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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 16 Dec 2014 07:01:59 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/16/t1418713338r2qqx15cyk5zuyx.htm/, Retrieved Thu, 16 May 2024 17:23:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269143, Retrieved Thu, 16 May 2024 17:23:44 +0000

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Estimated Impact

108

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

-     [Classical Decomposition] [] [2014-11-29 17:47:49] [b1d502e6dbdcdb9b136a9153b792139c]
-       [Classical Decomposition] [] [2014-11-29 17:55:03] [b1d502e6dbdcdb9b136a9153b792139c]
-    D    [Classical Decomposition] [] [2014-11-29 18:19:50] [b1d502e6dbdcdb9b136a9153b792139c]
- R           [Classical Decomposition] [] [2014-12-16 07:01:59] [823d84bc2f1aa2ddbab319cc794dd4cf] [Current]

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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=269143&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=269143&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269143&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	104.31	NA	NA	-0.807528	NA
2	104.76	NA	NA	0.632222	NA
3	105.68	NA	NA	0.756472	NA
4	106.22	NA	NA	0.808556	NA
5	106.69	NA	NA	0.540722	NA
6	107.17	NA	NA	0.588972	NA
7	107.46	107.056	106.884	0.172389	0.403861
8	107.16	106.856	107.257	-0.400778	0.303694
9	107.35	106.716	107.609	-0.893444	0.634278
10	107.65	107.299	107.905	-0.606361	0.351361
11	107.75	107.432	108.13	-0.698028	0.317611
12	108.22	108.188	108.282	-0.0931944	0.0315278
13	108.68	107.539	108.346	-0.807528	1.14128
14	109.35	108.967	108.335	0.632222	0.382778
15	109.54	109.023	108.267	0.756472	0.516861
16	109.46	108.971	108.163	0.808556	0.488528
17	108.86	108.596	108.055	0.540722	0.263861
18	108.63	108.539	107.95	0.588972	0.0906111
19	107.55	107.986	107.813	0.172389	-0.435722
20	106.8	107.26	107.661	-0.400778	-0.460056
21	106.07	106.642	107.536	-0.893444	-0.572389
22	106.44	106.827	107.434	-0.606361	-0.387389
23	106.38	106.655	107.353	-0.698028	-0.275306
24	107.07	107.195	107.288	-0.0931944	-0.124722
25	106.54	106.493	107.3	-0.807528	0.0471111
26	107.83	108.033	107.401	0.632222	-0.203472
27	108.06	108.288	107.532	0.756472	-0.228139
28	108.49	108.461	107.652	0.808556	0.0293611
29	107.9	108.302	107.762	0.540722	-0.402389
30	108.02	108.452	107.863	0.588972	-0.432306
31	108.46	108.116	107.944	0.172389	0.343861
32	108.31	107.634	108.035	-0.400778	0.676194
33	107.69	107.263	108.156	-0.893444	0.427194
34	107.71	107.696	108.302	-0.606361	0.0142778
35	107.74	107.782	108.48	-0.698028	-0.0419722
36	108.15	108.588	108.682	-0.0931944	-0.438472
37	107.39	108.055	108.862	-0.807528	-0.664556
