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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 08 Jan 2017 21:18:03 +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/2017/Jan/08/t14839103199p3l57lxsuufhfu.htm/, Retrieved Tue, 14 May 2024 02:53:44 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Tue, 14 May 2024 02:53:44 +0200

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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	'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.98	NA	NA	-0.22434	NA
2	98.97	NA	NA	-0.251424	NA
3	98.91	NA	NA	-0.223257	NA
4	98.98	NA	NA	-0.23959	NA
5	98.95	NA	NA	-0.220174	NA
6	98.96	NA	NA	-0.238257	NA
7	98.96	99.1131	99.3404	-0.22734	-0.153076
8	99.04	99.2317	99.4458	-0.214174	-0.19166
9	99.33	99.5946	99.5638	0.0308264	-0.264576
10	100.04	100.228	99.6938	0.534243	-0.187993
11	100.14	100.467	99.825	0.641576	-0.326576
12	100.21	100.585	99.9529	0.63191	-0.374826
13	100.21	99.8544	100.079	-0.22434	0.35559
14	100.27	99.9507	100.202	-0.251424	0.31934
15	100.44	100.109	100.332	-0.223257	0.331174
16	100.57	100.227	100.467	-0.23959	0.342507
17	100.51	100.375	100.595	-0.220174	0.134757
18	100.47	100.484	100.722	-0.238257	-0.0138264
19	100.47	100.622	100.85	-0.22734	-0.152243
20	100.49	100.76	100.974	-0.214174	-0.269993
21	101	101.121	101.09	0.0308264	-0.121243
22	101.61	101.732	101.198	0.534243	-0.12216
23	101.65	101.952	101.311	0.641576	-0.30241
24	101.74	102.071	101.439	0.63191	-0.331076
25	101.74	101.35	101.574	-0.22434	0.390174
26	101.73	101.456	101.708	-0.251424	0.273507
27	101.77	101.61	101.833	-0.223257	0.159924
28	101.82	101.702	101.941	-0.23959	0.11834
29	101.97	101.828	102.048	-0.220174	0.142257
30	102.09	101.923	102.162	-0.238257	0.16659
31	102.09	101.883	102.11	-0.22734	0.20734
32	102.08	101.682	101.897	-0.214174	0.397507
33	102.42	101.716	101.685	0.0308264	0.704174
34	102.78	102.009	101.475	0.534243	0.771174
35	103.04	101.907	101.265	0.641576	1.13301
36	103.08	101.684	101.052	0.63191	1.39559
37	99.16	100.631	100.855	-0.22434	-1.47066
38	99.19	100.434	100.685	-0.251424	-1.24358
39	99.23	100.298	100.521	-0.223257	-1.06799
40	99.31	100.129	100.368	-0.23959	-0.818743
41	99.46	100.004	100.224	-0.220174	-0.543993
42	99.49	99.8367	100.075	-0.238257	-0.346743
43	99.95	99.851	100.078	-0.22734	0.0990069
44	100.14	100.023	100.237	-0.214174	0.11709
45	100.43	100.425	100.394	0.0308264	0.00500694
46	101.1	101.074	100.54	0.534243	0.0257569
47	101.26	101.315	100.674	0.641576	-0.0553264
48	101.28	101.433	100.801	0.63191	-0.152743
49	101.04	100.691	100.915	-0.22434	0.34934
50	101.12	100.761	101.013	-0.251424	0.358507
