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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sat, 10 Nov 2012 05:49:39 -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/2012/Nov/10/t13525446130z8qj3wr6gdzzqm.htm/, Retrieved Sat, 14 Sep 2024 13:32:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=187286, Retrieved Sat, 14 Sep 2024 13:32:15 +0000

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Estimated Impact

202

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

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- RMPD      [Exponential Smoothing] [triple exponentia...] [2012-11-28 10:55:02] [2c4ddb4bf62114b8025bb962e2c7a2b5] 
- RMPD      [Histogram] [Histogram happiness] [2012-11-28 13:29:17] [2c4ddb4bf62114b8025bb962e2c7a2b5] 
- RMP         [Mean versus Median] [mean-median] [2012-11-28 14:02:18] [2c4ddb4bf62114b8025bb962e2c7a2b5] 
- RMP         [Stem-and-leaf Plot] [stem-and-leaf plot] [2012-11-28 14:22:07] [2c4ddb4bf62114b8025bb962e2c7a2b5] 
- RMPD      [Skewness and Kurtosis Test] [Skewness-kurtosis...] [2012-11-28 13:42:42] [2c4ddb4bf62114b8025bb962e2c7a2b5] 

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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	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=187286&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=187286&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187286&T=0

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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	4 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2.25	NA	NA	-0.0796990740740741	NA
2	2.25	NA	NA	-0.102893518518519	NA
3	2.45	NA	NA	-0.103796296296296	NA
4	2.5	NA	NA	-0.0896990740740739	NA
5	2.5	NA	NA	-0.0995601851851852	NA
6	2.64	NA	NA	-0.0524768518518518	NA
7	2.75	2.85842592592593	2.80875	0.0496759259259259	-0.108425925925926
8	2.93	3.03828703703704	2.91291666666667	0.12537037037037	-0.108287037037037
9	3	3.17078703703704	3.015	0.155787037037037	-0.170787037037037
10	3.17	3.27502314814815	3.11708333333333	0.157939814814815	-0.105023148148148
11	3.25	3.29168981481481	3.22125	0.0704398148148148	-0.0416898148148146
12	3.39	3.29474537037037	3.32583333333333	-0.0310879629629629	0.0952546296296299
13	3.5	3.35071759259259	3.43041666666667	-0.0796990740740741	0.149282407407407
14	3.5	3.42418981481481	3.52708333333333	-0.102893518518519	0.0758101851851851
15	3.65	3.50953703703704	3.61333333333333	-0.103796296296296	0.140462962962963
16	3.75	3.59988425925926	3.68958333333333	-0.0896990740740739	0.150115740740741
17	3.75	3.65585648148148	3.75541666666667	-0.0995601851851852	0.0941435185185191
18	3.9	3.75960648148148	3.81208333333333	-0.0524768518518518	0.140393518518519
19	4	3.90800925925926	3.85833333333333	0.0496759259259259	0.0919907407407408
20	4	4.02537037037037	3.9	0.12537037037037	-0.0253703703703705
21	4	4.0912037037037	3.93541666666667	0.155787037037037	-0.0912037037037039
22	4	4.11835648148148	3.96041666666667	0.157939814814815	-0.118356481481482
23	4	4.05168981481482	3.98125	0.0704398148148148	-0.0516898148148153
24	4	3.96474537037037	3.99583333333333	-0.0310879629629629	0.035254629629629
25	4	3.92780092592593	4.0075	-0.0796990740740741	0.0721990740740734
26	4	3.92252314814815	4.02541666666667	-0.102893518518519	0.0774768518518512
27	4	3.9424537037037	4.04625	-0.103796296296296	0.0575462962962954
28	4	3.96571759259259	4.05541666666667	-0.0896990740740739	0.0342824074074066
29	4	3.93043981481482	4.03	-0.0995601851851852	0.0695601851851837
30	4	3.90127314814815	3.95375	-0.0524768518518518	0.0987268518518509
31	4.18	3.88092592592593	3.83125	0.0496759259259259	0.299074074074073
32	4.25	3.80287037037037	3.6775	0.12537037037037	0.447129629629629
33	4.25	3.6524537037037	3.49666666666667	0.155787037037037	0.597546296296296
34	3.97	3.44502314814815	3.28708333333333	0.157939814814815	0.524976851851852
