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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Thu, 27 Nov 2014 14:02:20 +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/Nov/27/t141709696475049728kqb4eui.htm/, Retrieved Sun, 19 May 2024 21:02:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=260258, Retrieved Sun, 19 May 2024 21:02:18 +0000

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-       [Classical Decomposition] [] [2014-11-27 14:02:20] [5f87c1f524450f94c6870e724864065e] [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=260258&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=260258&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260258&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	102.9	NA	NA	-0.141736	NA
2	103.2	NA	NA	-0.0525694	NA
3	103.1	NA	NA	-0.0517361	NA
4	103.6	NA	NA	-0.0984028	NA
5	104.2	NA	NA	-0.00673611	NA
6	104.9	NA	NA	0.0765972	NA
7	104.5	102.914	102.287	0.626597	1.5859
8	103.9	102.087	101.721	0.366597	1.81257
9	102.8	101.342	101.129	0.213264	1.45757
10	100.8	100.41	100.5	-0.0900694	0.390069
11	99	99.5116	99.8125	-0.300903	-0.511597
12	97.8	98.5341	99.075	-0.540903	-0.734097
13	96.4	98.1749	98.3167	-0.141736	-1.77493
14	96.1	97.5224	97.575	-0.0525694	-1.42243
15	96	96.8358	96.8875	-0.0517361	-0.835764
16	95.6	96.2099	96.3083	-0.0984028	-0.609931
17	95.7	95.8766	95.8833	-0.00673611	-0.176597
18	95.7	95.6766	95.6	0.0765972	0.0234028
19	95.5	96.0849	95.4583	0.626597	-0.584931
20	95.1	95.7999	95.4333	0.366597	-0.699931
21	95.1	95.6674	95.4542	0.213264	-0.567431
22	94.6	95.4349	95.525	-0.0900694	-0.834931
23	95	95.3574	95.6583	-0.300903	-0.357431
24	95	95.3341	95.875	-0.540903	-0.334097
25	95.8	96.0541	96.1958	-0.141736	-0.254097
26	96.1	96.5808	96.6333	-0.0525694	-0.480764
27	96.5	97.1191	97.1708	-0.0517361	-0.619097
28	96.8	97.7433	97.8417	-0.0984028	-0.943264
29	97.7	98.6308	98.6375	-0.00673611	-0.930764
30	98.9	99.5974	99.5208	0.0765972	-0.697431
31	100	101.164	100.537	0.626597	-1.1641
32	101.1	102.046	101.679	0.366597	-0.945764
33	102	103.105	102.892	0.213264	-1.10493
34	103.8	104.06	104.15	-0.0900694	-0.259931
35	104.9	105.124	105.425	-0.300903	-0.224097
36	106.3	106.105	106.646	-0.540903	0.195069
37	108.9	107.65	107.792	-0.141736	1.25007
38	110.4	108.768	108.821	-0.0525694	1.63174
39	111.3	109.673	109.725	-0.0517361	1.62674
40	112.2	110.41	110.508	-0.0984028	1.79007
41	112.9	111.172	111.179	-0.00673611	1.72757
42	113	111.843	111.767	0.0765972	1.15674
43	113.4	112.864	112.238	0.626597	0.535903
44	112.4	112.962	112.596	0.366597	-0.562431
45	112.4	113.105	112.892	0.213264	-0.704931
46	112.2	113.072	113.163	-0.0900694	-0.872431
