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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 09 Dec 2013 06:11:35 -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/2013/Dec/09/t1386587508gcmn4o5ujyag0ks.htm/, Retrieved Wed, 24 Apr 2024 23:54:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231612, Retrieved Wed, 24 Apr 2024 23:54:47 +0000

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-       [Classical Decomposition] [] [2013-12-09 11:11:35] [d41d8cd98f00b204e9800998ecf8427e] [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	6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231612&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]6 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=231612&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231612&T=0

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	99.42	NA	NA	-2.80333	NA
2	99.42	NA	NA	-2.91027	NA
3	99.42	NA	NA	-3.19486	NA
4	99.42	NA	NA	-2.69083	NA
5	99.42	NA	NA	-2.29013	NA
6	109.26	NA	NA	3.43299	NA
7	110	110.695	103.01	7.6848	-0.695214
8	110	110.273	103.063	7.21001	-0.272922
9	109.26	106.409	103.115	3.29313	2.85145
10	100.07	101.186	103.168	-1.98173	-1.11619
11	100.07	100.597	103.22	-2.62312	-0.527297
12	100.05	100.1	103.226	-3.12666	-0.0495891
13	100.05	100.458	103.261	-2.80333	-0.407506
14	100.05	100.472	103.383	-2.91027	-0.422228
15	100.05	100.223	103.418	-3.19486	-0.173478
16	100.05	100.824	103.515	-2.69083	-0.774172
17	100.05	101.469	103.759	-2.29013	-1.41903
18	108.77	107.421	103.988	3.43299	1.34867
19	111.32	111.898	104.213	7.6848	-0.578131
20	111.6	111.648	104.438	7.21001	-0.0483391
21	108.52	107.956	104.663	3.29313	0.563536
22	103.13	102.907	104.888	-1.98173	0.223397
23	102.87	102.49	105.113	-2.62312	0.379786
24	102.75	102.368	105.495	-3.12666	0.382078
25	102.75	103.135	105.939	-2.80333	-0.385422
26	102.75	103.362	106.273	-2.91027	-0.612228
27	102.75	103.381	106.575	-3.19486	-0.630561
28	102.75	104.229	106.92	-2.69083	-1.47917
29	102.75	105.02	107.31	-2.29013	-2.26987
30	115.22	111.109	107.676	3.43299	4.11076
31	115.53	115.714	108.029	7.6848	-0.183547
32	115.4	115.591	108.381	7.21001	-0.191256
33	111.99	112.027	108.734	3.29313	-0.0368808
34	107.93	107.105	109.086	-1.98173	0.82548
35	107.43	106.816	109.439	-2.62312	0.614369
36	106.98	106.425	109.552	-3.12666	0.554578
37	106.98	106.821	109.624	-2.80333	0.159161
38	106.98	106.98	109.89	-2.91027	0.000271991
39	106.98	107	110.195	-3.19486	-0.019728
40	106.98	107.785	110.476	-2.69083	-0.805422
41	106.98	108.404	110.694	-2.29013	-1.42362
42	113.71	114.358	110.925	3.43299	-0.647992
43	118.77	118.853	111.168	7.6848	-0.0831308
44	118.54	118.656	111.446	7.21001	-0.115839