35	3.42	3.12418981481481	3.05375	0.0704398148148148	0.295810185185185
36	2.75	2.77641203703704	2.8075	-0.0310879629629629	-0.0264120370370367
37	2.31	2.47030092592593	2.55	-0.0796990740740741	-0.160300925925926
38	2	2.17918981481481	2.28208333333333	-0.102893518518519	-0.179189814814815
39	1.66	1.9074537037037	2.01125	-0.103796296296296	-0.247453703703704
40	1.31	1.66238425925926	1.75208333333333	-0.0896990740740739	-0.352384259259259
41	1.09	1.42793981481481	1.5275	-0.0995601851851852	-0.337939814814815
42	1	1.30127314814815	1.35375	-0.0524768518518518	-0.301273148148148
43	1	1.27592592592593	1.22625	0.0496759259259259	-0.275925925925926
44	1	1.25537037037037	1.13	0.12537037037037	-0.25537037037037
45	1	1.21662037037037	1.06083333333333	0.155787037037037	-0.21662037037037
46	1	1.17835648148148	1.02041666666667	0.157939814814815	-0.178356481481482
47	1	1.07418981481482	1.00375	0.0704398148148148	-0.0741898148148149
48	1	0.968912037037037	1	-0.0310879629629629	0.0310879629629626
49	1	0.920300925925926	1	-0.0796990740740741	0.079699074074074
50	1	0.897106481481482	1	-0.102893518518519	0.102893518518518
51	1	0.896203703703704	1	-0.103796296296296	0.103796296296296
52	1	0.910300925925926	1	-0.0896990740740739	0.0896990740740737
53	1	0.900439814814815	1	-0.0995601851851852	0.0995601851851851
54	1	0.947523148148148	1	-0.0524768518518518	0.0524768518518515
55	1	1.04967592592593	1	0.0496759259259259	-0.0496759259259261
56	1	1.12537037037037	1	0.12537037037037	-0.125370370370371
57	1	1.15578703703704	1	0.155787037037037	-0.155787037037037
58	1	1.16377314814815	1.00583333333333	0.157939814814815	-0.163773148148148
59	1	1.09252314814815	1.02208333333333	0.0704398148148148	-0.0925231481481482
60	1	1.0118287037037	1.04291666666667	-0.0310879629629629	-0.0118287037037041
61	1	0.990300925925926	1.07	-0.0796990740740741	0.00969907407407389
62	1	1.00460648148148	1.1075	-0.102893518518519	-0.00460648148148146
63	1	1.04537037037037	1.14916666666667	-0.103796296296296	-0.0453703703703703
64	1.14	1.10113425925926	1.19083333333333	-0.0896990740740739	0.0388657407407405
65	1.25	1.12543981481481	1.225	-0.0995601851851852	0.124560185185185
66	1.25	1.19043981481481	1.24291666666667	-0.0524768518518518	0.0595601851851852
67	1.4	1.29717592592593	1.2475	0.0496759259259259	0.102824074074074
68	1.5	1.37287037037037	1.2475	0.12537037037037	0.12712962962963
69	1.5	1.40328703703704	1.2475	0.155787037037037	0.0967129629629628
70	1.5	1.39960648148148	1.24166666666667	0.157939814814815	0.100393518518518
71	1.32	1.29585648148148	1.22541666666667	0.0704398148148148	0.0241435185185186
72	1.11	1.17349537037037	1.20458333333333	-0.0310879629629629	-0.0634953703703702
73	1	1.09071759259259	1.17041666666667	-0.0796990740740741	-0.0907175925925925
74	1	1.01252314814815	1.11541666666667	-0.102893518518519	-0.0125231481481478
75	1	0.94912037037037	1.05291666666667	-0.103796296296296	0.0508796296296299
76	1	0.900717592592593	0.990416666666667	-0.0896990740740739	0.0992824074074072
77	1	NA	NA	-0.0995601851851852	NA
78	1	NA	NA	-0.0524768518518518	NA
79	0.83	NA	NA	0.0496759259259259	NA
80	0.75	NA	NA	0.12537037037037	NA
81	0.75	NA	NA	0.155787037037037	NA
82	0.75	NA	NA	0.157939814814815	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.25 & NA & NA & -0.0796990740740741 & NA \tabularnewline
2 & 2.25 & NA & NA & -0.102893518518519 & NA \tabularnewline
3 & 2.45 & NA & NA & -0.103796296296296 & NA \tabularnewline
4 & 2.5 & NA & NA & -0.0896990740740739 & NA \tabularnewline
5 & 2.5 & NA & NA & -0.0995601851851852 & NA \tabularnewline
6 & 2.64 & NA & NA & -0.0524768518518518 & NA \tabularnewline
7 & 2.75 & 2.85842592592593 & 2.80875 & 0.0496759259259259 & -0.108425925925926 \tabularnewline
8 & 2.93 & 3.03828703703704 & 2.91291666666667 & 0.12537037037037 & -0.108287037037037 \tabularnewline