47	112.6	113.103	113.404	-0.300903	-0.503264
48	112.7	113.109	113.65	-0.540903	-0.409097
49	113.8	113.812	113.954	-0.141736	-0.0124306
50	114.1	114.327	114.379	-0.0525694	-0.226597
51	114.7	114.869	114.921	-0.0517361	-0.169097
52	115.3	115.435	115.533	-0.0984028	-0.134931
53	115.6	116.164	116.171	-0.00673611	-0.564097
54	116.2	116.856	116.779	0.0765972	-0.655764
55	117.5	117.956	117.329	0.626597	-0.455764
56	118.5	118.187	117.821	0.366597	0.312569
57	119.3	118.463	118.25	0.213264	0.836736
58	120	118.506	118.596	-0.0900694	1.49424
59	120.1	118.587	118.888	-0.300903	1.5134
60	119.8	118.601	119.142	-0.540903	1.19924
61	119.9	119.192	119.333	-0.141736	0.708403
62	119.8	119.385	119.438	-0.0525694	0.415069
63	119.3	119.386	119.438	-0.0517361	-0.0857639
64	119	119.185	119.283	-0.0984028	-0.184931
65	118.9	119.039	119.046	-0.00673611	-0.139097
66	119	118.91	118.833	0.0765972	0.0900694
67	119.3	NA	NA	0.626597	NA
68	119.2	NA	NA	0.366597	NA
69	118.6	NA	NA	0.213264	NA
70	117	NA	NA	-0.0900694	NA
71	117.4	NA	NA	-0.300903	NA
72	117.4	NA	NA	-0.540903	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 102.9 & NA & NA & -0.141736 & NA \tabularnewline
2 & 103.2 & NA & NA & -0.0525694 & NA \tabularnewline
3 & 103.1 & NA & NA & -0.0517361 & NA \tabularnewline
4 & 103.6 & NA & NA & -0.0984028 & NA \tabularnewline
5 & 104.2 & NA & NA & -0.00673611 & NA \tabularnewline
6 & 104.9 & NA & NA & 0.0765972 & NA \tabularnewline
7 & 104.5 & 102.914 & 102.287 & 0.626597 & 1.5859 \tabularnewline
8 & 103.9 & 102.087 & 101.721 & 0.366597 & 1.81257 \tabularnewline
9 & 102.8 & 101.342 & 101.129 & 0.213264 & 1.45757 \tabularnewline
10 & 100.8 & 100.41 & 100.5 & -0.0900694 & 0.390069 \tabularnewline
11 & 99 & 99.5116 & 99.8125 & -0.300903 & -0.511597 \tabularnewline
12 & 97.8 & 98.5341 & 99.075 & -0.540903 & -0.734097 \tabularnewline
13 & 96.4 & 98.1749 & 98.3167 & -0.141736 & -1.77493 \tabularnewline
14 & 96.1 & 97.5224 & 97.575 & -0.0525694 & -1.42243 \tabularnewline
15 & 96 & 96.8358 & 96.8875 & -0.0517361 & -0.835764 \tabularnewline
16 & 95.6 & 96.2099 & 96.3083 & -0.0984028 & -0.609931 \tabularnewline
17 & 95.7 & 95.8766 & 95.8833 & -0.00673611 & -0.176597 \tabularnewline
18 & 95.7 & 95.6766 & 95.6 & 0.0765972 & 0.0234028 \tabularnewline
19 & 95.5 & 96.0849 & 95.4583 & 0.626597 & -0.584931 \tabularnewline
20 & 95.1 & 95.7999 & 95.4333 & 0.366597 & -0.699931 \tabularnewline
21 & 95.1 & 95.6674 & 95.4542 & 0.213264 & -0.567431 \tabularnewline
22 & 94.6 & 95.4349 & 95.525 & -0.0900694 & -0.834931 \tabularnewline
23 & 95 & 95.3574 & 95.6583 & -0.300903 & -0.357431 \tabularnewline