45	116.16	115.024	111.731	3.29313	1.13562
46	110.52	110.008	111.99	-1.98173	0.512147
47	110.06	109.723	112.346	-2.62312	0.336869
48	109.9	109.42	112.547	-3.12666	0.479578
49	109.9	109.761	112.564	-2.80333	0.139161
50	110.72	109.752	112.662	-2.91027	0.967772
51	110.09	109.421	112.615	-3.19486	0.669439
52	110.07	109.823	112.513	-2.69083	0.247494
53	112.45	110.225	112.515	-2.29013	2.22513
54	113.06	115.949	112.516	3.43299	-2.88883
55	119.83	120.218	112.533	7.6848	-0.388131
56	119.84	119.748	112.538	7.21001	0.0924942
57	113.73	115.836	112.543	3.29313	-2.10646
58	110.5	110.685	112.666	-1.98173	-0.18452
59	110.12	110.131	112.754	-2.62312	-0.0106308
60	109.86	109.731	112.857	-3.12666	0.129161
61	110.36	110.303	113.106	-2.80333	0.0570775
62	110.36	110.386	113.296	-2.91027	-0.0255613
63	110.59	110.194	113.389	-3.19486	0.395689
64	112.52	110.777	113.468	-2.69083	1.74291
65	112.1	111.244	113.535	-2.29013	0.85555
66	115.9	116.986	113.553	3.43299	-1.08591
67	122.96	121.318	113.633	7.6848	1.64187
68	121.26	121.01	113.8	7.21001	0.249578
69	114.55	117.244	113.95	3.29313	-2.69355
70	111.57	112.117	114.098	-1.98173	-0.546603
71	110.65	111.729	114.352	-2.62312	-1.07938
72	109.77	111.552	114.679	-3.12666	-1.78209
73	112.38	112.229	115.032	-2.80333	0.151244
74	112.35	112.544	115.455	-2.91027	-0.194311
75	112.2	112.728	115.922	-3.19486	-0.527645
76	114.46	113.678	116.369	-2.69083	0.782078
77	116.26	114.514	116.805	-2.29013	1.74555
78	119.57	120.693	117.26	3.43299	-1.12299
79	127.77	NA	NA	7.6848	NA
80	126.59	NA	NA	7.21001	NA
81	120.45	NA	NA	3.29313	NA
82	116.38	NA	NA	-1.98173	NA
83	116.3	NA	NA	-2.62312	NA
84	115.05	NA	NA	-3.12666	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 99.42 & NA & NA & -2.80333 & NA \tabularnewline
2 & 99.42 & NA & NA & -2.91027 & NA \tabularnewline
3 & 99.42 & NA & NA & -3.19486 & NA \tabularnewline
4 & 99.42 & NA & NA & -2.69083 & NA \tabularnewline
5 & 99.42 & NA & NA & -2.29013 & NA \tabularnewline
6 & 109.26 & NA & NA & 3.43299 & NA \tabularnewline
7 & 110 & 110.695 & 103.01 & 7.6848 & -0.695214 \tabularnewline
8 & 110 & 110.273 & 103.063 & 7.21001 & -0.272922 \tabularnewline
9 & 109.26 & 106.409 & 103.115 & 3.29313 & 2.85145 \tabularnewline
10 & 100.07 & 101.186 & 103.168 & -1.98173 & -1.11619 \tabularnewline
11 & 100.07 & 100.597 & 103.22 & -2.62312 & -0.527297 \tabularnewline
12 & 100.05 & 100.1 & 103.226 & -3.12666 & -0.0495891 \tabularnewline
13 & 100.05 & 100.458 & 103.261 & -2.80333 & -0.407506 \tabularnewline
14 & 100.05 & 100.472 & 103.383 & -2.91027 & -0.422228 \tabularnewline
15 & 100.05 & 100.223 & 103.418 & -3.19486 & -0.173478 \tabularnewline
16 & 100.05 & 100.824 & 103.515 & -2.69083 & -0.774172 \tabularnewline