9 & 3 & 3.17078703703704 & 3.015 & 0.155787037037037 & -0.170787037037037 \tabularnewline
10 & 3.17 & 3.27502314814815 & 3.11708333333333 & 0.157939814814815 & -0.105023148148148 \tabularnewline
11 & 3.25 & 3.29168981481481 & 3.22125 & 0.0704398148148148 & -0.0416898148148146 \tabularnewline
12 & 3.39 & 3.29474537037037 & 3.32583333333333 & -0.0310879629629629 & 0.0952546296296299 \tabularnewline
13 & 3.5 & 3.35071759259259 & 3.43041666666667 & -0.0796990740740741 & 0.149282407407407 \tabularnewline
14 & 3.5 & 3.42418981481481 & 3.52708333333333 & -0.102893518518519 & 0.0758101851851851 \tabularnewline
15 & 3.65 & 3.50953703703704 & 3.61333333333333 & -0.103796296296296 & 0.140462962962963 \tabularnewline
16 & 3.75 & 3.59988425925926 & 3.68958333333333 & -0.0896990740740739 & 0.150115740740741 \tabularnewline
17 & 3.75 & 3.65585648148148 & 3.75541666666667 & -0.0995601851851852 & 0.0941435185185191 \tabularnewline
18 & 3.9 & 3.75960648148148 & 3.81208333333333 & -0.0524768518518518 & 0.140393518518519 \tabularnewline
19 & 4 & 3.90800925925926 & 3.85833333333333 & 0.0496759259259259 & 0.0919907407407408 \tabularnewline
20 & 4 & 4.02537037037037 & 3.9 & 0.12537037037037 & -0.0253703703703705 \tabularnewline
21 & 4 & 4.0912037037037 & 3.93541666666667 & 0.155787037037037 & -0.0912037037037039 \tabularnewline
22 & 4 & 4.11835648148148 & 3.96041666666667 & 0.157939814814815 & -0.118356481481482 \tabularnewline
23 & 4 & 4.05168981481482 & 3.98125 & 0.0704398148148148 & -0.0516898148148153 \tabularnewline
24 & 4 & 3.96474537037037 & 3.99583333333333 & -0.0310879629629629 & 0.035254629629629 \tabularnewline
25 & 4 & 3.92780092592593 & 4.0075 & -0.0796990740740741 & 0.0721990740740734 \tabularnewline
26 & 4 & 3.92252314814815 & 4.02541666666667 & -0.102893518518519 & 0.0774768518518512 \tabularnewline
27 & 4 & 3.9424537037037 & 4.04625 & -0.103796296296296 & 0.0575462962962954 \tabularnewline
28 & 4 & 3.96571759259259 & 4.05541666666667 & -0.0896990740740739 & 0.0342824074074066 \tabularnewline
29 & 4 & 3.93043981481482 & 4.03 & -0.0995601851851852 & 0.0695601851851837 \tabularnewline
30 & 4 & 3.90127314814815 & 3.95375 & -0.0524768518518518 & 0.0987268518518509 \tabularnewline
31 & 4.18 & 3.88092592592593 & 3.83125 & 0.0496759259259259 & 0.299074074074073 \tabularnewline
32 & 4.25 & 3.80287037037037 & 3.6775 & 0.12537037037037 & 0.447129629629629 \tabularnewline
33 & 4.25 & 3.6524537037037 & 3.49666666666667 & 0.155787037037037 & 0.597546296296296 \tabularnewline
34 & 3.97 & 3.44502314814815 & 3.28708333333333 & 0.157939814814815 & 0.524976851851852 \tabularnewline
35 & 3.42 & 3.12418981481481 & 3.05375 & 0.0704398148148148 & 0.295810185185185 \tabularnewline
36 & 2.75 & 2.77641203703704 & 2.8075 & -0.0310879629629629 & -0.0264120370370367 \tabularnewline
37 & 2.31 & 2.47030092592593 & 2.55 & -0.0796990740740741 & -0.160300925925926 \tabularnewline
38 & 2 & 2.17918981481481 & 2.28208333333333 & -0.102893518518519 & -0.179189814814815 \tabularnewline
39 & 1.66 & 1.9074537037037 & 2.01125 & -0.103796296296296 & -0.247453703703704 \tabularnewline
40 & 1.31 & 1.66238425925926 & 1.75208333333333 & -0.0896990740740739 & -0.352384259259259 \tabularnewline
41 & 1.09 & 1.42793981481481 & 1.5275 & -0.0995601851851852 & -0.337939814814815 \tabularnewline
42 & 1 & 1.30127314814815 & 1.35375 & -0.0524768518518518 & -0.301273148148148 \tabularnewline
43 & 1 & 1.27592592592593 & 1.22625 & 0.0496759259259259 & -0.275925925925926 \tabularnewline
44 & 1 & 1.25537037037037 & 1.13 & 0.12537037037037 & -0.25537037037037 \tabularnewline
45 & 1 & 1.21662037037037 & 1.06083333333333 & 0.155787037037037 & -0.21662037037037 \tabularnewline
46 & 1 & 1.17835648148148 & 1.02041666666667 & 0.157939814814815 & -0.178356481481482 \tabularnewline
47 & 1 & 1.07418981481482 & 1.00375 & 0.0704398148148148 & -0.0741898148148149 \tabularnewline