38	109.16	109.636	109.003	0.632222	-0.475556
39	109.65	109.895	109.139	0.756472	-0.245222
40	110.4	110.104	109.295	0.808556	0.296444
41	110.26	110.006	109.465	0.540722	0.253861
42	110.5	110.228	109.639	0.588972	0.271861
43	110.31	109.975	109.802	0.172389	0.335111
44	109.85	109.586	109.987	-0.400778	0.264111
45	109.4	109.283	110.176	-0.893444	0.117194
46	109.75	109.705	110.311	-0.606361	0.0451111
47	109.79	109.723	110.421	-0.698028	0.0667778
48	110.27	110.452	110.545	-0.0931944	-0.181806
49	109.19	109.865	110.672	-0.807528	-0.674972
50	111.78	111.425	110.793	0.632222	0.354861
51	111.58	111.689	110.933	0.756472	-0.109389
52	111.71	111.933	111.124	0.808556	-0.222722
53	111.59	111.895	111.354	0.540722	-0.304889
54	112.14	112.229	111.64	0.588972	-0.0885556
55	111.73	112.152	111.98	0.172389	-0.421972
56	111.32	111.879	112.28	-0.400778	-0.558806
57	111.29	111.671	112.565	-0.893444	-0.381139
58	112.45	112.248	112.855	-0.606361	0.201778
59	112.61	112.452	113.15	-0.698028	0.158028
60	114.3	113.361	113.455	-0.0931944	0.938611
61	113.32	112.944	113.751	-0.807528	0.376278
62	114.85	114.683	114.051	0.632222	0.166528
63	115.35	115.059	114.302	0.756472	0.291028
64	114.9	115.266	114.458	0.808556	-0.366472
65	115.49	115.075	114.535	0.540722	0.414694
66	115.55	115.166	114.578	0.588972	0.383528
67	115.44	NA	NA	0.172389	NA
68	114.81	NA	NA	-0.400778	NA
69	113.83	NA	NA	-0.893444	NA
70	113.64	NA	NA	-0.606361	NA
71	113.26	NA	NA	-0.698028	NA
72	114.68	NA	NA	-0.0931944	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 104.31 & NA & NA & -0.807528 & NA \tabularnewline
2 & 104.76 & NA & NA & 0.632222 & NA \tabularnewline
3 & 105.68 & NA & NA & 0.756472 & NA \tabularnewline
4 & 106.22 & NA & NA & 0.808556 & NA \tabularnewline
5 & 106.69 & NA & NA & 0.540722 & NA \tabularnewline
6 & 107.17 & NA & NA & 0.588972 & NA \tabularnewline
7 & 107.46 & 107.056 & 106.884 & 0.172389 & 0.403861 \tabularnewline
8 & 107.16 & 106.856 & 107.257 & -0.400778 & 0.303694 \tabularnewline
9 & 107.35 & 106.716 & 107.609 & -0.893444 & 0.634278 \tabularnewline
10 & 107.65 & 107.299 & 107.905 & -0.606361 & 0.351361 \tabularnewline
11 & 107.75 & 107.432 & 108.13 & -0.698028 & 0.317611 \tabularnewline
12 & 108.22 & 108.188 & 108.282 & -0.0931944 & 0.0315278 \tabularnewline
13 & 108.68 & 107.539 & 108.346 & -0.807528 & 1.14128 \tabularnewline
14 & 109.35 & 108.967 & 108.335 & 0.632222 & 0.382778 \tabularnewline
15 & 109.54 & 109.023 & 108.267 & 0.756472 & 0.516861 \tabularnewline
16 & 109.46 & 108.971 & 108.163 & 0.808556 & 0.488528 \tabularnewline
17 & 108.86 & 108.596 & 108.055 & 0.540722 & 0.263861 \tabularnewline
18 & 108.63 & 108.539 & 107.95 & 0.588972 & 0.0906111 \tabularnewline
19 & 107.55 & 107.986 & 107.813 & 0.172389 & -0.435722 \tabularnewline