51	101.07	100.873	101.097	-0.223257	0.19659
52	100.97	100.923	101.163	-0.23959	0.0466736
53	101.01	101.005	101.225	-0.220174	0.00517361
54	100.99	101.054	101.292	-0.238257	-0.0638264
55	101.19	101.15	101.377	-0.22734	0.0402569
56	101.25	101.262	101.476	-0.214174	-0.0116597
57	101.33	101.612	101.581	0.0308264	-0.282076
58	101.79	102.235	101.701	0.534243	-0.445493
59	102.06	102.467	101.826	0.641576	-0.40741
60	102.09	102.586	101.954	0.63191	-0.49566
61	102.27	101.853	102.078	-0.22434	0.41684
62	102.26	101.926	102.178	-0.251424	0.333507
63	102.46	102.038	102.262	-0.223257	0.42159
64	102.46	102.107	102.347	-0.23959	0.352507
65	102.51	102.207	102.427	-0.220174	0.30309
66	102.56	102.261	102.499	-0.238257	0.29909
67	102.59	NA	NA	-0.22734	NA
68	102.26	NA	NA	-0.214174	NA
69	102.33	NA	NA	0.0308264	NA
70	102.84	NA	NA	0.534243	NA
71	102.93	NA	NA	0.641576	NA
72	102.95	NA	NA	0.63191	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 98.98 & NA & NA & -0.22434 & NA \tabularnewline
2 & 98.97 & NA & NA & -0.251424 & NA \tabularnewline
3 & 98.91 & NA & NA & -0.223257 & NA \tabularnewline
4 & 98.98 & NA & NA & -0.23959 & NA \tabularnewline
5 & 98.95 & NA & NA & -0.220174 & NA \tabularnewline
6 & 98.96 & NA & NA & -0.238257 & NA \tabularnewline
7 & 98.96 & 99.1131 & 99.3404 & -0.22734 & -0.153076 \tabularnewline
8 & 99.04 & 99.2317 & 99.4458 & -0.214174 & -0.19166 \tabularnewline
9 & 99.33 & 99.5946 & 99.5638 & 0.0308264 & -0.264576 \tabularnewline
10 & 100.04 & 100.228 & 99.6938 & 0.534243 & -0.187993 \tabularnewline
11 & 100.14 & 100.467 & 99.825 & 0.641576 & -0.326576 \tabularnewline
12 & 100.21 & 100.585 & 99.9529 & 0.63191 & -0.374826 \tabularnewline
13 & 100.21 & 99.8544 & 100.079 & -0.22434 & 0.35559 \tabularnewline
14 & 100.27 & 99.9507 & 100.202 & -0.251424 & 0.31934 \tabularnewline
15 & 100.44 & 100.109 & 100.332 & -0.223257 & 0.331174 \tabularnewline
16 & 100.57 & 100.227 & 100.467 & -0.23959 & 0.342507 \tabularnewline
17 & 100.51 & 100.375 & 100.595 & -0.220174 & 0.134757 \tabularnewline
18 & 100.47 & 100.484 & 100.722 & -0.238257 & -0.0138264 \tabularnewline
19 & 100.47 & 100.622 & 100.85 & -0.22734 & -0.152243 \tabularnewline
20 & 100.49 & 100.76 & 100.974 & -0.214174 & -0.269993 \tabularnewline
21 & 101 & 101.121 & 101.09 & 0.0308264 & -0.121243 \tabularnewline
22 & 101.61 & 101.732 & 101.198 & 0.534243 & -0.12216 \tabularnewline
23 & 101.65 & 101.952 & 101.311 & 0.641576 & -0.30241 \tabularnewline
24 & 101.74 & 102.071 & 101.439 & 0.63191 & -0.331076 \tabularnewline
25 & 101.74 & 101.35 & 101.574 & -0.22434 & 0.390174 \tabularnewline
