83	NA	NA	-0.216197916666661	NA
59	101.83	NA	NA	-0.08109375	NA
60	101.88	NA	NA	0.0291145833333362	NA
61	101.9	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 105.71 & NA & NA & 0.41026041666666 & NA \tabularnewline
2 & 105.82 & NA & NA & 0.526302083333321 & NA \tabularnewline
3 & 105.82 & NA & NA & 0.302864583333332 & NA \tabularnewline
4 & 105.72 & NA & NA & 0.335468750000001 & NA \tabularnewline
5 & 105.76 & NA & NA & -0.24921875 & NA \tabularnewline
6 & 105.8 & NA & NA & -0.0991145833333276 & NA \tabularnewline
7 & 105.09 & 105.050885416667 & 105.443333333333 & -0.392447916666664 & 0.0391145833333439 \tabularnewline
8 & 105.06 & 105.120572916667 & 105.394166666667 & -0.273593749999995 & -0.0605729166666578 \tabularnewline
9 & 105.16 & 105.03515625 & 105.3275 & -0.292343750000003 & 0.124843750000011 \tabularnewline
10 & 105.2 & 105.022135416667 & 105.238333333333 & -0.216197916666661 & 0.177864583333346 \tabularnewline
11 & 105.21 & 105.03765625 & 105.11875 & -0.08109375 & 0.17234375000001 \tabularnewline
12 & 105.23 & 105.017864583333 & 104.98875 & 0.0291145833333362 & 0.212135416666683 \tabularnewline
13 & 105.19 & 105.313177083333 & 104.902916666667 & 0.41026041666666 & -0.123177083333317 \tabularnewline
14 & 105.16 & 105.37921875 & 104.852916666667 & 0.526302083333321 & -0.219218749999982 \tabularnewline
15 & 104.88 & 105.10578125 & 104.802916666667 & 0.302864583333332 & -0.225781249999983 \tabularnewline
16 & 104.52 & 105.087552083333 & 104.752083333333 & 0.335468750000001 & -0.567552083333339 \tabularnewline
17 & 104.09 & 104.451614583333 & 104.700833333333 & -0.24921875 & -0.361614583333321 \tabularnewline
18 & 104.35 & 104.554635416667 & 104.65375 & -0.0991145833333276 & -0.204635416666662 \tabularnewline
19 & 104.48 & 104.217552083333 & 104.61 & -0.392447916666664 & 0.262447916666702 \tabularnewline
20 & 104.47 & 104.295572916667 & 104.569166666667 & -0.273593749999995 & 0.174427083333356 \tabularnewline
21 & 104.55 & 104.26015625 & 104.5525 & -0.292343750000003 & 0.289843750000003 \tabularnewline
22 & 104.59 & 104.360052083333 & 104.57625 & -0.216197916666661 & 0.229947916666674 \tabularnewline
23 & 104.59 & 104.50265625 & 104.58375 & -0.08109375 & 0.0873437500000023 \tabularnewline
24 & 104.72 & 104.57578125 & 104.546666666667 & 0.0291145833333362 & 0.144218750000007 \tabularnewline
25 & 104.65 & 104.905677083333 & 104.495416666667 & 0.41026041666666 & -0.255677083333325 \tabularnewline
26 & 104.72 & 104.985052083333 & 104.45875 & 0.526302083333321 & -0.26505208333333 \tabularnewline
27 & 104.92 & 104.722447916667 & 104.419583333333 & 0.302864583333332 & 0.197552083333349 \tabularnewline
28 & 105.05 & 104.690885416667 & 104.355416666667 & 0.335468750000001 & 0.359114583333351 \tabularnewline
29 & 103.74 & 104.04953125 & 104.29875 & -0.24921875 & -0.309531249999992 \tabularnewline
30 & 103.81 & 104.14671875 & 104.245833333333 & -0.0991145833333276 & -0.336718749999989 \tabularnewline