24 & 95 & 95.3341 & 95.875 & -0.540903 & -0.334097 \tabularnewline
25 & 95.8 & 96.0541 & 96.1958 & -0.141736 & -0.254097 \tabularnewline
26 & 96.1 & 96.5808 & 96.6333 & -0.0525694 & -0.480764 \tabularnewline
27 & 96.5 & 97.1191 & 97.1708 & -0.0517361 & -0.619097 \tabularnewline
28 & 96.8 & 97.7433 & 97.8417 & -0.0984028 & -0.943264 \tabularnewline
29 & 97.7 & 98.6308 & 98.6375 & -0.00673611 & -0.930764 \tabularnewline
30 & 98.9 & 99.5974 & 99.5208 & 0.0765972 & -0.697431 \tabularnewline
31 & 100 & 101.164 & 100.537 & 0.626597 & -1.1641 \tabularnewline
32 & 101.1 & 102.046 & 101.679 & 0.366597 & -0.945764 \tabularnewline
33 & 102 & 103.105 & 102.892 & 0.213264 & -1.10493 \tabularnewline
34 & 103.8 & 104.06 & 104.15 & -0.0900694 & -0.259931 \tabularnewline
35 & 104.9 & 105.124 & 105.425 & -0.300903 & -0.224097 \tabularnewline
36 & 106.3 & 106.105 & 106.646 & -0.540903 & 0.195069 \tabularnewline
37 & 108.9 & 107.65 & 107.792 & -0.141736 & 1.25007 \tabularnewline
38 & 110.4 & 108.768 & 108.821 & -0.0525694 & 1.63174 \tabularnewline
39 & 111.3 & 109.673 & 109.725 & -0.0517361 & 1.62674 \tabularnewline
40 & 112.2 & 110.41 & 110.508 & -0.0984028 & 1.79007 \tabularnewline
41 & 112.9 & 111.172 & 111.179 & -0.00673611 & 1.72757 \tabularnewline
42 & 113 & 111.843 & 111.767 & 0.0765972 & 1.15674 \tabularnewline
43 & 113.4 & 112.864 & 112.238 & 0.626597 & 0.535903 \tabularnewline
44 & 112.4 & 112.962 & 112.596 & 0.366597 & -0.562431 \tabularnewline
45 & 112.4 & 113.105 & 112.892 & 0.213264 & -0.704931 \tabularnewline
46 & 112.2 & 113.072 & 113.163 & -0.0900694 & -0.872431 \tabularnewline
47 & 112.6 & 113.103 & 113.404 & -0.300903 & -0.503264 \tabularnewline
48 & 112.7 & 113.109 & 113.65 & -0.540903 & -0.409097 \tabularnewline
49 & 113.8 & 113.812 & 113.954 & -0.141736 & -0.0124306 \tabularnewline
50 & 114.1 & 114.327 & 114.379 & -0.0525694 & -0.226597 \tabularnewline
51 & 114.7 & 114.869 & 114.921 & -0.0517361 & -0.169097 \tabularnewline
52 & 115.3 & 115.435 & 115.533 & -0.0984028 & -0.134931 \tabularnewline
53 & 115.6 & 116.164 & 116.171 & -0.00673611 & -0.564097 \tabularnewline
54 & 116.2 & 116.856 & 116.779 & 0.0765972 & -0.655764 \tabularnewline
55 & 117.5 & 117.956 & 117.329 & 0.626597 & -0.455764 \tabularnewline
56 & 118.5 & 118.187 & 117.821 & 0.366597 & 0.312569 \tabularnewline
57 & 119.3 & 118.463 & 118.25 & 0.213264 & 0.836736 \tabularnewline
58 & 120 & 118.506 & 118.596 & -0.0900694 & 1.49424 \tabularnewline
59 & 120.1 & 118.587 & 118.888 & -0.300903 & 1.5134 \tabularnewline
60 & 119.8 & 118.601 & 119.142 & -0.540903 & 1.19924 \tabularnewline
61 & 119.9 & 119.192 & 119.333 & -0.141736 & 0.708403 \tabularnewline