48 & 1 & 0.968912037037037 & 1 & -0.0310879629629629 & 0.0310879629629626 \tabularnewline
49 & 1 & 0.920300925925926 & 1 & -0.0796990740740741 & 0.079699074074074 \tabularnewline
50 & 1 & 0.897106481481482 & 1 & -0.102893518518519 & 0.102893518518518 \tabularnewline
51 & 1 & 0.896203703703704 & 1 & -0.103796296296296 & 0.103796296296296 \tabularnewline
52 & 1 & 0.910300925925926 & 1 & -0.0896990740740739 & 0.0896990740740737 \tabularnewline
53 & 1 & 0.900439814814815 & 1 & -0.0995601851851852 & 0.0995601851851851 \tabularnewline
54 & 1 & 0.947523148148148 & 1 & -0.0524768518518518 & 0.0524768518518515 \tabularnewline
55 & 1 & 1.04967592592593 & 1 & 0.0496759259259259 & -0.0496759259259261 \tabularnewline
56 & 1 & 1.12537037037037 & 1 & 0.12537037037037 & -0.125370370370371 \tabularnewline
57 & 1 & 1.15578703703704 & 1 & 0.155787037037037 & -0.155787037037037 \tabularnewline
58 & 1 & 1.16377314814815 & 1.00583333333333 & 0.157939814814815 & -0.163773148148148 \tabularnewline
59 & 1 & 1.09252314814815 & 1.02208333333333 & 0.0704398148148148 & -0.0925231481481482 \tabularnewline
60 & 1 & 1.0118287037037 & 1.04291666666667 & -0.0310879629629629 & -0.0118287037037041 \tabularnewline
61 & 1 & 0.990300925925926 & 1.07 & -0.0796990740740741 & 0.00969907407407389 \tabularnewline
62 & 1 & 1.00460648148148 & 1.1075 & -0.102893518518519 & -0.00460648148148146 \tabularnewline
63 & 1 & 1.04537037037037 & 1.14916666666667 & -0.103796296296296 & -0.0453703703703703 \tabularnewline
64 & 1.14 & 1.10113425925926 & 1.19083333333333 & -0.0896990740740739 & 0.0388657407407405 \tabularnewline
65 & 1.25 & 1.12543981481481 & 1.225 & -0.0995601851851852 & 0.124560185185185 \tabularnewline
66 & 1.25 & 1.19043981481481 & 1.24291666666667 & -0.0524768518518518 & 0.0595601851851852 \tabularnewline
67 & 1.4 & 1.29717592592593 & 1.2475 & 0.0496759259259259 & 0.102824074074074 \tabularnewline
68 & 1.5 & 1.37287037037037 & 1.2475 & 0.12537037037037 & 0.12712962962963 \tabularnewline
69 & 1.5 & 1.40328703703704 & 1.2475 & 0.155787037037037 & 0.0967129629629628 \tabularnewline
70 & 1.5 & 1.39960648148148 & 1.24166666666667 & 0.157939814814815 & 0.100393518518518 \tabularnewline
71 & 1.32 & 1.29585648148148 & 1.22541666666667 & 0.0704398148148148 & 0.0241435185185186 \tabularnewline
72 & 1.11 & 1.17349537037037 & 1.20458333333333 & -0.0310879629629629 & -0.0634953703703702 \tabularnewline
73 & 1 & 1.09071759259259 & 1.17041666666667 & -0.0796990740740741 & -0.0907175925925925 \tabularnewline
74 & 1 & 1.01252314814815 & 1.11541666666667 & -0.102893518518519 & -0.0125231481481478 \tabularnewline
75 & 1 & 0.94912037037037 & 1.05291666666667 & -0.103796296296296 & 0.0508796296296299 \tabularnewline
76 & 1 & 0.900717592592593 & 0.990416666666667 & -0.0896990740740739 & 0.0992824074074072 \tabularnewline
77 & 1 & NA & NA & -0.0995601851851852 & NA \tabularnewline
78 & 1 & NA & NA & -0.0524768518518518 & NA \tabularnewline
79 & 0.83 & NA & NA & 0.0496759259259259 & NA \tabularnewline
80 & 0.75 & NA & NA & 0.12537037037037 & NA \tabularnewline
81 & 0.75 & NA & NA & 0.155787037037037 & NA \tabularnewline
82 & 0.75 & NA & NA & 0.157939814814815 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187286&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]2.25[/C][C]NA[/C][C]NA[/C][C]-0.0796990740740741[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.25[/C][C]NA[/C][C]NA[/C][C]-0.102893518518519[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2.45[/C][C]NA[/C][C]NA[/C][C]-0.103796296296296[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2.5[/C][C]NA[/C][C]NA[/C][C]-0.0896990740740739[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.5[/C][C]NA[/C][C]NA[/C][C]-0.0995601851851852[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]2.64[/C][C]NA[/C][C]NA[/C][C]-0.0524768518518518[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]2.75[/C][C]2.85842592592593[/C][C]2.80875[/C][C]0.0496759259259259[/C][C]-0.108425925925926[/C][/ROW]