31 & 103.79 & 103.835052083333 & 104.2275 & -0.392447916666664 & -0.0450520833333172 \tabularnewline
32 & 104.28 & 103.97515625 & 104.24875 & -0.273593749999995 & 0.304843749999989 \tabularnewline
33 & 103.8 & 103.92265625 & 104.215 & -0.292343750000003 & -0.122656250000006 \tabularnewline
34 & 103.8 & 103.91796875 & 104.134166666667 & -0.216197916666661 & -0.117968750000003 \tabularnewline
35 & 104.02 & 103.994322916667 & 104.075416666667 & -0.08109375 & 0.0256770833333064 \tabularnewline
36 & 104.02 & 104.057447916667 & 104.028333333333 & 0.0291145833333362 & -0.037447916666693 \tabularnewline
37 & 104.91 & 104.335260416667 & 103.925 & 0.41026041666666 & 0.574739583333326 \tabularnewline
38 & 104.97 & 104.271302083333 & 103.745 & 0.526302083333321 & 0.69869791666666 \tabularnewline
39 & 103.86 & 103.867447916667 & 103.564583333333 & 0.302864583333332 & -0.00744791666666345 \tabularnewline
40 & 104.17 & 103.737552083333 & 103.402083333333 & 0.335468750000001 & 0.432447916666661 \tabularnewline
41 & 103.21 & 102.976197916667 & 103.225416666667 & -0.24921875 & 0.23380208333333 \tabularnewline
42 & 103.21 & 102.94046875 & 103.039583333333 & -0.0991145833333276 & 0.26953125 \tabularnewline
43 & 101.91 & 102.43671875 & 102.829166666667 & -0.392447916666664 & -0.526718750000015 \tabularnewline
44 & 101.84 & 102.321822916667 & 102.595416666667 & -0.273593749999995 & -0.481822916666673 \tabularnewline
45 & 101.91 & 102.11765625 & 102.41 & -0.292343750000003 & -0.207656249999999 \tabularnewline
46 & 101.79 & 102.03296875 & 102.249166666667 & -0.216197916666661 & -0.242968749999989 \tabularnewline
47 & 101.79 & 102.028072916667 & 102.109166666667 & -0.08109375 & -0.238072916666653 \tabularnewline
48 & 101.79 & 102.041197916667 & 102.012083333333 & 0.0291145833333362 & -0.251197916666641 \tabularnewline
49 & 102.09 & 102.368177083333 & 101.957916666667 & 0.41026041666666 & -0.278177083333318 \tabularnewline
50 & 102.18 & 102.47671875 & 101.950416666667 & 0.526302083333321 & -0.296718749999982 \tabularnewline
51 & 102.2 & 102.246614583333 & 101.94375 & 0.302864583333332 & -0.0466145833333371 \tabularnewline
52 & 101.97 & 102.276302083333 & 101.940833333333 & 0.335468750000001 & -0.306302083333321 \tabularnewline
53 & 102.05 & 101.694947916667 & 101.944166666667 & -0.24921875 & 0.355052083333334 \tabularnewline
54 & 102.04 & 101.85046875 & 101.949583333333 & -0.0991145833333276 & 0.18953125000003 \tabularnewline
55 & 101.78 & 101.55296875 & 101.945416666667 & -0.392447916666664 & 0.22703125000001 \tabularnewline
56 & 101.79 & NA & NA & -0.273593749999995 & NA \tabularnewline
57 & 101.8 & NA & NA & -0.292343750000003 & NA \tabularnewline
58 & 101.83 & NA & NA & -0.216197916666661 & NA \tabularnewline
59 & 101.83 & NA & NA & -0.08109375 & NA \tabularnewline
60 & 101.88 & NA & NA & 0.0291145833333362 & NA \tabularnewline