26 & 101.73 & 101.456 & 101.708 & -0.251424 & 0.273507 \tabularnewline
27 & 101.77 & 101.61 & 101.833 & -0.223257 & 0.159924 \tabularnewline
28 & 101.82 & 101.702 & 101.941 & -0.23959 & 0.11834 \tabularnewline
29 & 101.97 & 101.828 & 102.048 & -0.220174 & 0.142257 \tabularnewline
30 & 102.09 & 101.923 & 102.162 & -0.238257 & 0.16659 \tabularnewline
31 & 102.09 & 101.883 & 102.11 & -0.22734 & 0.20734 \tabularnewline
32 & 102.08 & 101.682 & 101.897 & -0.214174 & 0.397507 \tabularnewline
33 & 102.42 & 101.716 & 101.685 & 0.0308264 & 0.704174 \tabularnewline
34 & 102.78 & 102.009 & 101.475 & 0.534243 & 0.771174 \tabularnewline
35 & 103.04 & 101.907 & 101.265 & 0.641576 & 1.13301 \tabularnewline
36 & 103.08 & 101.684 & 101.052 & 0.63191 & 1.39559 \tabularnewline
37 & 99.16 & 100.631 & 100.855 & -0.22434 & -1.47066 \tabularnewline
38 & 99.19 & 100.434 & 100.685 & -0.251424 & -1.24358 \tabularnewline
39 & 99.23 & 100.298 & 100.521 & -0.223257 & -1.06799 \tabularnewline
40 & 99.31 & 100.129 & 100.368 & -0.23959 & -0.818743 \tabularnewline
41 & 99.46 & 100.004 & 100.224 & -0.220174 & -0.543993 \tabularnewline
42 & 99.49 & 99.8367 & 100.075 & -0.238257 & -0.346743 \tabularnewline
43 & 99.95 & 99.851 & 100.078 & -0.22734 & 0.0990069 \tabularnewline
44 & 100.14 & 100.023 & 100.237 & -0.214174 & 0.11709 \tabularnewline
45 & 100.43 & 100.425 & 100.394 & 0.0308264 & 0.00500694 \tabularnewline
46 & 101.1 & 101.074 & 100.54 & 0.534243 & 0.0257569 \tabularnewline
47 & 101.26 & 101.315 & 100.674 & 0.641576 & -0.0553264 \tabularnewline
48 & 101.28 & 101.433 & 100.801 & 0.63191 & -0.152743 \tabularnewline
49 & 101.04 & 100.691 & 100.915 & -0.22434 & 0.34934 \tabularnewline
50 & 101.12 & 100.761 & 101.013 & -0.251424 & 0.358507 \tabularnewline
51 & 101.07 & 100.873 & 101.097 & -0.223257 & 0.19659 \tabularnewline
52 & 100.97 & 100.923 & 101.163 & -0.23959 & 0.0466736 \tabularnewline
53 & 101.01 & 101.005 & 101.225 & -0.220174 & 0.00517361 \tabularnewline
54 & 100.99 & 101.054 & 101.292 & -0.238257 & -0.0638264 \tabularnewline
55 & 101.19 & 101.15 & 101.377 & -0.22734 & 0.0402569 \tabularnewline
56 & 101.25 & 101.262 & 101.476 & -0.214174 & -0.0116597 \tabularnewline
57 & 101.33 & 101.612 & 101.581 & 0.0308264 & -0.282076 \tabularnewline
58 & 101.79 & 102.235 & 101.701 & 0.534243 & -0.445493 \tabularnewline
59 & 102.06 & 102.467 & 101.826 & 0.641576 & -0.40741 \tabularnewline
60 & 102.09 & 102.586 & 101.954 & 0.63191 & -0.49566 \tabularnewline
61 & 102.27 & 101.853 & 102.078 & -0.22434 & 0.41684 \tabularnewline
62 & 102.26 & 101.926 & 102.178 & -0.251424 & 0.333507 \tabularnewline