[ROW][C]8[/C][C]2.93[/C][C]3.03828703703704[/C][C]2.91291666666667[/C][C]0.12537037037037[/C][C]-0.108287037037037[/C][/ROW]
[ROW][C]9[/C][C]3[/C][C]3.17078703703704[/C][C]3.015[/C][C]0.155787037037037[/C][C]-0.170787037037037[/C][/ROW]
[ROW][C]10[/C][C]3.17[/C][C]3.27502314814815[/C][C]3.11708333333333[/C][C]0.157939814814815[/C][C]-0.105023148148148[/C][/ROW]
[ROW][C]11[/C][C]3.25[/C][C]3.29168981481481[/C][C]3.22125[/C][C]0.0704398148148148[/C][C]-0.0416898148148146[/C][/ROW]
[ROW][C]12[/C][C]3.39[/C][C]3.29474537037037[/C][C]3.32583333333333[/C][C]-0.0310879629629629[/C][C]0.0952546296296299[/C][/ROW]
[ROW][C]13[/C][C]3.5[/C][C]3.35071759259259[/C][C]3.43041666666667[/C][C]-0.0796990740740741[/C][C]0.149282407407407[/C][/ROW]
[ROW][C]14[/C][C]3.5[/C][C]3.42418981481481[/C][C]3.52708333333333[/C][C]-0.102893518518519[/C][C]0.0758101851851851[/C][/ROW]
[ROW][C]15[/C][C]3.65[/C][C]3.50953703703704[/C][C]3.61333333333333[/C][C]-0.103796296296296[/C][C]0.140462962962963[/C][/ROW]
[ROW][C]16[/C][C]3.75[/C][C]3.59988425925926[/C][C]3.68958333333333[/C][C]-0.0896990740740739[/C][C]0.150115740740741[/C][/ROW]
[ROW][C]17[/C][C]3.75[/C][C]3.65585648148148[/C][C]3.75541666666667[/C][C]-0.0995601851851852[/C][C]0.0941435185185191[/C][/ROW]
[ROW][C]18[/C][C]3.9[/C][C]3.75960648148148[/C][C]3.81208333333333[/C][C]-0.0524768518518518[/C][C]0.140393518518519[/C][/ROW]
[ROW][C]19[/C][C]4[/C][C]3.90800925925926[/C][C]3.85833333333333[/C][C]0.0496759259259259[/C][C]0.0919907407407408[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]4.02537037037037[/C][C]3.9[/C][C]0.12537037037037[/C][C]-0.0253703703703705[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]4.0912037037037[/C][C]3.93541666666667[/C][C]0.155787037037037[/C][C]-0.0912037037037039[/C][/ROW]
[ROW][C]22[/C][C]4[/C][C]4.11835648148148[/C][C]3.96041666666667[/C][C]0.157939814814815[/C][C]-0.118356481481482[/C][/ROW]
[ROW][C]23[/C][C]4[/C][C]4.05168981481482[/C][C]3.98125[/C][C]0.0704398148148148[/C][C]-0.0516898148148153[/C][/ROW]
[ROW][C]24[/C][C]4[/C][C]3.96474537037037[/C][C]3.99583333333333[/C][C]-0.0310879629629629[/C][C]0.035254629629629[/C][/ROW]
[ROW][C]25[/C][C]4[/C][C]3.92780092592593[/C][C]4.0075[/C][C]-0.0796990740740741[/C][C]0.0721990740740734[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]3.92252314814815[/C][C]4.02541666666667[/C][C]-0.102893518518519[/C][C]0.0774768518518512[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]3.9424537037037[/C][C]4.04625[/C][C]-0.103796296296296[/C][C]0.0575462962962954[/C][/ROW]
[ROW][C]28[/C][C]4[/C][C]3.96571759259259[/C][C]4.05541666666667[/C][C]-0.0896990740740739[/C][C]0.0342824074074066[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]3.93043981481482[/C][C]4.03[/C][C]-0.0995601851851852[/C][C]0.0695601851851837[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]3.90127314814815[/C][C]3.95375[/C][C]-0.0524768518518518[/C][C]0.0987268518518509[/C][/ROW]
[ROW][C]31[/C][C]4.18[/C][C]3.88092592592593[/C][C]3.83125[/C][C]0.0496759259259259[/C][C]0.299074074074073[/C][/ROW]
[ROW][C]32[/C][C]4.25[/C][C]3.80287037037037[/C][C]3.6775[/C][C]0.12537037037037[/C][C]0.447129629629629[/C][/ROW]
[ROW][C]33[/C][C]4.25[/C][C]3.6524537037037[/C][C]3.49666666666667[/C][C]0.155787037037037[/C][C]0.597546296296296[/C][/ROW]
[ROW][C]34[/C][C]3.97[/C][C]3.44502314814815[/C][C]3.28708333333333[/C][C]0.157939814814815[/C][C]0.524976851851852[/C][/ROW]
[ROW][C]35[/C][C]3.42[/C][C]3.12418981481481[/C][C]3.05375[/C][C]0.0704398148148148[/C][C]0.295810185185185[/C][/ROW]
[ROW][C]36[/C][C]2.75[/C][C]2.77641203703704[/C][C]2.8075[/C][C]-0.0310879629629629[/C][C]-0.0264120370370367[/C][/ROW]