17 & 100.05 & 101.469 & 103.759 & -2.29013 & -1.41903 \tabularnewline
18 & 108.77 & 107.421 & 103.988 & 3.43299 & 1.34867 \tabularnewline
19 & 111.32 & 111.898 & 104.213 & 7.6848 & -0.578131 \tabularnewline
20 & 111.6 & 111.648 & 104.438 & 7.21001 & -0.0483391 \tabularnewline
21 & 108.52 & 107.956 & 104.663 & 3.29313 & 0.563536 \tabularnewline
22 & 103.13 & 102.907 & 104.888 & -1.98173 & 0.223397 \tabularnewline
23 & 102.87 & 102.49 & 105.113 & -2.62312 & 0.379786 \tabularnewline
24 & 102.75 & 102.368 & 105.495 & -3.12666 & 0.382078 \tabularnewline
25 & 102.75 & 103.135 & 105.939 & -2.80333 & -0.385422 \tabularnewline
26 & 102.75 & 103.362 & 106.273 & -2.91027 & -0.612228 \tabularnewline
27 & 102.75 & 103.381 & 106.575 & -3.19486 & -0.630561 \tabularnewline
28 & 102.75 & 104.229 & 106.92 & -2.69083 & -1.47917 \tabularnewline
29 & 102.75 & 105.02 & 107.31 & -2.29013 & -2.26987 \tabularnewline
30 & 115.22 & 111.109 & 107.676 & 3.43299 & 4.11076 \tabularnewline
31 & 115.53 & 115.714 & 108.029 & 7.6848 & -0.183547 \tabularnewline
32 & 115.4 & 115.591 & 108.381 & 7.21001 & -0.191256 \tabularnewline
33 & 111.99 & 112.027 & 108.734 & 3.29313 & -0.0368808 \tabularnewline
34 & 107.93 & 107.105 & 109.086 & -1.98173 & 0.82548 \tabularnewline
35 & 107.43 & 106.816 & 109.439 & -2.62312 & 0.614369 \tabularnewline
36 & 106.98 & 106.425 & 109.552 & -3.12666 & 0.554578 \tabularnewline
37 & 106.98 & 106.821 & 109.624 & -2.80333 & 0.159161 \tabularnewline
38 & 106.98 & 106.98 & 109.89 & -2.91027 & 0.000271991 \tabularnewline
39 & 106.98 & 107 & 110.195 & -3.19486 & -0.019728 \tabularnewline
40 & 106.98 & 107.785 & 110.476 & -2.69083 & -0.805422 \tabularnewline
41 & 106.98 & 108.404 & 110.694 & -2.29013 & -1.42362 \tabularnewline
42 & 113.71 & 114.358 & 110.925 & 3.43299 & -0.647992 \tabularnewline
43 & 118.77 & 118.853 & 111.168 & 7.6848 & -0.0831308 \tabularnewline
44 & 118.54 & 118.656 & 111.446 & 7.21001 & -0.115839 \tabularnewline
45 & 116.16 & 115.024 & 111.731 & 3.29313 & 1.13562 \tabularnewline
46 & 110.52 & 110.008 & 111.99 & -1.98173 & 0.512147 \tabularnewline
47 & 110.06 & 109.723 & 112.346 & -2.62312 & 0.336869 \tabularnewline
48 & 109.9 & 109.42 & 112.547 & -3.12666 & 0.479578 \tabularnewline
49 & 109.9 & 109.761 & 112.564 & -2.80333 & 0.139161 \tabularnewline
50 & 110.72 & 109.752 & 112.662 & -2.91027 & 0.967772 \tabularnewline
51 & 110.09 & 109.421 & 112.615 & -3.19486 & 0.669439 \tabularnewline
52 & 110.07 & 109.823 & 112.513 & -2.69083 & 0.247494 \tabularnewline
53 & 112.45 & 110.225 & 112.515 & -2.29013 & 2.22513 \tabularnewline
54 & 113.06 & 115.949 & 112.516 & 3.43299 & -2.88883 \tabularnewline