63 & 102.46 & 102.038 & 102.262 & -0.223257 & 0.42159 \tabularnewline
64 & 102.46 & 102.107 & 102.347 & -0.23959 & 0.352507 \tabularnewline
65 & 102.51 & 102.207 & 102.427 & -0.220174 & 0.30309 \tabularnewline
66 & 102.56 & 102.261 & 102.499 & -0.238257 & 0.29909 \tabularnewline
67 & 102.59 & NA & NA & -0.22734 & NA \tabularnewline
68 & 102.26 & NA & NA & -0.214174 & NA \tabularnewline
69 & 102.33 & NA & NA & 0.0308264 & NA \tabularnewline
70 & 102.84 & NA & NA & 0.534243 & NA \tabularnewline
71 & 102.93 & NA & NA & 0.641576 & NA \tabularnewline
72 & 102.95 & NA & NA & 0.63191 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]98.98[/C][C]NA[/C][C]NA[/C][C]-0.22434[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]98.97[/C][C]NA[/C][C]NA[/C][C]-0.251424[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]98.91[/C][C]NA[/C][C]NA[/C][C]-0.223257[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]98.98[/C][C]NA[/C][C]NA[/C][C]-0.23959[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]98.95[/C][C]NA[/C][C]NA[/C][C]-0.220174[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]98.96[/C][C]NA[/C][C]NA[/C][C]-0.238257[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]98.96[/C][C]99.1131[/C][C]99.3404[/C][C]-0.22734[/C][C]-0.153076[/C][/ROW]
[ROW][C]8[/C][C]99.04[/C][C]99.2317[/C][C]99.4458[/C][C]-0.214174[/C][C]-0.19166[/C][/ROW]
[ROW][C]9[/C][C]99.33[/C][C]99.5946[/C][C]99.5638[/C][C]0.0308264[/C][C]-0.264576[/C][/ROW]
[ROW][C]10[/C][C]100.04[/C][C]100.228[/C][C]99.6938[/C][C]0.534243[/C][C]-0.187993[/C][/ROW]
[ROW][C]11[/C][C]100.14[/C][C]100.467[/C][C]99.825[/C][C]0.641576[/C][C]-0.326576[/C][/ROW]
[ROW][C]12[/C][C]100.21[/C][C]100.585[/C][C]99.9529[/C][C]0.63191[/C][C]-0.374826[/C][/ROW]
[ROW][C]13[/C][C]100.21[/C][C]99.8544[/C][C]100.079[/C][C]-0.22434[/C][C]0.35559[/C][/ROW]
[ROW][C]14[/C][C]100.27[/C][C]99.9507[/C][C]100.202[/C][C]-0.251424[/C][C]0.31934[/C][/ROW]
[ROW][C]15[/C][C]100.44[/C][C]100.109[/C][C]100.332[/C][C]-0.223257[/C][C]0.331174[/C][/ROW]
[ROW][C]16[/C][C]100.57[/C][C]100.227[/C][C]100.467[/C][C]-0.23959[/C][C]0.342507[/C][/ROW]
[ROW][C]17[/C][C]100.51[/C][C]100.375[/C][C]100.595[/C][C]-0.220174[/C][C]0.134757[/C][/ROW]
[ROW][C]18[/C][C]100.47[/C][C]100.484[/C][C]100.722[/C][C]-0.238257[/C][C]-0.0138264[/C][/ROW]
[ROW][C]19[/C][C]100.47[/C][C]100.622[/C][C]100.85[/C][C]-0.22734[/C][C]-0.152243[/C][/ROW]
[ROW][C]20[/C][C]100.49[/C][C]100.76[/C][C]100.974[/C][C]-0.214174[/C][C]-0.269993[/C][/ROW]
[ROW][C]21[/C][C]101[/C][C]101.121[/C][C]101.09[/C][C]0.0308264[/C][C]-0.121243[/C][/ROW]