61 & 101.9 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155169&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]105.71[/C][C]NA[/C][C]NA[/C][C]0.41026041666666[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]105.82[/C][C]NA[/C][C]NA[/C][C]0.526302083333321[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]105.82[/C][C]NA[/C][C]NA[/C][C]0.302864583333332[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]105.72[/C][C]NA[/C][C]NA[/C][C]0.335468750000001[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]105.76[/C][C]NA[/C][C]NA[/C][C]-0.24921875[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]105.8[/C][C]NA[/C][C]NA[/C][C]-0.0991145833333276[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]105.09[/C][C]105.050885416667[/C][C]105.443333333333[/C][C]-0.392447916666664[/C][C]0.0391145833333439[/C][/ROW]
[ROW][C]8[/C][C]105.06[/C][C]105.120572916667[/C][C]105.394166666667[/C][C]-0.273593749999995[/C][C]-0.0605729166666578[/C][/ROW]
[ROW][C]9[/C][C]105.16[/C][C]105.03515625[/C][C]105.3275[/C][C]-0.292343750000003[/C][C]0.124843750000011[/C][/ROW]
[ROW][C]10[/C][C]105.2[/C][C]105.022135416667[/C][C]105.238333333333[/C][C]-0.216197916666661[/C][C]0.177864583333346[/C][/ROW]
[ROW][C]11[/C][C]105.21[/C][C]105.03765625[/C][C]105.11875[/C][C]-0.08109375[/C][C]0.17234375000001[/C][/ROW]
[ROW][C]12[/C][C]105.23[/C][C]105.017864583333[/C][C]104.98875[/C][C]0.0291145833333362[/C][C]0.212135416666683[/C][/ROW]
[ROW][C]13[/C][C]105.19[/C][C]105.313177083333[/C][C]104.902916666667[/C][C]0.41026041666666[/C][C]-0.123177083333317[/C][/ROW]
[ROW][C]14[/C][C]105.16[/C][C]105.37921875[/C][C]104.852916666667[/C][C]0.526302083333321[/C][C]-0.219218749999982[/C][/ROW]
[ROW][C]15[/C][C]104.88[/C][C]105.10578125[/C][C]104.802916666667[/C][C]0.302864583333332[/C][C]-0.225781249999983[/C][/ROW]
[ROW][C]16[/C][C]104.52[/C][C]105.087552083333[/C][C]104.752083333333[/C][C]0.335468750000001[/C][C]-0.567552083333339[/C][/ROW]
[ROW][C]17[/C][C]104.09[/C][C]104.451614583333[/C][C]104.700833333333[/C][C]-0.24921875[/C][C]-0.361614583333321[/C][/ROW]
[ROW][C]18[/C][C]104.35[/C][C]104.554635416667[/C][C]104.65375[/C][C]-0.0991145833333276[/C][C]-0.204635416666662[/C][/ROW]
[ROW][C]19[/C][C]104.48[/C][C]104.217552083333[/C][C]104.61[/C][C]-0.392447916666664[/C][C]0.262447916666702[/C][/ROW]
[ROW][C]20[/C][C]104.47[/C][C]104.295572916667[/C][C]104.569166666667[/C][C]-0.273593749999995[/C][C]0.174427083333356[/C][/ROW]
[ROW][C]21[/C][C]104.55[/C][C]104.26015625[/C][C]104.5525[/C][C]-0.292343750000003[/C][C]0.289843750000003[/C][/ROW]
[ROW][C]22[/C][C]104.59[/C][C]104.360052083333[/C][C]104.57625[/C][C]-0.216197916666661[/C][C]0.229947916666674[/C][/ROW]
[ROW][C]23[/C][C]104.59[/C][C]104.50265625[/C][C]104.58375[/C][C]-0.08109375[/C][C]0.0873437500000023[/C][/ROW]
[ROW][C]24[/C][C]104.72[/C][C]104.57578125[/C][C]104.546666666667[/C][C]0.0291145833333362[/C][C]0.144218750000007[/C][/ROW]
[ROW][C]25[/C][C]104.65[/C][C]104.905677083333[/C][C]104.495416666667[/C][C]0.41026041666666[/C][C]-0.255677083333325[/C][/ROW]
