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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 Apr 2016 15:36:08 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/25/t1461595060ahajb2y3gn1re6d.htm/, Retrieved Sat, 02 May 2026 23:48:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294722, Retrieved Sat, 02 May 2026 23:48:29 +0000

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344

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-       [Classical Decomposition] [] [2016-04-25 14:36:08] [1af9caed13b550360754d0d82088541b] [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=294722&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=294722&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294722&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	103.71	NA	NA	-0.37875	NA
2	103.07	NA	NA	-0.171333	NA
3	103.93	NA	NA	-0.21525	NA
4	102.9	NA	NA	-0.043	NA
5	101.54	NA	NA	-0.02075	NA
6	102.13	NA	NA	0.13475	NA
7	101.08	101.356	101.51	-0.153917	-0.275667
8	101.33	101.433	101.133	0.299417	-0.10275
9	101.24	101.239	100.709	0.529833	0.001
10	100.58	100.586	100.258	0.328	-0.0055
11	99.87	99.8644	99.8887	-0.0243333	0.00558333
12	99.1	99.2366	99.5212	-0.284667	-0.136583
13	98.98	98.7833	99.1621	-0.37875	0.196667
14	98.77	98.6712	98.8425	-0.171333	0.0988333
15	98.05	98.3268	98.5421	-0.21525	-0.276833
16	97.94	98.2491	98.2921	-0.043	-0.309083
17	97.65	98.0597	98.0804	-0.02075	-0.409667
18	97.2	98.0752	97.9404	0.13475	-0.875167
19	97.39	97.6944	97.8483	-0.153917	-0.304417
20	97.35	98.1111	97.8117	0.299417	-0.761083
21	98.01	98.3869	97.8571	0.529833	-0.376917
22	97.81	98.2063	97.8783	0.328	-0.396333
23	97.56	97.8465	97.8708	-0.0243333	-0.2865
24	98.05	97.6274	97.9121	-0.284667	0.422583
25	97.82	97.61	97.9888	-0.37875	0.21
26	99.05	97.9682	98.1396	-0.171333	1.08175
27	98.86	98.0977	98.3129	-0.21525	0.762333
28	97.64	98.3749	98.4179	-0.043	-0.734917
29	97.77	98.4984	98.5192	-0.02075	-0.728417
30	98.07	98.736	98.6012	0.13475	-0.666
31	98.36	98.5111	98.665	-0.153917	-0.151083
32	100	99.029	98.7296	0.299417	0.971
33	99.52	99.3036	98.7737	0.529833	0.216417
34	98.82	99.2151	98.8871	0.328	-0.395083
35	98.98	99.029	99.0533	-0.0243333	-0.049
36	98.6	98.9174	99.2021	-0.284667	-0.317417
37	98.8	98.9362	99.315	-0.37875	-0.13625
38	99.62	99.1608	99.3321	-0.171333	0.45925
39	99.35	99.1431	99.3583	-0.21525	0.206917
40	99.87	99.4466	99.4896	-0.043	0.423417
41	99.53	99.6559	99.6767	-0.02075	-0.125917
42	99.88	100.025	99.89	0.13475	-0.14475
43	99.26	99.9665	100.12	-0.153917	-0.7065
44	99.51	100.677	100.378	0.299417	-1.16733
45	100.64	101.232	100.702	0.529833	-0.5915