20 & 106.8 & 107.26 & 107.661 & -0.400778 & -0.460056 \tabularnewline
21 & 106.07 & 106.642 & 107.536 & -0.893444 & -0.572389 \tabularnewline
22 & 106.44 & 106.827 & 107.434 & -0.606361 & -0.387389 \tabularnewline
23 & 106.38 & 106.655 & 107.353 & -0.698028 & -0.275306 \tabularnewline
24 & 107.07 & 107.195 & 107.288 & -0.0931944 & -0.124722 \tabularnewline
25 & 106.54 & 106.493 & 107.3 & -0.807528 & 0.0471111 \tabularnewline
26 & 107.83 & 108.033 & 107.401 & 0.632222 & -0.203472 \tabularnewline
27 & 108.06 & 108.288 & 107.532 & 0.756472 & -0.228139 \tabularnewline
28 & 108.49 & 108.461 & 107.652 & 0.808556 & 0.0293611 \tabularnewline
29 & 107.9 & 108.302 & 107.762 & 0.540722 & -0.402389 \tabularnewline
30 & 108.02 & 108.452 & 107.863 & 0.588972 & -0.432306 \tabularnewline
31 & 108.46 & 108.116 & 107.944 & 0.172389 & 0.343861 \tabularnewline
32 & 108.31 & 107.634 & 108.035 & -0.400778 & 0.676194 \tabularnewline
33 & 107.69 & 107.263 & 108.156 & -0.893444 & 0.427194 \tabularnewline
34 & 107.71 & 107.696 & 108.302 & -0.606361 & 0.0142778 \tabularnewline
35 & 107.74 & 107.782 & 108.48 & -0.698028 & -0.0419722 \tabularnewline
36 & 108.15 & 108.588 & 108.682 & -0.0931944 & -0.438472 \tabularnewline
37 & 107.39 & 108.055 & 108.862 & -0.807528 & -0.664556 \tabularnewline
38 & 109.16 & 109.636 & 109.003 & 0.632222 & -0.475556 \tabularnewline
39 & 109.65 & 109.895 & 109.139 & 0.756472 & -0.245222 \tabularnewline
40 & 110.4 & 110.104 & 109.295 & 0.808556 & 0.296444 \tabularnewline
41 & 110.26 & 110.006 & 109.465 & 0.540722 & 0.253861 \tabularnewline
42 & 110.5 & 110.228 & 109.639 & 0.588972 & 0.271861 \tabularnewline
43 & 110.31 & 109.975 & 109.802 & 0.172389 & 0.335111 \tabularnewline
44 & 109.85 & 109.586 & 109.987 & -0.400778 & 0.264111 \tabularnewline
45 & 109.4 & 109.283 & 110.176 & -0.893444 & 0.117194 \tabularnewline
46 & 109.75 & 109.705 & 110.311 & -0.606361 & 0.0451111 \tabularnewline
47 & 109.79 & 109.723 & 110.421 & -0.698028 & 0.0667778 \tabularnewline
48 & 110.27 & 110.452 & 110.545 & -0.0931944 & -0.181806 \tabularnewline
49 & 109.19 & 109.865 & 110.672 & -0.807528 & -0.674972 \tabularnewline
50 & 111.78 & 111.425 & 110.793 & 0.632222 & 0.354861 \tabularnewline
51 & 111.58 & 111.689 & 110.933 & 0.756472 & -0.109389 \tabularnewline
52 & 111.71 & 111.933 & 111.124 & 0.808556 & -0.222722 \tabularnewline
53 & 111.59 & 111.895 & 111.354 & 0.540722 & -0.304889 \tabularnewline
54 & 112.14 & 112.229 & 111.64 & 0.588972 & -0.0885556 \tabularnewline
55 & 111.73 & 112.152 & 111.98 & 0.172389 & -0.421972 \tabularnewline
56 & 111.32 & 111.879 & 112.28 & -0.400778 & -0.558806 \tabularnewline
57 & 111.29 & 111.671 & 112.565 & -0.893444 & -0.381139 \tabularnewline
58 & 112.45 & 112.248 & 112.855 & -0.606361 & 0.201778 \tabularnewline