[ROW][C]26[/C][C]104.72[/C][C]104.985052083333[/C][C]104.45875[/C][C]0.526302083333321[/C][C]-0.26505208333333[/C][/ROW]
[ROW][C]27[/C][C]104.92[/C][C]104.722447916667[/C][C]104.419583333333[/C][C]0.302864583333332[/C][C]0.197552083333349[/C][/ROW]
[ROW][C]28[/C][C]105.05[/C][C]104.690885416667[/C][C]104.355416666667[/C][C]0.335468750000001[/C][C]0.359114583333351[/C][/ROW]
[ROW][C]29[/C][C]103.74[/C][C]104.04953125[/C][C]104.29875[/C][C]-0.24921875[/C][C]-0.309531249999992[/C][/ROW]
[ROW][C]30[/C][C]103.81[/C][C]104.14671875[/C][C]104.245833333333[/C][C]-0.0991145833333276[/C][C]-0.336718749999989[/C][/ROW]
[ROW][C]31[/C][C]103.79[/C][C]103.835052083333[/C][C]104.2275[/C][C]-0.392447916666664[/C][C]-0.0450520833333172[/C][/ROW]
[ROW][C]32[/C][C]104.28[/C][C]103.97515625[/C][C]104.24875[/C][C]-0.273593749999995[/C][C]0.304843749999989[/C][/ROW]
[ROW][C]33[/C][C]103.8[/C][C]103.92265625[/C][C]104.215[/C][C]-0.292343750000003[/C][C]-0.122656250000006[/C][/ROW]
[ROW][C]34[/C][C]103.8[/C][C]103.91796875[/C][C]104.134166666667[/C][C]-0.216197916666661[/C][C]-0.117968750000003[/C][/ROW]
[ROW][C]35[/C][C]104.02[/C][C]103.994322916667[/C][C]104.075416666667[/C][C]-0.08109375[/C][C]0.0256770833333064[/C][/ROW]
[ROW][C]36[/C][C]104.02[/C][C]104.057447916667[/C][C]104.028333333333[/C][C]0.0291145833333362[/C][C]-0.037447916666693[/C][/ROW]
[ROW][C]37[/C][C]104.91[/C][C]104.335260416667[/C][C]103.925[/C][C]0.41026041666666[/C][C]0.574739583333326[/C][/ROW]
[ROW][C]38[/C][C]104.97[/C][C]104.271302083333[/C][C]103.745[/C][C]0.526302083333321[/C][C]0.69869791666666[/C][/ROW]
[ROW][C]39[/C][C]103.86[/C][C]103.867447916667[/C][C]103.564583333333[/C][C]0.302864583333332[/C][C]-0.00744791666666345[/C][/ROW]
[ROW][C]40[/C][C]104.17[/C][C]103.737552083333[/C][C]103.402083333333[/C][C]0.335468750000001[/C][C]0.432447916666661[/C][/ROW]
[ROW][C]41[/C][C]103.21[/C][C]102.976197916667[/C][C]103.225416666667[/C][C]-0.24921875[/C][C]0.23380208333333[/C][/ROW]
[ROW][C]42[/C][C]103.21[/C][C]102.94046875[/C][C]103.039583333333[/C][C]-0.0991145833333276[/C][C]0.26953125[/C][/ROW]
[ROW][C]43[/C][C]101.91[/C][C]102.43671875[/C][C]102.829166666667[/C][C]-0.392447916666664[/C][C]-0.526718750000015[/C][/ROW]
[ROW][C]44[/C][C]101.84[/C][C]102.321822916667[/C][C]102.595416666667[/C][C]-0.273593749999995[/C][C]-0.481822916666673[/C][/ROW]
[ROW][C]45[/C][C]101.91[/C][C]102.11765625[/C][C]102.41[/C][C]-0.292343750000003[/C][C]-0.207656249999999[/C][/ROW]
[ROW][C]46[/C][C]101.79[/C][C]102.03296875[/C][C]102.249166666667[/C][C]-0.216197916666661[/C][C]-0.242968749999989[/C][/ROW]
[ROW][C]47[/C][C]101.79[/C][C]102.028072916667[/C][C]102.109166666667[/C][C]-0.08109375[/C][C]-0.238072916666653[/C][/ROW]
[ROW][C]48[/C][C]101.79[/C][C]102.041197916667[/C][C]102.012083333333[/C][C]0.0291145833333362[/C][C]-0.251197916666641[/C][/ROW]
[ROW][C]49[/C][C]102.09[/C][C]102.368177083333[/C][C]101.957916666667[/C][C]0.41026041666666[/C][C]-0.278177083333318[/C][/ROW]