[ROW][C]37[/C][C]2.31[/C][C]2.47030092592593[/C][C]2.55[/C][C]-0.0796990740740741[/C][C]-0.160300925925926[/C][/ROW]
[ROW][C]38[/C][C]2[/C][C]2.17918981481481[/C][C]2.28208333333333[/C][C]-0.102893518518519[/C][C]-0.179189814814815[/C][/ROW]
[ROW][C]39[/C][C]1.66[/C][C]1.9074537037037[/C][C]2.01125[/C][C]-0.103796296296296[/C][C]-0.247453703703704[/C][/ROW]
[ROW][C]40[/C][C]1.31[/C][C]1.66238425925926[/C][C]1.75208333333333[/C][C]-0.0896990740740739[/C][C]-0.352384259259259[/C][/ROW]
[ROW][C]41[/C][C]1.09[/C][C]1.42793981481481[/C][C]1.5275[/C][C]-0.0995601851851852[/C][C]-0.337939814814815[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]1.30127314814815[/C][C]1.35375[/C][C]-0.0524768518518518[/C][C]-0.301273148148148[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]1.27592592592593[/C][C]1.22625[/C][C]0.0496759259259259[/C][C]-0.275925925925926[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]1.25537037037037[/C][C]1.13[/C][C]0.12537037037037[/C][C]-0.25537037037037[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]1.21662037037037[/C][C]1.06083333333333[/C][C]0.155787037037037[/C][C]-0.21662037037037[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]1.17835648148148[/C][C]1.02041666666667[/C][C]0.157939814814815[/C][C]-0.178356481481482[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]1.07418981481482[/C][C]1.00375[/C][C]0.0704398148148148[/C][C]-0.0741898148148149[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.968912037037037[/C][C]1[/C][C]-0.0310879629629629[/C][C]0.0310879629629626[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]0.920300925925926[/C][C]1[/C][C]-0.0796990740740741[/C][C]0.079699074074074[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.897106481481482[/C][C]1[/C][C]-0.102893518518519[/C][C]0.102893518518518[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.896203703703704[/C][C]1[/C][C]-0.103796296296296[/C][C]0.103796296296296[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]0.910300925925926[/C][C]1[/C][C]-0.0896990740740739[/C][C]0.0896990740740737[/C][/ROW]
[ROW][C]53[/C][C]1[/C][C]0.900439814814815[/C][C]1[/C][C]-0.0995601851851852[/C][C]0.0995601851851851[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.947523148148148[/C][C]1[/C][C]-0.0524768518518518[/C][C]0.0524768518518515[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]1.04967592592593[/C][C]1[/C][C]0.0496759259259259[/C][C]-0.0496759259259261[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]1.12537037037037[/C][C]1[/C][C]0.12537037037037[/C][C]-0.125370370370371[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]1.15578703703704[/C][C]1[/C][C]0.155787037037037[/C][C]-0.155787037037037[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]1.16377314814815[/C][C]1.00583333333333[/C][C]0.157939814814815[/C][C]-0.163773148148148[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]1.09252314814815[/C][C]1.02208333333333[/C][C]0.0704398148148148[/C][C]-0.0925231481481482[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]1.0118287037037[/C][C]1.04291666666667[/C][C]-0.0310879629629629[/C][C]-0.0118287037037041[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]0.990300925925926[/C][C]1.07[/C][C]-0.0796990740740741[/C][C]0.00969907407407389[/C][/ROW]
[ROW][C]62[/C][C]1[/C][C]1.00460648148148[/C][C]1.1075[/C][C]-0.102893518518519[/C][C]-0.00460648148148146[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]1.04537037037037[/C][C]1.14916666666667[/C][C]-0.103796296296296[/C][C]-0.0453703703703703[/C][/ROW]
[ROW][C]64[/C][C]1.14[/C][C]1.10113425925926[/C][C]1.19083333333333[/C][C]-0.0896990740740739[/C][C]0.0388657407407405[/C][/ROW]
[ROW][C]65[/C][C]1.25[/C][C]1.12543981481481[/C][C]1.225[/C][C]-0.0995601851851852[/C][C]0.124560185185185[/C][/ROW]