[ROW][C]22[/C][C]101.61[/C][C]101.732[/C][C]101.198[/C][C]0.534243[/C][C]-0.12216[/C][/ROW]
[ROW][C]23[/C][C]101.65[/C][C]101.952[/C][C]101.311[/C][C]0.641576[/C][C]-0.30241[/C][/ROW]
[ROW][C]24[/C][C]101.74[/C][C]102.071[/C][C]101.439[/C][C]0.63191[/C][C]-0.331076[/C][/ROW]
[ROW][C]25[/C][C]101.74[/C][C]101.35[/C][C]101.574[/C][C]-0.22434[/C][C]0.390174[/C][/ROW]
[ROW][C]26[/C][C]101.73[/C][C]101.456[/C][C]101.708[/C][C]-0.251424[/C][C]0.273507[/C][/ROW]
[ROW][C]27[/C][C]101.77[/C][C]101.61[/C][C]101.833[/C][C]-0.223257[/C][C]0.159924[/C][/ROW]
[ROW][C]28[/C][C]101.82[/C][C]101.702[/C][C]101.941[/C][C]-0.23959[/C][C]0.11834[/C][/ROW]
[ROW][C]29[/C][C]101.97[/C][C]101.828[/C][C]102.048[/C][C]-0.220174[/C][C]0.142257[/C][/ROW]
[ROW][C]30[/C][C]102.09[/C][C]101.923[/C][C]102.162[/C][C]-0.238257[/C][C]0.16659[/C][/ROW]
[ROW][C]31[/C][C]102.09[/C][C]101.883[/C][C]102.11[/C][C]-0.22734[/C][C]0.20734[/C][/ROW]
[ROW][C]32[/C][C]102.08[/C][C]101.682[/C][C]101.897[/C][C]-0.214174[/C][C]0.397507[/C][/ROW]
[ROW][C]33[/C][C]102.42[/C][C]101.716[/C][C]101.685[/C][C]0.0308264[/C][C]0.704174[/C][/ROW]
[ROW][C]34[/C][C]102.78[/C][C]102.009[/C][C]101.475[/C][C]0.534243[/C][C]0.771174[/C][/ROW]
[ROW][C]35[/C][C]103.04[/C][C]101.907[/C][C]101.265[/C][C]0.641576[/C][C]1.13301[/C][/ROW]
[ROW][C]36[/C][C]103.08[/C][C]101.684[/C][C]101.052[/C][C]0.63191[/C][C]1.39559[/C][/ROW]
[ROW][C]37[/C][C]99.16[/C][C]100.631[/C][C]100.855[/C][C]-0.22434[/C][C]-1.47066[/C][/ROW]
[ROW][C]38[/C][C]99.19[/C][C]100.434[/C][C]100.685[/C][C]-0.251424[/C][C]-1.24358[/C][/ROW]
[ROW][C]39[/C][C]99.23[/C][C]100.298[/C][C]100.521[/C][C]-0.223257[/C][C]-1.06799[/C][/ROW]
[ROW][C]40[/C][C]99.31[/C][C]100.129[/C][C]100.368[/C][C]-0.23959[/C][C]-0.818743[/C][/ROW]
[ROW][C]41[/C][C]99.46[/C][C]100.004[/C][C]100.224[/C][C]-0.220174[/C][C]-0.543993[/C][/ROW]
[ROW][C]42[/C][C]99.49[/C][C]99.8367[/C][C]100.075[/C][C]-0.238257[/C][C]-0.346743[/C][/ROW]
[ROW][C]43[/C][C]99.95[/C][C]99.851[/C][C]100.078[/C][C]-0.22734[/C][C]0.0990069[/C][/ROW]
[ROW][C]44[/C][C]100.14[/C][C]100.023[/C][C]100.237[/C][C]-0.214174[/C][C]0.11709[/C][/ROW]
[ROW][C]45[/C][C]100.43[/C][C]100.425[/C][C]100.394[/C][C]0.0308264[/C][C]0.00500694[/C][/ROW]
[ROW][C]46[/C][C]101.1[/C][C]101.074[/C][C]100.54[/C][C]0.534243[/C][C]0.0257569[/C][/ROW]
[ROW][C]47[/C][C]101.26[/C][C]101.315[/C][C]100.674[/C][C]0.641576[/C][C]-0.0553264[/C][/ROW]
[ROW][C]48[/C][C]101.28[/C][C]101.433[/C][C]100.801[/C][C]0.63191[/C][C]-0.152743[/C][/ROW]
[ROW][C]49[/C][C]101.04[/C][C]100.691[/C][C]100.915[/C][C]-0.22434[/C][C]0.34934[/C][/ROW]