46	100.85	101.479	101.151	0.328	-0.628833
47	101.44	101.699	101.723	-0.0243333	-0.258583
48	101.26	102.107	102.391	-0.284667	-0.846583
49	101.67	102.753	103.132	-0.37875	-1.08333
50	102.93	103.736	103.908	-0.171333	-0.806167
51	103.81	104.445	104.66	-0.21525	-0.635167
52	106.19	105.356	105.399	-0.043	0.833833
53	106.94	106.07	106.091	-0.02075	0.869917
54	108.51	106.86	106.725	0.13475	1.64983
55	108.41	107.194	107.348	-0.153917	1.216
56	108.97	108.131	107.832	0.299417	0.8385
57	109.25	108.721	108.191	0.529833	0.529333
58	109.97	108.766	108.438	0.328	1.20408
59	108.92	108.553	108.578	-0.0243333	0.366833
60	109.01	108.354	108.638	-0.284667	0.656333
61	108.86	108.269	108.648	-0.37875	0.59125
62	107.36	108.415	108.587	-0.171333	-1.05533
63	107.99	108.269	108.484	-0.21525	-0.278917
64	107.94	108.375	108.418	-0.043	-0.434917
65	108.54	108.368	108.388	-0.02075	0.172417
66	108.37	108.556	108.421	0.13475	-0.185583
67	108.77	NA	NA	-0.153917	NA
68	107.15	NA	NA	0.299417	NA
69	108.61	NA	NA	0.529833	NA
70	109.02	NA	NA	0.328	NA
71	109.16	NA	NA	-0.0243333	NA
72	109.55	NA	NA	-0.284667	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 103.71 & NA & NA & -0.37875 & NA \tabularnewline
2 & 103.07 & NA & NA & -0.171333 & NA \tabularnewline
3 & 103.93 & NA & NA & -0.21525 & NA \tabularnewline
4 & 102.9 & NA & NA & -0.043 & NA \tabularnewline
5 & 101.54 & NA & NA & -0.02075 & NA \tabularnewline
6 & 102.13 & NA & NA & 0.13475 & NA \tabularnewline
7 & 101.08 & 101.356 & 101.51 & -0.153917 & -0.275667 \tabularnewline
8 & 101.33 & 101.433 & 101.133 & 0.299417 & -0.10275 \tabularnewline
9 & 101.24 & 101.239 & 100.709 & 0.529833 & 0.001 \tabularnewline
10 & 100.58 & 100.586 & 100.258 & 0.328 & -0.0055 \tabularnewline
11 & 99.87 & 99.8644 & 99.8887 & -0.0243333 & 0.00558333 \tabularnewline
12 & 99.1 & 99.2366 & 99.5212 & -0.284667 & -0.136583 \tabularnewline
13 & 98.98 & 98.7833 & 99.1621 & -0.37875 & 0.196667 \tabularnewline
14 & 98.77 & 98.6712 & 98.8425 & -0.171333 & 0.0988333 \tabularnewline
15 & 98.05 & 98.3268 & 98.5421 & -0.21525 & -0.276833 \tabularnewline
16 & 97.94 & 98.2491 & 98.2921 & -0.043 & -0.309083 \tabularnewline
17 & 97.65 & 98.0597 & 98.0804 & -0.02075 & -0.409667 \tabularnewline
18 & 97.2 & 98.0752 & 97.9404 & 0.13475 & -0.875167 \tabularnewline
19 & 97.39 & 97.6944 & 97.8483 & -0.153917 & -0.304417 \tabularnewline
20 & 97.35 & 98.1111 & 97.8117 & 0.299417 & -0.761083 \tabularnewline
21 & 98.01 & 98.3869 & 97.8571 & 0.529833 & -0.376917 \tabularnewline
22 & 97.81 & 98.2063 & 97.8783 & 0.328 & -0.396333 \tabularnewline
23 & 97.56 & 97.8465 & 97.8708 & -0.0243333 & -0.2865 \tabularnewline