62 & 119.8 & 119.385 & 119.438 & -0.0525694 & 0.415069 \tabularnewline
63 & 119.3 & 119.386 & 119.438 & -0.0517361 & -0.0857639 \tabularnewline
64 & 119 & 119.185 & 119.283 & -0.0984028 & -0.184931 \tabularnewline
65 & 118.9 & 119.039 & 119.046 & -0.00673611 & -0.139097 \tabularnewline
66 & 119 & 118.91 & 118.833 & 0.0765972 & 0.0900694 \tabularnewline
67 & 119.3 & NA & NA & 0.626597 & NA \tabularnewline
68 & 119.2 & NA & NA & 0.366597 & NA \tabularnewline
69 & 118.6 & NA & NA & 0.213264 & NA \tabularnewline
70 & 117 & NA & NA & -0.0900694 & NA \tabularnewline
71 & 117.4 & NA & NA & -0.300903 & NA \tabularnewline
72 & 117.4 & NA & NA & -0.540903 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260258&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]102.9[/C][C]NA[/C][C]NA[/C][C]-0.141736[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]103.2[/C][C]NA[/C][C]NA[/C][C]-0.0525694[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]103.1[/C][C]NA[/C][C]NA[/C][C]-0.0517361[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]103.6[/C][C]NA[/C][C]NA[/C][C]-0.0984028[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]104.2[/C][C]NA[/C][C]NA[/C][C]-0.00673611[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]104.9[/C][C]NA[/C][C]NA[/C][C]0.0765972[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]104.5[/C][C]102.914[/C][C]102.287[/C][C]0.626597[/C][C]1.5859[/C][/ROW]
[ROW][C]8[/C][C]103.9[/C][C]102.087[/C][C]101.721[/C][C]0.366597[/C][C]1.81257[/C][/ROW]
[ROW][C]9[/C][C]102.8[/C][C]101.342[/C][C]101.129[/C][C]0.213264[/C][C]1.45757[/C][/ROW]
[ROW][C]10[/C][C]100.8[/C][C]100.41[/C][C]100.5[/C][C]-0.0900694[/C][C]0.390069[/C][/ROW]
[ROW][C]11[/C][C]99[/C][C]99.5116[/C][C]99.8125[/C][C]-0.300903[/C][C]-0.511597[/C][/ROW]
[ROW][C]12[/C][C]97.8[/C][C]98.5341[/C][C]99.075[/C][C]-0.540903[/C][C]-0.734097[/C][/ROW]
[ROW][C]13[/C][C]96.4[/C][C]98.1749[/C][C]98.3167[/C][C]-0.141736[/C][C]-1.77493[/C][/ROW]
[ROW][C]14[/C][C]96.1[/C][C]97.5224[/C][C]97.575[/C][C]-0.0525694[/C][C]-1.42243[/C][/ROW]
[ROW][C]15[/C][C]96[/C][C]96.8358[/C][C]96.8875[/C][C]-0.0517361[/C][C]-0.835764[/C][/ROW]
[ROW][C]16[/C][C]95.6[/C][C]96.2099[/C][C]96.3083[/C][C]-0.0984028[/C][C]-0.609931[/C][/ROW]
[ROW][C]17[/C][C]95.7[/C][C]95.8766[/C][C]95.8833[/C][C]-0.00673611[/C][C]-0.176597[/C][/ROW]
[ROW][C]18[/C][C]95.7[/C][C]95.6766[/C][C]95.6[/C][C]0.0765972[/C][C]0.0234028[/C][/ROW]
[ROW][C]19[/C][C]95.5[/C][C]96.0849[/C][C]95.4583[/C][C]0.626597[/C][C]-0.584931[/C][/ROW]
[ROW][C]20[/C][C]95.1[/C][C]95.7999[/C][C]95.4333[/C][C]0.366597[/C][C]-0.699931[/C][/ROW]