[ROW][C]50[/C][C]101.12[/C][C]100.761[/C][C]101.013[/C][C]-0.251424[/C][C]0.358507[/C][/ROW]
[ROW][C]51[/C][C]101.07[/C][C]100.873[/C][C]101.097[/C][C]-0.223257[/C][C]0.19659[/C][/ROW]
[ROW][C]52[/C][C]100.97[/C][C]100.923[/C][C]101.163[/C][C]-0.23959[/C][C]0.0466736[/C][/ROW]
[ROW][C]53[/C][C]101.01[/C][C]101.005[/C][C]101.225[/C][C]-0.220174[/C][C]0.00517361[/C][/ROW]
[ROW][C]54[/C][C]100.99[/C][C]101.054[/C][C]101.292[/C][C]-0.238257[/C][C]-0.0638264[/C][/ROW]
[ROW][C]55[/C][C]101.19[/C][C]101.15[/C][C]101.377[/C][C]-0.22734[/C][C]0.0402569[/C][/ROW]
[ROW][C]56[/C][C]101.25[/C][C]101.262[/C][C]101.476[/C][C]-0.214174[/C][C]-0.0116597[/C][/ROW]
[ROW][C]57[/C][C]101.33[/C][C]101.612[/C][C]101.581[/C][C]0.0308264[/C][C]-0.282076[/C][/ROW]
[ROW][C]58[/C][C]101.79[/C][C]102.235[/C][C]101.701[/C][C]0.534243[/C][C]-0.445493[/C][/ROW]
[ROW][C]59[/C][C]102.06[/C][C]102.467[/C][C]101.826[/C][C]0.641576[/C][C]-0.40741[/C][/ROW]
[ROW][C]60[/C][C]102.09[/C][C]102.586[/C][C]101.954[/C][C]0.63191[/C][C]-0.49566[/C][/ROW]
[ROW][C]61[/C][C]102.27[/C][C]101.853[/C][C]102.078[/C][C]-0.22434[/C][C]0.41684[/C][/ROW]
[ROW][C]62[/C][C]102.26[/C][C]101.926[/C][C]102.178[/C][C]-0.251424[/C][C]0.333507[/C][/ROW]
[ROW][C]63[/C][C]102.46[/C][C]102.038[/C][C]102.262[/C][C]-0.223257[/C][C]0.42159[/C][/ROW]
[ROW][C]64[/C][C]102.46[/C][C]102.107[/C][C]102.347[/C][C]-0.23959[/C][C]0.352507[/C][/ROW]
[ROW][C]65[/C][C]102.51[/C][C]102.207[/C][C]102.427[/C][C]-0.220174[/C][C]0.30309[/C][/ROW]
[ROW][C]66[/C][C]102.56[/C][C]102.261[/C][C]102.499[/C][C]-0.238257[/C][C]0.29909[/C][/ROW]
[ROW][C]67[/C][C]102.59[/C][C]NA[/C][C]NA[/C][C]-0.22734[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]102.26[/C][C]NA[/C][C]NA[/C][C]-0.214174[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]102.33[/C][C]NA[/C][C]NA[/C][C]0.0308264[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]102.84[/C][C]NA[/C][C]NA[/C][C]0.534243[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]102.93[/C][C]NA[/C][C]NA[/C][C]0.641576[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]102.95[/C][C]NA[/C][C]NA[/C][C]0.63191[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	98.98	NA	NA	-0.22434	NA
2	98.97	NA	NA	-0.251424	NA
3	98.91	NA	NA	-0.223257	NA
4	98.98	NA	NA	-0.23959	NA
5	98.95	NA	NA	-0.220174	NA
6	98.96	NA	NA	-0.238257	NA
7	98.96	99.1131	99.3404	-0.22734	-0.153076
8	99.04	99.2317	99.4458	-0.214174	-0.19166
9	99.33	99.5946	99.5638	0.0308264	-0.264576
10	100.04	100.228	99.6938	0.534243	-0.187993
11	100.14	100.467	99.825	0.641576	-0.326576
12	100.21	100.585	99.9529	0.63191	-0.374826
13	100.21	99.8544	100.079	-0.22434	0.35559