55 & 119.83 & 120.218 & 112.533 & 7.6848 & -0.388131 \tabularnewline
56 & 119.84 & 119.748 & 112.538 & 7.21001 & 0.0924942 \tabularnewline
57 & 113.73 & 115.836 & 112.543 & 3.29313 & -2.10646 \tabularnewline
58 & 110.5 & 110.685 & 112.666 & -1.98173 & -0.18452 \tabularnewline
59 & 110.12 & 110.131 & 112.754 & -2.62312 & -0.0106308 \tabularnewline
60 & 109.86 & 109.731 & 112.857 & -3.12666 & 0.129161 \tabularnewline
61 & 110.36 & 110.303 & 113.106 & -2.80333 & 0.0570775 \tabularnewline
62 & 110.36 & 110.386 & 113.296 & -2.91027 & -0.0255613 \tabularnewline
63 & 110.59 & 110.194 & 113.389 & -3.19486 & 0.395689 \tabularnewline
64 & 112.52 & 110.777 & 113.468 & -2.69083 & 1.74291 \tabularnewline
65 & 112.1 & 111.244 & 113.535 & -2.29013 & 0.85555 \tabularnewline
66 & 115.9 & 116.986 & 113.553 & 3.43299 & -1.08591 \tabularnewline
67 & 122.96 & 121.318 & 113.633 & 7.6848 & 1.64187 \tabularnewline
68 & 121.26 & 121.01 & 113.8 & 7.21001 & 0.249578 \tabularnewline
69 & 114.55 & 117.244 & 113.95 & 3.29313 & -2.69355 \tabularnewline
70 & 111.57 & 112.117 & 114.098 & -1.98173 & -0.546603 \tabularnewline
71 & 110.65 & 111.729 & 114.352 & -2.62312 & -1.07938 \tabularnewline
72 & 109.77 & 111.552 & 114.679 & -3.12666 & -1.78209 \tabularnewline
73 & 112.38 & 112.229 & 115.032 & -2.80333 & 0.151244 \tabularnewline
74 & 112.35 & 112.544 & 115.455 & -2.91027 & -0.194311 \tabularnewline
75 & 112.2 & 112.728 & 115.922 & -3.19486 & -0.527645 \tabularnewline
76 & 114.46 & 113.678 & 116.369 & -2.69083 & 0.782078 \tabularnewline
77 & 116.26 & 114.514 & 116.805 & -2.29013 & 1.74555 \tabularnewline
78 & 119.57 & 120.693 & 117.26 & 3.43299 & -1.12299 \tabularnewline
79 & 127.77 & NA & NA & 7.6848 & NA \tabularnewline
80 & 126.59 & NA & NA & 7.21001 & NA \tabularnewline
81 & 120.45 & NA & NA & 3.29313 & NA \tabularnewline
82 & 116.38 & NA & NA & -1.98173 & NA \tabularnewline
83 & 116.3 & NA & NA & -2.62312 & NA \tabularnewline
84 & 115.05 & NA & NA & -3.12666 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231612&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]99.42[/C][C]NA[/C][C]NA[/C][C]-2.80333[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]99.42[/C][C]NA[/C][C]NA[/C][C]-2.91027[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]99.42[/C][C]NA[/C][C]NA[/C][C]-3.19486[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]99.42[/C][C]NA[/C][C]NA[/C][C]-2.69083[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]99.42[/C][C]NA[/C][C]NA[/C][C]-2.29013[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]109.26[/C][C]NA[/C][C]NA[/C][C]3.43299[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]110[/C][C]110.695[/C][C]103.01[/C][C]7.6848[/C][C]-0.695214[/C][/ROW]