[ROW][C]66[/C][C]1.25[/C][C]1.19043981481481[/C][C]1.24291666666667[/C][C]-0.0524768518518518[/C][C]0.0595601851851852[/C][/ROW]
[ROW][C]67[/C][C]1.4[/C][C]1.29717592592593[/C][C]1.2475[/C][C]0.0496759259259259[/C][C]0.102824074074074[/C][/ROW]
[ROW][C]68[/C][C]1.5[/C][C]1.37287037037037[/C][C]1.2475[/C][C]0.12537037037037[/C][C]0.12712962962963[/C][/ROW]
[ROW][C]69[/C][C]1.5[/C][C]1.40328703703704[/C][C]1.2475[/C][C]0.155787037037037[/C][C]0.0967129629629628[/C][/ROW]
[ROW][C]70[/C][C]1.5[/C][C]1.39960648148148[/C][C]1.24166666666667[/C][C]0.157939814814815[/C][C]0.100393518518518[/C][/ROW]
[ROW][C]71[/C][C]1.32[/C][C]1.29585648148148[/C][C]1.22541666666667[/C][C]0.0704398148148148[/C][C]0.0241435185185186[/C][/ROW]
[ROW][C]72[/C][C]1.11[/C][C]1.17349537037037[/C][C]1.20458333333333[/C][C]-0.0310879629629629[/C][C]-0.0634953703703702[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]1.09071759259259[/C][C]1.17041666666667[/C][C]-0.0796990740740741[/C][C]-0.0907175925925925[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]1.01252314814815[/C][C]1.11541666666667[/C][C]-0.102893518518519[/C][C]-0.0125231481481478[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.94912037037037[/C][C]1.05291666666667[/C][C]-0.103796296296296[/C][C]0.0508796296296299[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.900717592592593[/C][C]0.990416666666667[/C][C]-0.0896990740740739[/C][C]0.0992824074074072[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]NA[/C][C]NA[/C][C]-0.0995601851851852[/C][C]NA[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]NA[/C][C]NA[/C][C]-0.0524768518518518[/C][C]NA[/C][/ROW]
[ROW][C]79[/C][C]0.83[/C][C]NA[/C][C]NA[/C][C]0.0496759259259259[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]0.75[/C][C]NA[/C][C]NA[/C][C]0.12537037037037[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]0.75[/C][C]NA[/C][C]NA[/C][C]0.155787037037037[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]0.75[/C][C]NA[/C][C]NA[/C][C]0.157939814814815[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187286&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187286&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	2.25	NA	NA	-0.0796990740740741	NA
2	2.25	NA	NA	-0.102893518518519	NA
3	2.45	NA	NA	-0.103796296296296	NA
4	2.5	NA	NA	-0.0896990740740739	NA
5	2.5	NA	NA	-0.0995601851851852	NA
6	2.64	NA	NA	-0.0524768518518518	NA
7	2.75	2.85842592592593	2.80875	0.0496759259259259	-0.108425925925926
8	2.93	3.03828703703704	2.91291666666667	0.12537037037037	-0.108287037037037
9	3	3.17078703703704	3.015	0.155787037037037	-0.170787037037037
10	3.17	3.27502314814815	3.11708333333333	0.157939814814815	-0.105023148148148
11	3.25	3.29168981481481	3.22125	0.0704398148148148	-0.0416898148148146
12	3.39	3.29474537037037	3.32583333333333	-0.0310879629629629	0.0952546296296299
13	3.5	3.35071759259259	3.43041666666667	-0.0796990740740741	0.149282407407407
14	3.5	3.42418981481481	3.52708333333333	-0.102893518518519	0.0758101851851851
15	3.65	3.50953703703704	3.61333333333333	-0.103796296296296	0.140462962962963
16	3.75	3.59988425925926	3.68958333333333	-0.0896990740740739	0.150115740740741
17	3.75	3.65585648148148	3.75541666666667	-0.0995601851851852	0.0941435185185191
18	3.9	3.75960648148148	3.81208333333333	-0.0524768518518518	0.140393518518519
19	4	3.90800925925926	3.85833333333333	0.0496759259259259	0.0919907407407408
20	4	4.02537037037037	3.9	0.12537037037037	-0.0253703703703705
21	4	4.0912037037037	3.93541666666667	0.155787037037037	-0.0912037037037039
22	4	4.11835648148148	3.96041666666667	0.157939814814815	-0.118356481481482
23	4	4.05168981481482	3.98125	0.0704398148148148	-0.0516898148148153
24	4	3.96474537037037	3.99583333333333	-0.0310879629629629	0.035254629629629
25	4	3.92780092592593	4.0075	-0.0796990740740741	0.0721990740740734
26	4	3.92252314814815	4.02541666666667	-0.102893518518519	0.0774768518518512