14	100.27	99.9507	100.202	-0.251424	0.31934
15	100.44	100.109	100.332	-0.223257	0.331174
16	100.57	100.227	100.467	-0.23959	0.342507
17	100.51	100.375	100.595	-0.220174	0.134757
18	100.47	100.484	100.722	-0.238257	-0.0138264
19	100.47	100.622	100.85	-0.22734	-0.152243
20	100.49	100.76	100.974	-0.214174	-0.269993
21	101	101.121	101.09	0.0308264	-0.121243
22	101.61	101.732	101.198	0.534243	-0.12216
23	101.65	101.952	101.311	0.641576	-0.30241
24	101.74	102.071	101.439	0.63191	-0.331076
25	101.74	101.35	101.574	-0.22434	0.390174
26	101.73	101.456	101.708	-0.251424	0.273507
27	101.77	101.61	101.833	-0.223257	0.159924
28	101.82	101.702	101.941	-0.23959	0.11834
29	101.97	101.828	102.048	-0.220174	0.142257
30	102.09	101.923	102.162	-0.238257	0.16659
31	102.09	101.883	102.11	-0.22734	0.20734
32	102.08	101.682	101.897	-0.214174	0.397507
33	102.42	101.716	101.685	0.0308264	0.704174
34	102.78	102.009	101.475	0.534243	0.771174
35	103.04	101.907	101.265	0.641576	1.13301
36	103.08	101.684	101.052	0.63191	1.39559
37	99.16	100.631	100.855	-0.22434	-1.47066
38	99.19	100.434	100.685	-0.251424	-1.24358
39	99.23	100.298	100.521	-0.223257	-1.06799
40	99.31	100.129	100.368	-0.23959	-0.818743
41	99.46	100.004	100.224	-0.220174	-0.543993
42	99.49	99.8367	100.075	-0.238257	-0.346743
43	99.95	99.851	100.078	-0.22734	0.0990069
44	100.14	100.023	100.237	-0.214174	0.11709
45	100.43	100.425	100.394	0.0308264	0.00500694
46	101.1	101.074	100.54	0.534243	0.0257569
47	101.26	101.315	100.674	0.641576	-0.0553264
48	101.28	101.433	100.801	0.63191	-0.152743
49	101.04	100.691	100.915	-0.22434	0.34934
50	101.12	100.761	101.013	-0.251424	0.358507
51	101.07	100.873	101.097	-0.223257	0.19659
52	100.97	100.923	101.163	-0.23959	0.0466736
53	101.01	101.005	101.225	-0.220174	0.00517361
54	100.99	101.054	101.292	-0.238257	-0.0638264
55	101.19	101.15	101.377	-0.22734	0.0402569
56	101.25	101.262	101.476	-0.214174	-0.0116597
57	101.33	101.612	101.581	0.0308264	-0.282076
58	101.79	102.235	101.701	0.534243	-0.445493
59	102.06	102.467	101.826	0.641576	-0.40741
60	102.09	102.586	101.954	0.63191	-0.49566
61	102.27	101.853	102.078	-0.22434	0.41684
62	102.26	101.926	102.178	-0.251424	0.333507
63	102.46	102.038	102.262	-0.223257	0.42159
64	102.46	102.107	102.347	-0.23959	0.352507
65	102.51	102.207	102.427	-0.220174	0.30309
66	102.56	102.261	102.499	-0.238257	0.29909
67	102.59	NA	NA	-0.22734	NA
68	102.26	NA	NA	-0.214174	NA
69	102.33	NA	NA	0.0308264	NA
70	102.84	NA	NA	0.534243	NA
71	102.93	NA	NA	0.641576	NA
72	102.95	NA	NA	0.63191	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