[ROW][C]8[/C][C]110[/C][C]110.273[/C][C]103.063[/C][C]7.21001[/C][C]-0.272922[/C][/ROW]
[ROW][C]9[/C][C]109.26[/C][C]106.409[/C][C]103.115[/C][C]3.29313[/C][C]2.85145[/C][/ROW]
[ROW][C]10[/C][C]100.07[/C][C]101.186[/C][C]103.168[/C][C]-1.98173[/C][C]-1.11619[/C][/ROW]
[ROW][C]11[/C][C]100.07[/C][C]100.597[/C][C]103.22[/C][C]-2.62312[/C][C]-0.527297[/C][/ROW]
[ROW][C]12[/C][C]100.05[/C][C]100.1[/C][C]103.226[/C][C]-3.12666[/C][C]-0.0495891[/C][/ROW]
[ROW][C]13[/C][C]100.05[/C][C]100.458[/C][C]103.261[/C][C]-2.80333[/C][C]-0.407506[/C][/ROW]
[ROW][C]14[/C][C]100.05[/C][C]100.472[/C][C]103.383[/C][C]-2.91027[/C][C]-0.422228[/C][/ROW]
[ROW][C]15[/C][C]100.05[/C][C]100.223[/C][C]103.418[/C][C]-3.19486[/C][C]-0.173478[/C][/ROW]
[ROW][C]16[/C][C]100.05[/C][C]100.824[/C][C]103.515[/C][C]-2.69083[/C][C]-0.774172[/C][/ROW]
[ROW][C]17[/C][C]100.05[/C][C]101.469[/C][C]103.759[/C][C]-2.29013[/C][C]-1.41903[/C][/ROW]
[ROW][C]18[/C][C]108.77[/C][C]107.421[/C][C]103.988[/C][C]3.43299[/C][C]1.34867[/C][/ROW]
[ROW][C]19[/C][C]111.32[/C][C]111.898[/C][C]104.213[/C][C]7.6848[/C][C]-0.578131[/C][/ROW]
[ROW][C]20[/C][C]111.6[/C][C]111.648[/C][C]104.438[/C][C]7.21001[/C][C]-0.0483391[/C][/ROW]
[ROW][C]21[/C][C]108.52[/C][C]107.956[/C][C]104.663[/C][C]3.29313[/C][C]0.563536[/C][/ROW]
[ROW][C]22[/C][C]103.13[/C][C]102.907[/C][C]104.888[/C][C]-1.98173[/C][C]0.223397[/C][/ROW]
[ROW][C]23[/C][C]102.87[/C][C]102.49[/C][C]105.113[/C][C]-2.62312[/C][C]0.379786[/C][/ROW]
[ROW][C]24[/C][C]102.75[/C][C]102.368[/C][C]105.495[/C][C]-3.12666[/C][C]0.382078[/C][/ROW]
[ROW][C]25[/C][C]102.75[/C][C]103.135[/C][C]105.939[/C][C]-2.80333[/C][C]-0.385422[/C][/ROW]
[ROW][C]26[/C][C]102.75[/C][C]103.362[/C][C]106.273[/C][C]-2.91027[/C][C]-0.612228[/C][/ROW]
[ROW][C]27[/C][C]102.75[/C][C]103.381[/C][C]106.575[/C][C]-3.19486[/C][C]-0.630561[/C][/ROW]
[ROW][C]28[/C][C]102.75[/C][C]104.229[/C][C]106.92[/C][C]-2.69083[/C][C]-1.47917[/C][/ROW]
[ROW][C]29[/C][C]102.75[/C][C]105.02[/C][C]107.31[/C][C]-2.29013[/C][C]-2.26987[/C][/ROW]
[ROW][C]30[/C][C]115.22[/C][C]111.109[/C][C]107.676[/C][C]3.43299[/C][C]4.11076[/C][/ROW]
[ROW][C]31[/C][C]115.53[/C][C]115.714[/C][C]108.029[/C][C]7.6848[/C][C]-0.183547[/C][/ROW]
[ROW][C]32[/C][C]115.4[/C][C]115.591[/C][C]108.381[/C][C]7.21001[/C][C]-0.191256[/C][/ROW]
[ROW][C]33[/C][C]111.99[/C][C]112.027[/C][C]108.734[/C][C]3.29313[/C][C]-0.0368808[/C][/ROW]
[ROW][C]34[/C][C]107.93[/C][C]107.105[/C][C]109.086[/C][C]-1.98173[/C][C]0.82548[/C][/ROW]
[ROW][C]35[/C][C]107.43[/C][C]106.816[/C][C]109.439[/C][C]-2.62312[/C][C]0.614369[/C][/ROW]
[ROW][C]36[/C][C]106.98[/C][C]106.425[/C][C]109.552[/C][C]-3.12666[/C][C]0.554578[/C][/ROW]