[ROW][C]50[/C][C]102.18[/C][C]102.47671875[/C][C]101.950416666667[/C][C]0.526302083333321[/C][C]-0.296718749999982[/C][/ROW]
[ROW][C]51[/C][C]102.2[/C][C]102.246614583333[/C][C]101.94375[/C][C]0.302864583333332[/C][C]-0.0466145833333371[/C][/ROW]
[ROW][C]52[/C][C]101.97[/C][C]102.276302083333[/C][C]101.940833333333[/C][C]0.335468750000001[/C][C]-0.306302083333321[/C][/ROW]
[ROW][C]53[/C][C]102.05[/C][C]101.694947916667[/C][C]101.944166666667[/C][C]-0.24921875[/C][C]0.355052083333334[/C][/ROW]
[ROW][C]54[/C][C]102.04[/C][C]101.85046875[/C][C]101.949583333333[/C][C]-0.0991145833333276[/C][C]0.18953125000003[/C][/ROW]
[ROW][C]55[/C][C]101.78[/C][C]101.55296875[/C][C]101.945416666667[/C][C]-0.392447916666664[/C][C]0.22703125000001[/C][/ROW]
[ROW][C]56[/C][C]101.79[/C][C]NA[/C][C]NA[/C][C]-0.273593749999995[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]101.8[/C][C]NA[/C][C]NA[/C][C]-0.292343750000003[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]101.83[/C][C]NA[/C][C]NA[/C][C]-0.216197916666661[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]101.83[/C][C]NA[/C][C]NA[/C][C]-0.08109375[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]101.88[/C][C]NA[/C][C]NA[/C][C]0.0291145833333362[/C][C]NA[/C][/ROW]
[ROW][C]61[/C][C]101.9[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155169&T=1

As an alternative you can also use a QR Code:

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

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	105.71	NA	NA	0.41026041666666	NA
2	105.82	NA	NA	0.526302083333321	NA
3	105.82	NA	NA	0.302864583333332	NA
4	105.72	NA	NA	0.335468750000001	NA
5	105.76	NA	NA	-0.24921875	NA
6	105.8	NA	NA	-0.0991145833333276	NA
7	105.09	105.050885416667	105.443333333333	-0.392447916666664	0.0391145833333439
8	105.06	105.120572916667	105.394166666667	-0.273593749999995	-0.0605729166666578
9	105.16	105.03515625	105.3275	-0.292343750000003	0.124843750000011
10	105.2	105.022135416667	105.238333333333	-0.216197916666661	0.177864583333346
11	105.21	105.03765625	105.11875	-0.08109375	0.17234375000001
12	105.23	105.017864583333	104.98875	0.0291145833333362	0.212135416666683
13	105.19	105.313177083333	104.902916666667	0.41026041666666	-0.123177083333317
14	105.16	105.37921875	104.852916666667	0.526302083333321	-0.219218749999982
15	104.88	105.10578125	104.802916666667	0.302864583333332	-0.225781249999983
16	104.52	105.087552083333	104.752083333333	0.335468750000001	-0.567552083333339
17	104.09	104.451614583333	104.700833333333	-0.24921875	-0.361614583333321
18	104.35	104.554635416667	104.65375	-0.0991145833333276	-0.204635416666662
19	104.48	104.217552083333	104.61	-0.392447916666664	0.262447916666702
20	104.47	104.295572916667	104.569166666667	-0.273593749999995	0.174427083333356
21	104.55	104.26015625	104.5525	-0.292343750000003	0.289843750000003
22	104.59	104.360052083333	104.57625	-0.216197916666661	0.229947916666674