[ROW][C]21[/C][C]95.1[/C][C]95.6674[/C][C]95.4542[/C][C]0.213264[/C][C]-0.567431[/C][/ROW]
[ROW][C]22[/C][C]94.6[/C][C]95.4349[/C][C]95.525[/C][C]-0.0900694[/C][C]-0.834931[/C][/ROW]
[ROW][C]23[/C][C]95[/C][C]95.3574[/C][C]95.6583[/C][C]-0.300903[/C][C]-0.357431[/C][/ROW]
[ROW][C]24[/C][C]95[/C][C]95.3341[/C][C]95.875[/C][C]-0.540903[/C][C]-0.334097[/C][/ROW]
[ROW][C]25[/C][C]95.8[/C][C]96.0541[/C][C]96.1958[/C][C]-0.141736[/C][C]-0.254097[/C][/ROW]
[ROW][C]26[/C][C]96.1[/C][C]96.5808[/C][C]96.6333[/C][C]-0.0525694[/C][C]-0.480764[/C][/ROW]
[ROW][C]27[/C][C]96.5[/C][C]97.1191[/C][C]97.1708[/C][C]-0.0517361[/C][C]-0.619097[/C][/ROW]
[ROW][C]28[/C][C]96.8[/C][C]97.7433[/C][C]97.8417[/C][C]-0.0984028[/C][C]-0.943264[/C][/ROW]
[ROW][C]29[/C][C]97.7[/C][C]98.6308[/C][C]98.6375[/C][C]-0.00673611[/C][C]-0.930764[/C][/ROW]
[ROW][C]30[/C][C]98.9[/C][C]99.5974[/C][C]99.5208[/C][C]0.0765972[/C][C]-0.697431[/C][/ROW]
[ROW][C]31[/C][C]100[/C][C]101.164[/C][C]100.537[/C][C]0.626597[/C][C]-1.1641[/C][/ROW]
[ROW][C]32[/C][C]101.1[/C][C]102.046[/C][C]101.679[/C][C]0.366597[/C][C]-0.945764[/C][/ROW]
[ROW][C]33[/C][C]102[/C][C]103.105[/C][C]102.892[/C][C]0.213264[/C][C]-1.10493[/C][/ROW]
[ROW][C]34[/C][C]103.8[/C][C]104.06[/C][C]104.15[/C][C]-0.0900694[/C][C]-0.259931[/C][/ROW]
[ROW][C]35[/C][C]104.9[/C][C]105.124[/C][C]105.425[/C][C]-0.300903[/C][C]-0.224097[/C][/ROW]
[ROW][C]36[/C][C]106.3[/C][C]106.105[/C][C]106.646[/C][C]-0.540903[/C][C]0.195069[/C][/ROW]
[ROW][C]37[/C][C]108.9[/C][C]107.65[/C][C]107.792[/C][C]-0.141736[/C][C]1.25007[/C][/ROW]
[ROW][C]38[/C][C]110.4[/C][C]108.768[/C][C]108.821[/C][C]-0.0525694[/C][C]1.63174[/C][/ROW]
[ROW][C]39[/C][C]111.3[/C][C]109.673[/C][C]109.725[/C][C]-0.0517361[/C][C]1.62674[/C][/ROW]
[ROW][C]40[/C][C]112.2[/C][C]110.41[/C][C]110.508[/C][C]-0.0984028[/C][C]1.79007[/C][/ROW]
[ROW][C]41[/C][C]112.9[/C][C]111.172[/C][C]111.179[/C][C]-0.00673611[/C][C]1.72757[/C][/ROW]
[ROW][C]42[/C][C]113[/C][C]111.843[/C][C]111.767[/C][C]0.0765972[/C][C]1.15674[/C][/ROW]
[ROW][C]43[/C][C]113.4[/C][C]112.864[/C][C]112.238[/C][C]0.626597[/C][C]0.535903[/C][/ROW]
[ROW][C]44[/C][C]112.4[/C][C]112.962[/C][C]112.596[/C][C]0.366597[/C][C]-0.562431[/C][/ROW]
[ROW][C]45[/C][C]112.4[/C][C]113.105[/C][C]112.892[/C][C]0.213264[/C][C]-0.704931[/C][/ROW]
[ROW][C]46[/C][C]112.2[/C][C]113.072[/C][C]113.163[/C][C]-0.0900694[/C][C]-0.872431[/C][/ROW]
[ROW][C]47[/C][C]112.6[/C][C]113.103[/C][C]113.404[/C][C]-0.300903[/C][C]-0.503264[/C][/ROW]
[ROW][C]48[/C][C]112.7[/C][C]113.109[/C][C]113.65[/C][C]-0.540903[/C][C]-0.409097[/C][/ROW]
[ROW][C]49[/C][C]113.8[/C][C]113.812[/C][C]113.954[/C][C]-0.141736[/C][C]-0.0124306[/C][/ROW]