[ROW][C]37[/C][C]106.98[/C][C]106.821[/C][C]109.624[/C][C]-2.80333[/C][C]0.159161[/C][/ROW]
[ROW][C]38[/C][C]106.98[/C][C]106.98[/C][C]109.89[/C][C]-2.91027[/C][C]0.000271991[/C][/ROW]
[ROW][C]39[/C][C]106.98[/C][C]107[/C][C]110.195[/C][C]-3.19486[/C][C]-0.019728[/C][/ROW]
[ROW][C]40[/C][C]106.98[/C][C]107.785[/C][C]110.476[/C][C]-2.69083[/C][C]-0.805422[/C][/ROW]
[ROW][C]41[/C][C]106.98[/C][C]108.404[/C][C]110.694[/C][C]-2.29013[/C][C]-1.42362[/C][/ROW]
[ROW][C]42[/C][C]113.71[/C][C]114.358[/C][C]110.925[/C][C]3.43299[/C][C]-0.647992[/C][/ROW]
[ROW][C]43[/C][C]118.77[/C][C]118.853[/C][C]111.168[/C][C]7.6848[/C][C]-0.0831308[/C][/ROW]
[ROW][C]44[/C][C]118.54[/C][C]118.656[/C][C]111.446[/C][C]7.21001[/C][C]-0.115839[/C][/ROW]
[ROW][C]45[/C][C]116.16[/C][C]115.024[/C][C]111.731[/C][C]3.29313[/C][C]1.13562[/C][/ROW]
[ROW][C]46[/C][C]110.52[/C][C]110.008[/C][C]111.99[/C][C]-1.98173[/C][C]0.512147[/C][/ROW]
[ROW][C]47[/C][C]110.06[/C][C]109.723[/C][C]112.346[/C][C]-2.62312[/C][C]0.336869[/C][/ROW]
[ROW][C]48[/C][C]109.9[/C][C]109.42[/C][C]112.547[/C][C]-3.12666[/C][C]0.479578[/C][/ROW]
[ROW][C]49[/C][C]109.9[/C][C]109.761[/C][C]112.564[/C][C]-2.80333[/C][C]0.139161[/C][/ROW]
[ROW][C]50[/C][C]110.72[/C][C]109.752[/C][C]112.662[/C][C]-2.91027[/C][C]0.967772[/C][/ROW]
[ROW][C]51[/C][C]110.09[/C][C]109.421[/C][C]112.615[/C][C]-3.19486[/C][C]0.669439[/C][/ROW]
[ROW][C]52[/C][C]110.07[/C][C]109.823[/C][C]112.513[/C][C]-2.69083[/C][C]0.247494[/C][/ROW]
[ROW][C]53[/C][C]112.45[/C][C]110.225[/C][C]112.515[/C][C]-2.29013[/C][C]2.22513[/C][/ROW]
[ROW][C]54[/C][C]113.06[/C][C]115.949[/C][C]112.516[/C][C]3.43299[/C][C]-2.88883[/C][/ROW]
[ROW][C]55[/C][C]119.83[/C][C]120.218[/C][C]112.533[/C][C]7.6848[/C][C]-0.388131[/C][/ROW]
[ROW][C]56[/C][C]119.84[/C][C]119.748[/C][C]112.538[/C][C]7.21001[/C][C]0.0924942[/C][/ROW]
[ROW][C]57[/C][C]113.73[/C][C]115.836[/C][C]112.543[/C][C]3.29313[/C][C]-2.10646[/C][/ROW]
[ROW][C]58[/C][C]110.5[/C][C]110.685[/C][C]112.666[/C][C]-1.98173[/C][C]-0.18452[/C][/ROW]
[ROW][C]59[/C][C]110.12[/C][C]110.131[/C][C]112.754[/C][C]-2.62312[/C][C]-0.0106308[/C][/ROW]
[ROW][C]60[/C][C]109.86[/C][C]109.731[/C][C]112.857[/C][C]-3.12666[/C][C]0.129161[/C][/ROW]
[ROW][C]61[/C][C]110.36[/C][C]110.303[/C][C]113.106[/C][C]-2.80333[/C][C]0.0570775[/C][/ROW]
[ROW][C]62[/C][C]110.36[/C][C]110.386[/C][C]113.296[/C][C]-2.91027[/C][C]-0.0255613[/C][/ROW]
[ROW][C]63[/C][C]110.59[/C][C]110.194[/C][C]113.389[/C][C]-3.19486[/C][C]0.395689[/C][/ROW]
[ROW][C]64[/C][C]112.52[/C][C]110.777[/C][C]113.468[/C][C]-2.69083[/C][C]1.74291[/C][/ROW]
[ROW][C]65[/C][C]112.1[/C][C]111.244[/C][C]113.535[/C][C]-2.29013[/C][C]0.85555[/C][/ROW]