59 & 112.61 & 112.452 & 113.15 & -0.698028 & 0.158028 \tabularnewline
60 & 114.3 & 113.361 & 113.455 & -0.0931944 & 0.938611 \tabularnewline
61 & 113.32 & 112.944 & 113.751 & -0.807528 & 0.376278 \tabularnewline
62 & 114.85 & 114.683 & 114.051 & 0.632222 & 0.166528 \tabularnewline
63 & 115.35 & 115.059 & 114.302 & 0.756472 & 0.291028 \tabularnewline
64 & 114.9 & 115.266 & 114.458 & 0.808556 & -0.366472 \tabularnewline
65 & 115.49 & 115.075 & 114.535 & 0.540722 & 0.414694 \tabularnewline
66 & 115.55 & 115.166 & 114.578 & 0.588972 & 0.383528 \tabularnewline
67 & 115.44 & NA & NA & 0.172389 & NA \tabularnewline
68 & 114.81 & NA & NA & -0.400778 & NA \tabularnewline
69 & 113.83 & NA & NA & -0.893444 & NA \tabularnewline
70 & 113.64 & NA & NA & -0.606361 & NA \tabularnewline
71 & 113.26 & NA & NA & -0.698028 & NA \tabularnewline
72 & 114.68 & NA & NA & -0.0931944 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269143&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]104.31[/C][C]NA[/C][C]NA[/C][C]-0.807528[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]104.76[/C][C]NA[/C][C]NA[/C][C]0.632222[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]105.68[/C][C]NA[/C][C]NA[/C][C]0.756472[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]106.22[/C][C]NA[/C][C]NA[/C][C]0.808556[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]106.69[/C][C]NA[/C][C]NA[/C][C]0.540722[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]107.17[/C][C]NA[/C][C]NA[/C][C]0.588972[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]107.46[/C][C]107.056[/C][C]106.884[/C][C]0.172389[/C][C]0.403861[/C][/ROW]
[ROW][C]8[/C][C]107.16[/C][C]106.856[/C][C]107.257[/C][C]-0.400778[/C][C]0.303694[/C][/ROW]
[ROW][C]9[/C][C]107.35[/C][C]106.716[/C][C]107.609[/C][C]-0.893444[/C][C]0.634278[/C][/ROW]
[ROW][C]10[/C][C]107.65[/C][C]107.299[/C][C]107.905[/C][C]-0.606361[/C][C]0.351361[/C][/ROW]
[ROW][C]11[/C][C]107.75[/C][C]107.432[/C][C]108.13[/C][C]-0.698028[/C][C]0.317611[/C][/ROW]
[ROW][C]12[/C][C]108.22[/C][C]108.188[/C][C]108.282[/C][C]-0.0931944[/C][C]0.0315278[/C][/ROW]
[ROW][C]13[/C][C]108.68[/C][C]107.539[/C][C]108.346[/C][C]-0.807528[/C][C]1.14128[/C][/ROW]
[ROW][C]14[/C][C]109.35[/C][C]108.967[/C][C]108.335[/C][C]0.632222[/C][C]0.382778[/C][/ROW]
[ROW][C]15[/C][C]109.54[/C][C]109.023[/C][C]108.267[/C][C]0.756472[/C][C]0.516861[/C][/ROW]
[ROW][C]16[/C][C]109.46[/C][C]108.971[/C][C]108.163[/C][C]0.808556[/C][C]0.488528[/C][/ROW]
[ROW][C]17[/C][C]108.86[/C][C]108.596[/C][C]108.055[/C][C]0.540722[/C][C]0.263861[/C][/ROW]
[ROW][C]18[/C][C]108.63[/C][C]108.539[/C][C]107.95[/C][C]0.588972[/C][C]0.0906111[/C][/ROW]
[ROW][C]19[/C][C]107.55[/C][C]107.986[/C][C]107.813[/C][C]0.172389[/C][C]-0.435722[/C][/ROW]