24 & 98.05 & 97.6274 & 97.9121 & -0.284667 & 0.422583 \tabularnewline
25 & 97.82 & 97.61 & 97.9888 & -0.37875 & 0.21 \tabularnewline
26 & 99.05 & 97.9682 & 98.1396 & -0.171333 & 1.08175 \tabularnewline
27 & 98.86 & 98.0977 & 98.3129 & -0.21525 & 0.762333 \tabularnewline
28 & 97.64 & 98.3749 & 98.4179 & -0.043 & -0.734917 \tabularnewline
29 & 97.77 & 98.4984 & 98.5192 & -0.02075 & -0.728417 \tabularnewline
30 & 98.07 & 98.736 & 98.6012 & 0.13475 & -0.666 \tabularnewline
31 & 98.36 & 98.5111 & 98.665 & -0.153917 & -0.151083 \tabularnewline
32 & 100 & 99.029 & 98.7296 & 0.299417 & 0.971 \tabularnewline
33 & 99.52 & 99.3036 & 98.7737 & 0.529833 & 0.216417 \tabularnewline
34 & 98.82 & 99.2151 & 98.8871 & 0.328 & -0.395083 \tabularnewline
35 & 98.98 & 99.029 & 99.0533 & -0.0243333 & -0.049 \tabularnewline
36 & 98.6 & 98.9174 & 99.2021 & -0.284667 & -0.317417 \tabularnewline
37 & 98.8 & 98.9362 & 99.315 & -0.37875 & -0.13625 \tabularnewline
38 & 99.62 & 99.1608 & 99.3321 & -0.171333 & 0.45925 \tabularnewline
39 & 99.35 & 99.1431 & 99.3583 & -0.21525 & 0.206917 \tabularnewline
40 & 99.87 & 99.4466 & 99.4896 & -0.043 & 0.423417 \tabularnewline
41 & 99.53 & 99.6559 & 99.6767 & -0.02075 & -0.125917 \tabularnewline
42 & 99.88 & 100.025 & 99.89 & 0.13475 & -0.14475 \tabularnewline
43 & 99.26 & 99.9665 & 100.12 & -0.153917 & -0.7065 \tabularnewline
44 & 99.51 & 100.677 & 100.378 & 0.299417 & -1.16733 \tabularnewline
45 & 100.64 & 101.232 & 100.702 & 0.529833 & -0.5915 \tabularnewline
46 & 100.85 & 101.479 & 101.151 & 0.328 & -0.628833 \tabularnewline
47 & 101.44 & 101.699 & 101.723 & -0.0243333 & -0.258583 \tabularnewline
48 & 101.26 & 102.107 & 102.391 & -0.284667 & -0.846583 \tabularnewline
49 & 101.67 & 102.753 & 103.132 & -0.37875 & -1.08333 \tabularnewline
50 & 102.93 & 103.736 & 103.908 & -0.171333 & -0.806167 \tabularnewline
51 & 103.81 & 104.445 & 104.66 & -0.21525 & -0.635167 \tabularnewline
52 & 106.19 & 105.356 & 105.399 & -0.043 & 0.833833 \tabularnewline
53 & 106.94 & 106.07 & 106.091 & -0.02075 & 0.869917 \tabularnewline
54 & 108.51 & 106.86 & 106.725 & 0.13475 & 1.64983 \tabularnewline
55 & 108.41 & 107.194 & 107.348 & -0.153917 & 1.216 \tabularnewline
56 & 108.97 & 108.131 & 107.832 & 0.299417 & 0.8385 \tabularnewline
57 & 109.25 & 108.721 & 108.191 & 0.529833 & 0.529333 \tabularnewline
58 & 109.97 & 108.766 & 108.438 & 0.328 & 1.20408 \tabularnewline
59 & 108.92 & 108.553 & 108.578 & -0.0243333 & 0.366833 \tabularnewline
60 & 109.01 & 108.354 & 108.638 & -0.284667 & 0.656333 \tabularnewline
61 & 108.86 & 108.269 & 108.648 & -0.37875 & 0.59125 \tabularnewline