[ROW][C]66[/C][C]115.9[/C][C]116.986[/C][C]113.553[/C][C]3.43299[/C][C]-1.08591[/C][/ROW]
[ROW][C]67[/C][C]122.96[/C][C]121.318[/C][C]113.633[/C][C]7.6848[/C][C]1.64187[/C][/ROW]
[ROW][C]68[/C][C]121.26[/C][C]121.01[/C][C]113.8[/C][C]7.21001[/C][C]0.249578[/C][/ROW]
[ROW][C]69[/C][C]114.55[/C][C]117.244[/C][C]113.95[/C][C]3.29313[/C][C]-2.69355[/C][/ROW]
[ROW][C]70[/C][C]111.57[/C][C]112.117[/C][C]114.098[/C][C]-1.98173[/C][C]-0.546603[/C][/ROW]
[ROW][C]71[/C][C]110.65[/C][C]111.729[/C][C]114.352[/C][C]-2.62312[/C][C]-1.07938[/C][/ROW]
[ROW][C]72[/C][C]109.77[/C][C]111.552[/C][C]114.679[/C][C]-3.12666[/C][C]-1.78209[/C][/ROW]
[ROW][C]73[/C][C]112.38[/C][C]112.229[/C][C]115.032[/C][C]-2.80333[/C][C]0.151244[/C][/ROW]
[ROW][C]74[/C][C]112.35[/C][C]112.544[/C][C]115.455[/C][C]-2.91027[/C][C]-0.194311[/C][/ROW]
[ROW][C]75[/C][C]112.2[/C][C]112.728[/C][C]115.922[/C][C]-3.19486[/C][C]-0.527645[/C][/ROW]
[ROW][C]76[/C][C]114.46[/C][C]113.678[/C][C]116.369[/C][C]-2.69083[/C][C]0.782078[/C][/ROW]
[ROW][C]77[/C][C]116.26[/C][C]114.514[/C][C]116.805[/C][C]-2.29013[/C][C]1.74555[/C][/ROW]
[ROW][C]78[/C][C]119.57[/C][C]120.693[/C][C]117.26[/C][C]3.43299[/C][C]-1.12299[/C][/ROW]
[ROW][C]79[/C][C]127.77[/C][C]NA[/C][C]NA[/C][C]7.6848[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]126.59[/C][C]NA[/C][C]NA[/C][C]7.21001[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]120.45[/C][C]NA[/C][C]NA[/C][C]3.29313[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]116.38[/C][C]NA[/C][C]NA[/C][C]-1.98173[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]116.3[/C][C]NA[/C][C]NA[/C][C]-2.62312[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]115.05[/C][C]NA[/C][C]NA[/C][C]-3.12666[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231612&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231612&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	99.42	NA	NA	-2.80333	NA
2	99.42	NA	NA	-2.91027	NA
3	99.42	NA	NA	-3.19486	NA
4	99.42	NA	NA	-2.69083	NA
5	99.42	NA	NA	-2.29013	NA
6	109.26	NA	NA	3.43299	NA
7	110	110.695	103.01	7.6848	-0.695214
8	110	110.273	103.063	7.21001	-0.272922
9	109.26	106.409	103.115	3.29313	2.85145
10	100.07	101.186	103.168	-1.98173	-1.11619
11	100.07	100.597	103.22	-2.62312	-0.527297
12	100.05	100.1	103.226	-3.12666	-0.0495891
13	100.05	100.458	103.261	-2.80333	-0.407506
14	100.05	100.472	103.383	-2.91027	-0.422228
15	100.05	100.223	103.418	-3.19486	-0.173478
16	100.05	100.824	103.515	-2.69083	-0.774172
17	100.05	101.469	103.759	-2.29013	-1.41903
18	108.77	107.421	103.988	3.43299	1.34867
19	111.32	111.898	104.213	7.6848	-0.578131
20	111.6	111.648	104.438	7.21001	-0.0483391
21	108.52	107.956	104.663	3.29313	0.563536