[ROW][C]20[/C][C]106.8[/C][C]107.26[/C][C]107.661[/C][C]-0.400778[/C][C]-0.460056[/C][/ROW]
[ROW][C]21[/C][C]106.07[/C][C]106.642[/C][C]107.536[/C][C]-0.893444[/C][C]-0.572389[/C][/ROW]
[ROW][C]22[/C][C]106.44[/C][C]106.827[/C][C]107.434[/C][C]-0.606361[/C][C]-0.387389[/C][/ROW]
[ROW][C]23[/C][C]106.38[/C][C]106.655[/C][C]107.353[/C][C]-0.698028[/C][C]-0.275306[/C][/ROW]
[ROW][C]24[/C][C]107.07[/C][C]107.195[/C][C]107.288[/C][C]-0.0931944[/C][C]-0.124722[/C][/ROW]
[ROW][C]25[/C][C]106.54[/C][C]106.493[/C][C]107.3[/C][C]-0.807528[/C][C]0.0471111[/C][/ROW]
[ROW][C]26[/C][C]107.83[/C][C]108.033[/C][C]107.401[/C][C]0.632222[/C][C]-0.203472[/C][/ROW]
[ROW][C]27[/C][C]108.06[/C][C]108.288[/C][C]107.532[/C][C]0.756472[/C][C]-0.228139[/C][/ROW]
[ROW][C]28[/C][C]108.49[/C][C]108.461[/C][C]107.652[/C][C]0.808556[/C][C]0.0293611[/C][/ROW]
[ROW][C]29[/C][C]107.9[/C][C]108.302[/C][C]107.762[/C][C]0.540722[/C][C]-0.402389[/C][/ROW]
[ROW][C]30[/C][C]108.02[/C][C]108.452[/C][C]107.863[/C][C]0.588972[/C][C]-0.432306[/C][/ROW]
[ROW][C]31[/C][C]108.46[/C][C]108.116[/C][C]107.944[/C][C]0.172389[/C][C]0.343861[/C][/ROW]
[ROW][C]32[/C][C]108.31[/C][C]107.634[/C][C]108.035[/C][C]-0.400778[/C][C]0.676194[/C][/ROW]
[ROW][C]33[/C][C]107.69[/C][C]107.263[/C][C]108.156[/C][C]-0.893444[/C][C]0.427194[/C][/ROW]
[ROW][C]34[/C][C]107.71[/C][C]107.696[/C][C]108.302[/C][C]-0.606361[/C][C]0.0142778[/C][/ROW]
[ROW][C]35[/C][C]107.74[/C][C]107.782[/C][C]108.48[/C][C]-0.698028[/C][C]-0.0419722[/C][/ROW]
[ROW][C]36[/C][C]108.15[/C][C]108.588[/C][C]108.682[/C][C]-0.0931944[/C][C]-0.438472[/C][/ROW]
[ROW][C]37[/C][C]107.39[/C][C]108.055[/C][C]108.862[/C][C]-0.807528[/C][C]-0.664556[/C][/ROW]
[ROW][C]38[/C][C]109.16[/C][C]109.636[/C][C]109.003[/C][C]0.632222[/C][C]-0.475556[/C][/ROW]
[ROW][C]39[/C][C]109.65[/C][C]109.895[/C][C]109.139[/C][C]0.756472[/C][C]-0.245222[/C][/ROW]
[ROW][C]40[/C][C]110.4[/C][C]110.104[/C][C]109.295[/C][C]0.808556[/C][C]0.296444[/C][/ROW]
[ROW][C]41[/C][C]110.26[/C][C]110.006[/C][C]109.465[/C][C]0.540722[/C][C]0.253861[/C][/ROW]
[ROW][C]42[/C][C]110.5[/C][C]110.228[/C][C]109.639[/C][C]0.588972[/C][C]0.271861[/C][/ROW]
[ROW][C]43[/C][C]110.31[/C][C]109.975[/C][C]109.802[/C][C]0.172389[/C][C]0.335111[/C][/ROW]
[ROW][C]44[/C][C]109.85[/C][C]109.586[/C][C]109.987[/C][C]-0.400778[/C][C]0.264111[/C][/ROW]
[ROW][C]45[/C][C]109.4[/C][C]109.283[/C][C]110.176[/C][C]-0.893444[/C][C]0.117194[/C][/ROW]
[ROW][C]46[/C][C]109.75[/C][C]109.705[/C][C]110.311[/C][C]-0.606361[/C][C]0.0451111[/C][/ROW]
[ROW][C]47[/C][C]109.79[/C][C]109.723[/C][C]110.421[/C][C]-0.698028[/C][C]0.0667778[/C][/ROW]
[ROW][C]48[/C][C]110.27[/C][C]110.452[/C][C]110.545[/C][C]-0.0931944[/C][C]-0.181806[/C][/ROW]