23	104.59	104.50265625	104.58375	-0.08109375	0.0873437500000023
24	104.72	104.57578125	104.546666666667	0.0291145833333362	0.144218750000007
25	104.65	104.905677083333	104.495416666667	0.41026041666666	-0.255677083333325
26	104.72	104.985052083333	104.45875	0.526302083333321	-0.26505208333333
27	104.92	104.722447916667	104.419583333333	0.302864583333332	0.197552083333349
28	105.05	104.690885416667	104.355416666667	0.335468750000001	0.359114583333351
29	103.74	104.04953125	104.29875	-0.24921875	-0.309531249999992
30	103.81	104.14671875	104.245833333333	-0.0991145833333276	-0.336718749999989
31	103.79	103.835052083333	104.2275	-0.392447916666664	-0.0450520833333172
32	104.28	103.97515625	104.24875	-0.273593749999995	0.304843749999989
33	103.8	103.92265625	104.215	-0.292343750000003	-0.122656250000006
34	103.8	103.91796875	104.134166666667	-0.216197916666661	-0.117968750000003
35	104.02	103.994322916667	104.075416666667	-0.08109375	0.0256770833333064
36	104.02	104.057447916667	104.028333333333	0.0291145833333362	-0.037447916666693
37	104.91	104.335260416667	103.925	0.41026041666666	0.574739583333326
38	104.97	104.271302083333	103.745	0.526302083333321	0.69869791666666
39	103.86	103.867447916667	103.564583333333	0.302864583333332	-0.00744791666666345
40	104.17	103.737552083333	103.402083333333	0.335468750000001	0.432447916666661
41	103.21	102.976197916667	103.225416666667	-0.24921875	0.23380208333333
42	103.21	102.94046875	103.039583333333	-0.0991145833333276	0.26953125
43	101.91	102.43671875	102.829166666667	-0.392447916666664	-0.526718750000015
44	101.84	102.321822916667	102.595416666667	-0.273593749999995	-0.481822916666673
45	101.91	102.11765625	102.41	-0.292343750000003	-0.207656249999999
46	101.79	102.03296875	102.249166666667	-0.216197916666661	-0.242968749999989
47	101.79	102.028072916667	102.109166666667	-0.08109375	-0.238072916666653
48	101.79	102.041197916667	102.012083333333	0.0291145833333362	-0.251197916666641
49	102.09	102.368177083333	101.957916666667	0.41026041666666	-0.278177083333318
50	102.18	102.47671875	101.950416666667	0.526302083333321	-0.296718749999982
51	102.2	102.246614583333	101.94375	0.302864583333332	-0.0466145833333371
52	101.97	102.276302083333	101.940833333333	0.335468750000001	-0.306302083333321
53	102.05	101.694947916667	101.944166666667	-0.24921875	0.355052083333334
54	102.04	101.85046875	101.949583333333	-0.0991145833333276	0.18953125000003
55	101.78	101.55296875	101.945416666667	-0.392447916666664	0.22703125000001
56	101.79	NA	NA	-0.273593749999995	NA
57	101.8	NA	NA	-0.292343750000003	NA
58	101.83	NA	NA	-0.216197916666661	NA
59	101.83	NA	NA	-0.08109375	NA
60	101.88	NA	NA	0.0291145833333362	NA
61	101.9	NA	NA	NA	NA

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 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; par2 = 12 ;

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

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code