62 & 107.36 & 108.415 & 108.587 & -0.171333 & -1.05533 \tabularnewline
63 & 107.99 & 108.269 & 108.484 & -0.21525 & -0.278917 \tabularnewline
64 & 107.94 & 108.375 & 108.418 & -0.043 & -0.434917 \tabularnewline
65 & 108.54 & 108.368 & 108.388 & -0.02075 & 0.172417 \tabularnewline
66 & 108.37 & 108.556 & 108.421 & 0.13475 & -0.185583 \tabularnewline
67 & 108.77 & NA & NA & -0.153917 & NA \tabularnewline
68 & 107.15 & NA & NA & 0.299417 & NA \tabularnewline
69 & 108.61 & NA & NA & 0.529833 & NA \tabularnewline
70 & 109.02 & NA & NA & 0.328 & NA \tabularnewline
71 & 109.16 & NA & NA & -0.0243333 & NA \tabularnewline
72 & 109.55 & NA & NA & -0.284667 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294722&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]103.71[/C][C]NA[/C][C]NA[/C][C]-0.37875[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]103.07[/C][C]NA[/C][C]NA[/C][C]-0.171333[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]103.93[/C][C]NA[/C][C]NA[/C][C]-0.21525[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]102.9[/C][C]NA[/C][C]NA[/C][C]-0.043[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]101.54[/C][C]NA[/C][C]NA[/C][C]-0.02075[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]102.13[/C][C]NA[/C][C]NA[/C][C]0.13475[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]101.08[/C][C]101.356[/C][C]101.51[/C][C]-0.153917[/C][C]-0.275667[/C][/ROW]
[ROW][C]8[/C][C]101.33[/C][C]101.433[/C][C]101.133[/C][C]0.299417[/C][C]-0.10275[/C][/ROW]
[ROW][C]9[/C][C]101.24[/C][C]101.239[/C][C]100.709[/C][C]0.529833[/C][C]0.001[/C][/ROW]
[ROW][C]10[/C][C]100.58[/C][C]100.586[/C][C]100.258[/C][C]0.328[/C][C]-0.0055[/C][/ROW]
[ROW][C]11[/C][C]99.87[/C][C]99.8644[/C][C]99.8887[/C][C]-0.0243333[/C][C]0.00558333[/C][/ROW]
[ROW][C]12[/C][C]99.1[/C][C]99.2366[/C][C]99.5212[/C][C]-0.284667[/C][C]-0.136583[/C][/ROW]
[ROW][C]13[/C][C]98.98[/C][C]98.7833[/C][C]99.1621[/C][C]-0.37875[/C][C]0.196667[/C][/ROW]
[ROW][C]14[/C][C]98.77[/C][C]98.6712[/C][C]98.8425[/C][C]-0.171333[/C][C]0.0988333[/C][/ROW]
[ROW][C]15[/C][C]98.05[/C][C]98.3268[/C][C]98.5421[/C][C]-0.21525[/C][C]-0.276833[/C][/ROW]
[ROW][C]16[/C][C]97.94[/C][C]98.2491[/C][C]98.2921[/C][C]-0.043[/C][C]-0.309083[/C][/ROW]
[ROW][C]17[/C][C]97.65[/C][C]98.0597[/C][C]98.0804[/C][C]-0.02075[/C][C]-0.409667[/C][/ROW]
[ROW][C]18[/C][C]97.2[/C][C]98.0752[/C][C]97.9404[/C][C]0.13475[/C][C]-0.875167[/C][/ROW]
[ROW][C]19[/C][C]97.39[/C][C]97.6944[/C][C]97.8483[/C][C]-0.153917[/C][C]-0.304417[/C][/ROW]
[ROW][C]20[/C][C]97.35[/C][C]98.1111[/C][C]97.8117[/C][C]0.299417[/C][C]-0.761083[/C][/ROW]