27	4	3.9424537037037	4.04625	-0.103796296296296	0.0575462962962954
28	4	3.96571759259259	4.05541666666667	-0.0896990740740739	0.0342824074074066
29	4	3.93043981481482	4.03	-0.0995601851851852	0.0695601851851837
30	4	3.90127314814815	3.95375	-0.0524768518518518	0.0987268518518509
31	4.18	3.88092592592593	3.83125	0.0496759259259259	0.299074074074073
32	4.25	3.80287037037037	3.6775	0.12537037037037	0.447129629629629
33	4.25	3.6524537037037	3.49666666666667	0.155787037037037	0.597546296296296
34	3.97	3.44502314814815	3.28708333333333	0.157939814814815	0.524976851851852
35	3.42	3.12418981481481	3.05375	0.0704398148148148	0.295810185185185
36	2.75	2.77641203703704	2.8075	-0.0310879629629629	-0.0264120370370367
37	2.31	2.47030092592593	2.55	-0.0796990740740741	-0.160300925925926
38	2	2.17918981481481	2.28208333333333	-0.102893518518519	-0.179189814814815
39	1.66	1.9074537037037	2.01125	-0.103796296296296	-0.247453703703704
40	1.31	1.66238425925926	1.75208333333333	-0.0896990740740739	-0.352384259259259
41	1.09	1.42793981481481	1.5275	-0.0995601851851852	-0.337939814814815
42	1	1.30127314814815	1.35375	-0.0524768518518518	-0.301273148148148
43	1	1.27592592592593	1.22625	0.0496759259259259	-0.275925925925926
44	1	1.25537037037037	1.13	0.12537037037037	-0.25537037037037
45	1	1.21662037037037	1.06083333333333	0.155787037037037	-0.21662037037037
46	1	1.17835648148148	1.02041666666667	0.157939814814815	-0.178356481481482
47	1	1.07418981481482	1.00375	0.0704398148148148	-0.0741898148148149
48	1	0.968912037037037	1	-0.0310879629629629	0.0310879629629626
49	1	0.920300925925926	1	-0.0796990740740741	0.079699074074074
50	1	0.897106481481482	1	-0.102893518518519	0.102893518518518
51	1	0.896203703703704	1	-0.103796296296296	0.103796296296296
52	1	0.910300925925926	1	-0.0896990740740739	0.0896990740740737
53	1	0.900439814814815	1	-0.0995601851851852	0.0995601851851851
54	1	0.947523148148148	1	-0.0524768518518518	0.0524768518518515
55	1	1.04967592592593	1	0.0496759259259259	-0.0496759259259261
56	1	1.12537037037037	1	0.12537037037037	-0.125370370370371
57	1	1.15578703703704	1	0.155787037037037	-0.155787037037037
58	1	1.16377314814815	1.00583333333333	0.157939814814815	-0.163773148148148
59	1	1.09252314814815	1.02208333333333	0.0704398148148148	-0.0925231481481482
60	1	1.0118287037037	1.04291666666667	-0.0310879629629629	-0.0118287037037041
61	1	0.990300925925926	1.07	-0.0796990740740741	0.00969907407407389
62	1	1.00460648148148	1.1075	-0.102893518518519	-0.00460648148148146
63	1	1.04537037037037	1.14916666666667	-0.103796296296296	-0.0453703703703703
64	1.14	1.10113425925926	1.19083333333333	-0.0896990740740739	0.0388657407407405
65	1.25	1.12543981481481	1.225	-0.0995601851851852	0.124560185185185
66	1.25	1.19043981481481	1.24291666666667	-0.0524768518518518	0.0595601851851852
67	1.4	1.29717592592593	1.2475	0.0496759259259259	0.102824074074074
68	1.5	1.37287037037037	1.2475	0.12537037037037	0.12712962962963
69	1.5	1.40328703703704	1.2475	0.155787037037037	0.0967129629629628
70	1.5	1.39960648148148	1.24166666666667	0.157939814814815	0.100393518518518
71	1.32	1.29585648148148	1.22541666666667	0.0704398148148148	0.0241435185185186
72	1.11	1.17349537037037	1.20458333333333	-0.0310879629629629	-0.0634953703703702
73	1	1.09071759259259	1.17041666666667	-0.0796990740740741	-0.0907175925925925
74	1	1.01252314814815	1.11541666666667	-0.102893518518519	-0.0125231481481478
75	1	0.94912037037037	1.05291666666667	-0.103796296296296	0.0508796296296299
76	1	0.900717592592593	0.990416666666667	-0.0896990740740739	0.0992824074074072
77	1	NA	NA	-0.0995601851851852	NA
78	1	NA	NA	-0.0524768518518518	NA
79	0.83	NA	NA	0.0496759259259259	NA
80	0.75	NA	NA	0.12537037037037	NA
81	0.75	NA	NA	0.155787037037037	NA
82	0.75	NA	NA	0.157939814814815	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