[ROW][C]50[/C][C]114.1[/C][C]114.327[/C][C]114.379[/C][C]-0.0525694[/C][C]-0.226597[/C][/ROW]
[ROW][C]51[/C][C]114.7[/C][C]114.869[/C][C]114.921[/C][C]-0.0517361[/C][C]-0.169097[/C][/ROW]
[ROW][C]52[/C][C]115.3[/C][C]115.435[/C][C]115.533[/C][C]-0.0984028[/C][C]-0.134931[/C][/ROW]
[ROW][C]53[/C][C]115.6[/C][C]116.164[/C][C]116.171[/C][C]-0.00673611[/C][C]-0.564097[/C][/ROW]
[ROW][C]54[/C][C]116.2[/C][C]116.856[/C][C]116.779[/C][C]0.0765972[/C][C]-0.655764[/C][/ROW]
[ROW][C]55[/C][C]117.5[/C][C]117.956[/C][C]117.329[/C][C]0.626597[/C][C]-0.455764[/C][/ROW]
[ROW][C]56[/C][C]118.5[/C][C]118.187[/C][C]117.821[/C][C]0.366597[/C][C]0.312569[/C][/ROW]
[ROW][C]57[/C][C]119.3[/C][C]118.463[/C][C]118.25[/C][C]0.213264[/C][C]0.836736[/C][/ROW]
[ROW][C]58[/C][C]120[/C][C]118.506[/C][C]118.596[/C][C]-0.0900694[/C][C]1.49424[/C][/ROW]
[ROW][C]59[/C][C]120.1[/C][C]118.587[/C][C]118.888[/C][C]-0.300903[/C][C]1.5134[/C][/ROW]
[ROW][C]60[/C][C]119.8[/C][C]118.601[/C][C]119.142[/C][C]-0.540903[/C][C]1.19924[/C][/ROW]
[ROW][C]61[/C][C]119.9[/C][C]119.192[/C][C]119.333[/C][C]-0.141736[/C][C]0.708403[/C][/ROW]
[ROW][C]62[/C][C]119.8[/C][C]119.385[/C][C]119.438[/C][C]-0.0525694[/C][C]0.415069[/C][/ROW]
[ROW][C]63[/C][C]119.3[/C][C]119.386[/C][C]119.438[/C][C]-0.0517361[/C][C]-0.0857639[/C][/ROW]
[ROW][C]64[/C][C]119[/C][C]119.185[/C][C]119.283[/C][C]-0.0984028[/C][C]-0.184931[/C][/ROW]
[ROW][C]65[/C][C]118.9[/C][C]119.039[/C][C]119.046[/C][C]-0.00673611[/C][C]-0.139097[/C][/ROW]
[ROW][C]66[/C][C]119[/C][C]118.91[/C][C]118.833[/C][C]0.0765972[/C][C]0.0900694[/C][/ROW]
[ROW][C]67[/C][C]119.3[/C][C]NA[/C][C]NA[/C][C]0.626597[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]119.2[/C][C]NA[/C][C]NA[/C][C]0.366597[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]118.6[/C][C]NA[/C][C]NA[/C][C]0.213264[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]117[/C][C]NA[/C][C]NA[/C][C]-0.0900694[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]117.4[/C][C]NA[/C][C]NA[/C][C]-0.300903[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]117.4[/C][C]NA[/C][C]NA[/C][C]-0.540903[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260258&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260258&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	102.9	NA	NA	-0.141736	NA
2	103.2	NA	NA	-0.0525694	NA
3	103.1	NA	NA	-0.0517361	NA
4	103.6	NA	NA	-0.0984028	NA
5	104.2	NA	NA	-0.00673611	NA
6	104.9	NA	NA	0.0765972	NA
7	104.5	102.914	102.287	0.626597	1.5859
8	103.9	102.087	101.721	0.366597	1.81257
9	102.8	101.342	101.129	0.213264	1.45757
10	100.8	100.41	100.5	-0.0900694	0.390069
11	99	99.5116	99.8125	-0.300903	-0.511597