[ROW][C]21[/C][C]98.01[/C][C]98.3869[/C][C]97.8571[/C][C]0.529833[/C][C]-0.376917[/C][/ROW]
[ROW][C]22[/C][C]97.81[/C][C]98.2063[/C][C]97.8783[/C][C]0.328[/C][C]-0.396333[/C][/ROW]
[ROW][C]23[/C][C]97.56[/C][C]97.8465[/C][C]97.8708[/C][C]-0.0243333[/C][C]-0.2865[/C][/ROW]
[ROW][C]24[/C][C]98.05[/C][C]97.6274[/C][C]97.9121[/C][C]-0.284667[/C][C]0.422583[/C][/ROW]
[ROW][C]25[/C][C]97.82[/C][C]97.61[/C][C]97.9888[/C][C]-0.37875[/C][C]0.21[/C][/ROW]
[ROW][C]26[/C][C]99.05[/C][C]97.9682[/C][C]98.1396[/C][C]-0.171333[/C][C]1.08175[/C][/ROW]
[ROW][C]27[/C][C]98.86[/C][C]98.0977[/C][C]98.3129[/C][C]-0.21525[/C][C]0.762333[/C][/ROW]
[ROW][C]28[/C][C]97.64[/C][C]98.3749[/C][C]98.4179[/C][C]-0.043[/C][C]-0.734917[/C][/ROW]
[ROW][C]29[/C][C]97.77[/C][C]98.4984[/C][C]98.5192[/C][C]-0.02075[/C][C]-0.728417[/C][/ROW]
[ROW][C]30[/C][C]98.07[/C][C]98.736[/C][C]98.6012[/C][C]0.13475[/C][C]-0.666[/C][/ROW]
[ROW][C]31[/C][C]98.36[/C][C]98.5111[/C][C]98.665[/C][C]-0.153917[/C][C]-0.151083[/C][/ROW]
[ROW][C]32[/C][C]100[/C][C]99.029[/C][C]98.7296[/C][C]0.299417[/C][C]0.971[/C][/ROW]
[ROW][C]33[/C][C]99.52[/C][C]99.3036[/C][C]98.7737[/C][C]0.529833[/C][C]0.216417[/C][/ROW]
[ROW][C]34[/C][C]98.82[/C][C]99.2151[/C][C]98.8871[/C][C]0.328[/C][C]-0.395083[/C][/ROW]
[ROW][C]35[/C][C]98.98[/C][C]99.029[/C][C]99.0533[/C][C]-0.0243333[/C][C]-0.049[/C][/ROW]
[ROW][C]36[/C][C]98.6[/C][C]98.9174[/C][C]99.2021[/C][C]-0.284667[/C][C]-0.317417[/C][/ROW]
[ROW][C]37[/C][C]98.8[/C][C]98.9362[/C][C]99.315[/C][C]-0.37875[/C][C]-0.13625[/C][/ROW]
[ROW][C]38[/C][C]99.62[/C][C]99.1608[/C][C]99.3321[/C][C]-0.171333[/C][C]0.45925[/C][/ROW]
[ROW][C]39[/C][C]99.35[/C][C]99.1431[/C][C]99.3583[/C][C]-0.21525[/C][C]0.206917[/C][/ROW]
[ROW][C]40[/C][C]99.87[/C][C]99.4466[/C][C]99.4896[/C][C]-0.043[/C][C]0.423417[/C][/ROW]
[ROW][C]41[/C][C]99.53[/C][C]99.6559[/C][C]99.6767[/C][C]-0.02075[/C][C]-0.125917[/C][/ROW]
[ROW][C]42[/C][C]99.88[/C][C]100.025[/C][C]99.89[/C][C]0.13475[/C][C]-0.14475[/C][/ROW]
[ROW][C]43[/C][C]99.26[/C][C]99.9665[/C][C]100.12[/C][C]-0.153917[/C][C]-0.7065[/C][/ROW]
[ROW][C]44[/C][C]99.51[/C][C]100.677[/C][C]100.378[/C][C]0.299417[/C][C]-1.16733[/C][/ROW]
[ROW][C]45[/C][C]100.64[/C][C]101.232[/C][C]100.702[/C][C]0.529833[/C][C]-0.5915[/C][/ROW]
[ROW][C]46[/C][C]100.85[/C][C]101.479[/C][C]101.151[/C][C]0.328[/C][C]-0.628833[/C][/ROW]
[ROW][C]47[/C][C]101.44[/C][C]101.699[/C][C]101.723[/C][C]-0.0243333[/C][C]-0.258583[/C][/ROW]
[ROW][C]48[/C][C]101.26[/C][C]102.107[/C][C]102.391[/C][C]-0.284667[/C][C]-0.846583[/C][/ROW]
[ROW][C]49[/C][C]101.67[/C][C]102.753[/C][C]103.132[/C][C]-0.37875[/C][C]-1.08333[/C][/ROW]