22	103.13	102.907	104.888	-1.98173	0.223397
23	102.87	102.49	105.113	-2.62312	0.379786
24	102.75	102.368	105.495	-3.12666	0.382078
25	102.75	103.135	105.939	-2.80333	-0.385422
26	102.75	103.362	106.273	-2.91027	-0.612228
27	102.75	103.381	106.575	-3.19486	-0.630561
28	102.75	104.229	106.92	-2.69083	-1.47917
29	102.75	105.02	107.31	-2.29013	-2.26987
30	115.22	111.109	107.676	3.43299	4.11076
31	115.53	115.714	108.029	7.6848	-0.183547
32	115.4	115.591	108.381	7.21001	-0.191256
33	111.99	112.027	108.734	3.29313	-0.0368808
34	107.93	107.105	109.086	-1.98173	0.82548
35	107.43	106.816	109.439	-2.62312	0.614369
36	106.98	106.425	109.552	-3.12666	0.554578
37	106.98	106.821	109.624	-2.80333	0.159161
38	106.98	106.98	109.89	-2.91027	0.000271991
39	106.98	107	110.195	-3.19486	-0.019728
40	106.98	107.785	110.476	-2.69083	-0.805422
41	106.98	108.404	110.694	-2.29013	-1.42362
42	113.71	114.358	110.925	3.43299	-0.647992
43	118.77	118.853	111.168	7.6848	-0.0831308
44	118.54	118.656	111.446	7.21001	-0.115839
45	116.16	115.024	111.731	3.29313	1.13562
46	110.52	110.008	111.99	-1.98173	0.512147
47	110.06	109.723	112.346	-2.62312	0.336869
48	109.9	109.42	112.547	-3.12666	0.479578
49	109.9	109.761	112.564	-2.80333	0.139161
50	110.72	109.752	112.662	-2.91027	0.967772
51	110.09	109.421	112.615	-3.19486	0.669439
52	110.07	109.823	112.513	-2.69083	0.247494
53	112.45	110.225	112.515	-2.29013	2.22513
54	113.06	115.949	112.516	3.43299	-2.88883
55	119.83	120.218	112.533	7.6848	-0.388131
56	119.84	119.748	112.538	7.21001	0.0924942
57	113.73	115.836	112.543	3.29313	-2.10646
58	110.5	110.685	112.666	-1.98173	-0.18452
59	110.12	110.131	112.754	-2.62312	-0.0106308
60	109.86	109.731	112.857	-3.12666	0.129161
61	110.36	110.303	113.106	-2.80333	0.0570775
62	110.36	110.386	113.296	-2.91027	-0.0255613
63	110.59	110.194	113.389	-3.19486	0.395689
64	112.52	110.777	113.468	-2.69083	1.74291
65	112.1	111.244	113.535	-2.29013	0.85555
66	115.9	116.986	113.553	3.43299	-1.08591
67	122.96	121.318	113.633	7.6848	1.64187
68	121.26	121.01	113.8	7.21001	0.249578
69	114.55	117.244	113.95	3.29313	-2.69355
70	111.57	112.117	114.098	-1.98173	-0.546603
71	110.65	111.729	114.352	-2.62312	-1.07938
72	109.77	111.552	114.679	-3.12666	-1.78209
73	112.38	112.229	115.032	-2.80333	0.151244
74	112.35	112.544	115.455	-2.91027	-0.194311
75	112.2	112.728	115.922	-3.19486	-0.527645
76	114.46	113.678	116.369	-2.69083	0.782078
77	116.26	114.514	116.805	-2.29013	1.74555
78	119.57	120.693	117.26	3.43299	-1.12299
79	127.77	NA	NA	7.6848	NA
80	126.59	NA	NA	7.21001	NA
81	120.45	NA	NA	3.29313	NA
82	116.38	NA	NA	-1.98173	NA
83	116.3	NA	NA	-2.62312	NA
84	115.05	NA	NA	-3.12666	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