[ROW][C]49[/C][C]109.19[/C][C]109.865[/C][C]110.672[/C][C]-0.807528[/C][C]-0.674972[/C][/ROW]
[ROW][C]50[/C][C]111.78[/C][C]111.425[/C][C]110.793[/C][C]0.632222[/C][C]0.354861[/C][/ROW]
[ROW][C]51[/C][C]111.58[/C][C]111.689[/C][C]110.933[/C][C]0.756472[/C][C]-0.109389[/C][/ROW]
[ROW][C]52[/C][C]111.71[/C][C]111.933[/C][C]111.124[/C][C]0.808556[/C][C]-0.222722[/C][/ROW]
[ROW][C]53[/C][C]111.59[/C][C]111.895[/C][C]111.354[/C][C]0.540722[/C][C]-0.304889[/C][/ROW]
[ROW][C]54[/C][C]112.14[/C][C]112.229[/C][C]111.64[/C][C]0.588972[/C][C]-0.0885556[/C][/ROW]
[ROW][C]55[/C][C]111.73[/C][C]112.152[/C][C]111.98[/C][C]0.172389[/C][C]-0.421972[/C][/ROW]
[ROW][C]56[/C][C]111.32[/C][C]111.879[/C][C]112.28[/C][C]-0.400778[/C][C]-0.558806[/C][/ROW]
[ROW][C]57[/C][C]111.29[/C][C]111.671[/C][C]112.565[/C][C]-0.893444[/C][C]-0.381139[/C][/ROW]
[ROW][C]58[/C][C]112.45[/C][C]112.248[/C][C]112.855[/C][C]-0.606361[/C][C]0.201778[/C][/ROW]
[ROW][C]59[/C][C]112.61[/C][C]112.452[/C][C]113.15[/C][C]-0.698028[/C][C]0.158028[/C][/ROW]
[ROW][C]60[/C][C]114.3[/C][C]113.361[/C][C]113.455[/C][C]-0.0931944[/C][C]0.938611[/C][/ROW]
[ROW][C]61[/C][C]113.32[/C][C]112.944[/C][C]113.751[/C][C]-0.807528[/C][C]0.376278[/C][/ROW]
[ROW][C]62[/C][C]114.85[/C][C]114.683[/C][C]114.051[/C][C]0.632222[/C][C]0.166528[/C][/ROW]
[ROW][C]63[/C][C]115.35[/C][C]115.059[/C][C]114.302[/C][C]0.756472[/C][C]0.291028[/C][/ROW]
[ROW][C]64[/C][C]114.9[/C][C]115.266[/C][C]114.458[/C][C]0.808556[/C][C]-0.366472[/C][/ROW]
[ROW][C]65[/C][C]115.49[/C][C]115.075[/C][C]114.535[/C][C]0.540722[/C][C]0.414694[/C][/ROW]
[ROW][C]66[/C][C]115.55[/C][C]115.166[/C][C]114.578[/C][C]0.588972[/C][C]0.383528[/C][/ROW]
[ROW][C]67[/C][C]115.44[/C][C]NA[/C][C]NA[/C][C]0.172389[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]114.81[/C][C]NA[/C][C]NA[/C][C]-0.400778[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]113.83[/C][C]NA[/C][C]NA[/C][C]-0.893444[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]113.64[/C][C]NA[/C][C]NA[/C][C]-0.606361[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]113.26[/C][C]NA[/C][C]NA[/C][C]-0.698028[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]114.68[/C][C]NA[/C][C]NA[/C][C]-0.0931944[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269143&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269143&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	104.31	NA	NA	-0.807528	NA
2	104.76	NA	NA	0.632222	NA
3	105.68	NA	NA	0.756472	NA
4	106.22	NA	NA	0.808556	NA
5	106.69	NA	NA	0.540722	NA
6	107.17	NA	NA	0.588972	NA
7	107.46	107.056	106.884	0.172389	0.403861
8	107.16	106.856	107.257	-0.400778	0.303694
9	107.35	106.716	107.609	-0.893444	0.634278
10	107.65	107.299	107.905	-0.606361	0.351361
11	107.75	107.432	108.13	-0.698028	0.317611