[ROW][C]50[/C][C]102.93[/C][C]103.736[/C][C]103.908[/C][C]-0.171333[/C][C]-0.806167[/C][/ROW]
[ROW][C]51[/C][C]103.81[/C][C]104.445[/C][C]104.66[/C][C]-0.21525[/C][C]-0.635167[/C][/ROW]
[ROW][C]52[/C][C]106.19[/C][C]105.356[/C][C]105.399[/C][C]-0.043[/C][C]0.833833[/C][/ROW]
[ROW][C]53[/C][C]106.94[/C][C]106.07[/C][C]106.091[/C][C]-0.02075[/C][C]0.869917[/C][/ROW]
[ROW][C]54[/C][C]108.51[/C][C]106.86[/C][C]106.725[/C][C]0.13475[/C][C]1.64983[/C][/ROW]
[ROW][C]55[/C][C]108.41[/C][C]107.194[/C][C]107.348[/C][C]-0.153917[/C][C]1.216[/C][/ROW]
[ROW][C]56[/C][C]108.97[/C][C]108.131[/C][C]107.832[/C][C]0.299417[/C][C]0.8385[/C][/ROW]
[ROW][C]57[/C][C]109.25[/C][C]108.721[/C][C]108.191[/C][C]0.529833[/C][C]0.529333[/C][/ROW]
[ROW][C]58[/C][C]109.97[/C][C]108.766[/C][C]108.438[/C][C]0.328[/C][C]1.20408[/C][/ROW]
[ROW][C]59[/C][C]108.92[/C][C]108.553[/C][C]108.578[/C][C]-0.0243333[/C][C]0.366833[/C][/ROW]
[ROW][C]60[/C][C]109.01[/C][C]108.354[/C][C]108.638[/C][C]-0.284667[/C][C]0.656333[/C][/ROW]
[ROW][C]61[/C][C]108.86[/C][C]108.269[/C][C]108.648[/C][C]-0.37875[/C][C]0.59125[/C][/ROW]
[ROW][C]62[/C][C]107.36[/C][C]108.415[/C][C]108.587[/C][C]-0.171333[/C][C]-1.05533[/C][/ROW]
[ROW][C]63[/C][C]107.99[/C][C]108.269[/C][C]108.484[/C][C]-0.21525[/C][C]-0.278917[/C][/ROW]
[ROW][C]64[/C][C]107.94[/C][C]108.375[/C][C]108.418[/C][C]-0.043[/C][C]-0.434917[/C][/ROW]
[ROW][C]65[/C][C]108.54[/C][C]108.368[/C][C]108.388[/C][C]-0.02075[/C][C]0.172417[/C][/ROW]
[ROW][C]66[/C][C]108.37[/C][C]108.556[/C][C]108.421[/C][C]0.13475[/C][C]-0.185583[/C][/ROW]
[ROW][C]67[/C][C]108.77[/C][C]NA[/C][C]NA[/C][C]-0.153917[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]107.15[/C][C]NA[/C][C]NA[/C][C]0.299417[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]108.61[/C][C]NA[/C][C]NA[/C][C]0.529833[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]109.02[/C][C]NA[/C][C]NA[/C][C]0.328[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]109.16[/C][C]NA[/C][C]NA[/C][C]-0.0243333[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]109.55[/C][C]NA[/C][C]NA[/C][C]-0.284667[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294722&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294722&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	103.71	NA	NA	-0.37875	NA
2	103.07	NA	NA	-0.171333	NA
3	103.93	NA	NA	-0.21525	NA
4	102.9	NA	NA	-0.043	NA
5	101.54	NA	NA	-0.02075	NA
6	102.13	NA	NA	0.13475	NA
7	101.08	101.356	101.51	-0.153917	-0.275667
8	101.33	101.433	101.133	0.299417	-0.10275
9	101.24	101.239	100.709	0.529833	0.001
10	100.58	100.586	100.258	0.328	-0.0055