12	97.8	98.5341	99.075	-0.540903	-0.734097
13	96.4	98.1749	98.3167	-0.141736	-1.77493
14	96.1	97.5224	97.575	-0.0525694	-1.42243
15	96	96.8358	96.8875	-0.0517361	-0.835764
16	95.6	96.2099	96.3083	-0.0984028	-0.609931
17	95.7	95.8766	95.8833	-0.00673611	-0.176597
18	95.7	95.6766	95.6	0.0765972	0.0234028
19	95.5	96.0849	95.4583	0.626597	-0.584931
20	95.1	95.7999	95.4333	0.366597	-0.699931
21	95.1	95.6674	95.4542	0.213264	-0.567431
22	94.6	95.4349	95.525	-0.0900694	-0.834931
23	95	95.3574	95.6583	-0.300903	-0.357431
24	95	95.3341	95.875	-0.540903	-0.334097
25	95.8	96.0541	96.1958	-0.141736	-0.254097
26	96.1	96.5808	96.6333	-0.0525694	-0.480764
27	96.5	97.1191	97.1708	-0.0517361	-0.619097
28	96.8	97.7433	97.8417	-0.0984028	-0.943264
29	97.7	98.6308	98.6375	-0.00673611	-0.930764
30	98.9	99.5974	99.5208	0.0765972	-0.697431
31	100	101.164	100.537	0.626597	-1.1641
32	101.1	102.046	101.679	0.366597	-0.945764
33	102	103.105	102.892	0.213264	-1.10493
34	103.8	104.06	104.15	-0.0900694	-0.259931
35	104.9	105.124	105.425	-0.300903	-0.224097
36	106.3	106.105	106.646	-0.540903	0.195069
37	108.9	107.65	107.792	-0.141736	1.25007
38	110.4	108.768	108.821	-0.0525694	1.63174
39	111.3	109.673	109.725	-0.0517361	1.62674
40	112.2	110.41	110.508	-0.0984028	1.79007
41	112.9	111.172	111.179	-0.00673611	1.72757
42	113	111.843	111.767	0.0765972	1.15674
43	113.4	112.864	112.238	0.626597	0.535903
44	112.4	112.962	112.596	0.366597	-0.562431
45	112.4	113.105	112.892	0.213264	-0.704931
46	112.2	113.072	113.163	-0.0900694	-0.872431
47	112.6	113.103	113.404	-0.300903	-0.503264
48	112.7	113.109	113.65	-0.540903	-0.409097
49	113.8	113.812	113.954	-0.141736	-0.0124306
50	114.1	114.327	114.379	-0.0525694	-0.226597
51	114.7	114.869	114.921	-0.0517361	-0.169097
52	115.3	115.435	115.533	-0.0984028	-0.134931
53	115.6	116.164	116.171	-0.00673611	-0.564097
54	116.2	116.856	116.779	0.0765972	-0.655764
55	117.5	117.956	117.329	0.626597	-0.455764
56	118.5	118.187	117.821	0.366597	0.312569
57	119.3	118.463	118.25	0.213264	0.836736
58	120	118.506	118.596	-0.0900694	1.49424
59	120.1	118.587	118.888	-0.300903	1.5134
60	119.8	118.601	119.142	-0.540903	1.19924
61	119.9	119.192	119.333	-0.141736	0.708403
62	119.8	119.385	119.438	-0.0525694	0.415069
63	119.3	119.386	119.438	-0.0517361	-0.0857639
64	119	119.185	119.283	-0.0984028	-0.184931
65	118.9	119.039	119.046	-0.00673611	-0.139097
66	119	118.91	118.833	0.0765972	0.0900694
67	119.3	NA	NA	0.626597	NA
68	119.2	NA	NA	0.366597	NA
69	118.6	NA	NA	0.213264	NA
70	117	NA	NA	-0.0900694	NA
71	117.4	NA	NA	-0.300903	NA
72	117.4	NA	NA	-0.540903	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