12	108.22	108.188	108.282	-0.0931944	0.0315278
13	108.68	107.539	108.346	-0.807528	1.14128
14	109.35	108.967	108.335	0.632222	0.382778
15	109.54	109.023	108.267	0.756472	0.516861
16	109.46	108.971	108.163	0.808556	0.488528
17	108.86	108.596	108.055	0.540722	0.263861
18	108.63	108.539	107.95	0.588972	0.0906111
19	107.55	107.986	107.813	0.172389	-0.435722
20	106.8	107.26	107.661	-0.400778	-0.460056
21	106.07	106.642	107.536	-0.893444	-0.572389
22	106.44	106.827	107.434	-0.606361	-0.387389
23	106.38	106.655	107.353	-0.698028	-0.275306
24	107.07	107.195	107.288	-0.0931944	-0.124722
25	106.54	106.493	107.3	-0.807528	0.0471111
26	107.83	108.033	107.401	0.632222	-0.203472
27	108.06	108.288	107.532	0.756472	-0.228139
28	108.49	108.461	107.652	0.808556	0.0293611
29	107.9	108.302	107.762	0.540722	-0.402389
30	108.02	108.452	107.863	0.588972	-0.432306
31	108.46	108.116	107.944	0.172389	0.343861
32	108.31	107.634	108.035	-0.400778	0.676194
33	107.69	107.263	108.156	-0.893444	0.427194
34	107.71	107.696	108.302	-0.606361	0.0142778
35	107.74	107.782	108.48	-0.698028	-0.0419722
36	108.15	108.588	108.682	-0.0931944	-0.438472
37	107.39	108.055	108.862	-0.807528	-0.664556
38	109.16	109.636	109.003	0.632222	-0.475556
39	109.65	109.895	109.139	0.756472	-0.245222
40	110.4	110.104	109.295	0.808556	0.296444
41	110.26	110.006	109.465	0.540722	0.253861
42	110.5	110.228	109.639	0.588972	0.271861
43	110.31	109.975	109.802	0.172389	0.335111
44	109.85	109.586	109.987	-0.400778	0.264111
45	109.4	109.283	110.176	-0.893444	0.117194
46	109.75	109.705	110.311	-0.606361	0.0451111
47	109.79	109.723	110.421	-0.698028	0.0667778
48	110.27	110.452	110.545	-0.0931944	-0.181806
49	109.19	109.865	110.672	-0.807528	-0.674972
50	111.78	111.425	110.793	0.632222	0.354861
51	111.58	111.689	110.933	0.756472	-0.109389
52	111.71	111.933	111.124	0.808556	-0.222722
53	111.59	111.895	111.354	0.540722	-0.304889
54	112.14	112.229	111.64	0.588972	-0.0885556
55	111.73	112.152	111.98	0.172389	-0.421972
56	111.32	111.879	112.28	-0.400778	-0.558806
57	111.29	111.671	112.565	-0.893444	-0.381139
58	112.45	112.248	112.855	-0.606361	0.201778
59	112.61	112.452	113.15	-0.698028	0.158028
60	114.3	113.361	113.455	-0.0931944	0.938611
61	113.32	112.944	113.751	-0.807528	0.376278
62	114.85	114.683	114.051	0.632222	0.166528
63	115.35	115.059	114.302	0.756472	0.291028
64	114.9	115.266	114.458	0.808556	-0.366472
65	115.49	115.075	114.535	0.540722	0.414694
66	115.55	115.166	114.578	0.588972	0.383528
67	115.44	NA	NA	0.172389	NA
68	114.81	NA	NA	-0.400778	NA
69	113.83	NA	NA	-0.893444	NA
70	113.64	NA	NA	-0.606361	NA
71	113.26	NA	NA	-0.698028	NA
72	114.68	NA	NA	-0.0931944	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
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