11	99.87	99.8644	99.8887	-0.0243333	0.00558333
12	99.1	99.2366	99.5212	-0.284667	-0.136583
13	98.98	98.7833	99.1621	-0.37875	0.196667
14	98.77	98.6712	98.8425	-0.171333	0.0988333
15	98.05	98.3268	98.5421	-0.21525	-0.276833
16	97.94	98.2491	98.2921	-0.043	-0.309083
17	97.65	98.0597	98.0804	-0.02075	-0.409667
18	97.2	98.0752	97.9404	0.13475	-0.875167
19	97.39	97.6944	97.8483	-0.153917	-0.304417
20	97.35	98.1111	97.8117	0.299417	-0.761083
21	98.01	98.3869	97.8571	0.529833	-0.376917
22	97.81	98.2063	97.8783	0.328	-0.396333
23	97.56	97.8465	97.8708	-0.0243333	-0.2865
24	98.05	97.6274	97.9121	-0.284667	0.422583
25	97.82	97.61	97.9888	-0.37875	0.21
26	99.05	97.9682	98.1396	-0.171333	1.08175
27	98.86	98.0977	98.3129	-0.21525	0.762333
28	97.64	98.3749	98.4179	-0.043	-0.734917
29	97.77	98.4984	98.5192	-0.02075	-0.728417
30	98.07	98.736	98.6012	0.13475	-0.666
31	98.36	98.5111	98.665	-0.153917	-0.151083
32	100	99.029	98.7296	0.299417	0.971
33	99.52	99.3036	98.7737	0.529833	0.216417
34	98.82	99.2151	98.8871	0.328	-0.395083
35	98.98	99.029	99.0533	-0.0243333	-0.049
36	98.6	98.9174	99.2021	-0.284667	-0.317417
37	98.8	98.9362	99.315	-0.37875	-0.13625
38	99.62	99.1608	99.3321	-0.171333	0.45925
39	99.35	99.1431	99.3583	-0.21525	0.206917
40	99.87	99.4466	99.4896	-0.043	0.423417
41	99.53	99.6559	99.6767	-0.02075	-0.125917
42	99.88	100.025	99.89	0.13475	-0.14475
43	99.26	99.9665	100.12	-0.153917	-0.7065
44	99.51	100.677	100.378	0.299417	-1.16733
45	100.64	101.232	100.702	0.529833	-0.5915
46	100.85	101.479	101.151	0.328	-0.628833
47	101.44	101.699	101.723	-0.0243333	-0.258583
48	101.26	102.107	102.391	-0.284667	-0.846583
49	101.67	102.753	103.132	-0.37875	-1.08333
50	102.93	103.736	103.908	-0.171333	-0.806167
51	103.81	104.445	104.66	-0.21525	-0.635167
52	106.19	105.356	105.399	-0.043	0.833833
53	106.94	106.07	106.091	-0.02075	0.869917
54	108.51	106.86	106.725	0.13475	1.64983
55	108.41	107.194	107.348	-0.153917	1.216
56	108.97	108.131	107.832	0.299417	0.8385
57	109.25	108.721	108.191	0.529833	0.529333
58	109.97	108.766	108.438	0.328	1.20408
59	108.92	108.553	108.578	-0.0243333	0.366833
60	109.01	108.354	108.638	-0.284667	0.656333
61	108.86	108.269	108.648	-0.37875	0.59125
62	107.36	108.415	108.587	-0.171333	-1.05533
63	107.99	108.269	108.484	-0.21525	-0.278917
64	107.94	108.375	108.418	-0.043	-0.434917
65	108.54	108.368	108.388	-0.02075	0.172417
66	108.37	108.556	108.421	0.13475	-0.185583
67	108.77	NA	NA	-0.153917	NA
68	107.15	NA	NA	0.299417	NA
69	108.61	NA	NA	0.529833	NA
70	109.02	NA	NA	0.328	NA
71	109.16	NA	NA	-0.0243333	NA
72	109.55	NA	NA	-0.284667	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