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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 01 May 2017 13:54:40 +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/2017/May/01/t1493643303zax1diqp6ghmtba.htm/, Retrieved Fri, 21 Aug 2026 07:36:40 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Fri, 21 Aug 2026 07:36:40 +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	3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.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]3 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=&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	3 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	101.68	NA	NA	-0.0906736	NA
2	101.25	NA	NA	-0.535424	NA
3	101.24	NA	NA	-0.45909	NA
4	101.11	NA	NA	-0.342424	NA
5	101.08	NA	NA	-0.174757	NA
6	101.09	NA	NA	-0.125674	NA
7	101.09	101.152	101.501	-0.348757	-0.0620764
8	101.62	101.583	101.526	0.0574097	0.0367569
9	101.66	101.788	101.552	0.235576	-0.128076
10	101.96	102.086	101.598	0.48766	-0.125993
11	102.04	102.309	101.669	0.64016	-0.269326
12	102.02	102.41	101.754	0.655993	-0.389743
13	102.02	101.751	101.841	-0.0906736	0.269424
14	101.51	101.39	101.925	-0.535424	0.120007
15	101.62	101.559	102.018	-0.45909	0.0607569
16	101.83	101.785	102.127	-0.342424	0.0453403
17	102.06	102.071	102.246	-0.174757	-0.0110764
18	102.14	102.248	102.373	-0.125674	-0.10766
19	102.14	102.155	102.503	-0.348757	-0.0145764
20	102.59	102.681	102.623	0.0574097	-0.0907431
21	102.92	102.966	102.73	0.235576	-0.0455764
22	103.31	103.319	102.832	0.48766	-0.00932639
23	103.54	103.569	102.929	0.64016	-0.0293264
24	103.58	103.68	103.024	0.655993	-0.10016
25	103.58	103.028	103.119	-0.0906736	0.551507
26	102.83	102.681	103.217	-0.535424	0.148757
27	102.86	102.849	103.308	-0.45909	0.0107569
28	103.03	103.047	103.39	-0.342424	-0.0171597
29	103.2	103.291	103.465	-0.174757	-0.0906597
30	103.28	103.412	103.538	-0.125674	-0.132243
31	103.28	103.073	103.422	-0.348757	0.20709
32	103.79	103.174	103.117	0.0574097	0.615507
33	103.92	103.047	102.812	0.235576	0.872757
34	104.26	102.993	102.505	0.48766	1.26734
35	104.41	102.843	102.202	0.64016	1.56734
36	104.45	102.559	101.903	0.655993	1.89109
37	99.92	101.513	101.604	-0.0906736	-1.59349
38	99.18	100.766	101.301	-0.535424	-1.58583
39	99.18	100.54	101	-0.45909	-1.36049
40	99.35	100.365	100.707	-0.342424	-1.01466
41	99.62	100.246	100.421	-0.174757	-0.626076
42	99.67	100.013	100.139	-0.125674	-0.343493
43	99.72	99.7067	100.055	-0.348757	0.0133403
44	100.08	100.25	100.192	0.0574097	-0.16991
45	100.39	100.592	100.357	0.235576	-0.202243
46	100.77	101.003	100.516	0.48766	-0.233493
47	101.03	101.298	100.658	0.64016	-0.268493
48	101.07	101.444	100.788	0.655993	-0.37391
49	101.29	100.805	100.895	-0.0906736	0.485257
50	101.1	100.445	100.98	-0.535424	0.655424
51	101.2	100.592	101.051	-0.45909	0.608257
52	101.15	100.752	101.095	-0.342424	0.39784
53	101.24	100.938	101.112	-0.174757	0.302257
54	101.16	100.999	101.125	-0.125674	0.16109
55	100.81	100.805	101.154	-0.348757	0.00500694
56	101.02	101.263	101.205	0.0574097	-0.242826
57	101.15	101.498	101.263	0.235576	-0.348076
58	101.06	101.81	101.322	0.48766	-0.749743
59	101.17	102.021	101.381	0.64016	-0.85141
60	101.22	102.098	101.443	0.655993	-0.878493
61	101.84	101.404	101.495	-0.0906736	0.43609
62	101.79	100.98	101.515	-0.535424	0.810424
63	101.88	101.05	101.51	-0.45909	0.829507
64	101.9	101.163	101.505	-0.342424	0.737424
65	101.91	101.336	101.51	-0.174757	0.57434
66	101.96	101.389	101.515	-0.125674	0.57109
67	101.26	NA	NA	-0.348757	NA
68	101.06	NA	NA	0.0574097	NA
69	100.98	NA	NA	0.235576	NA
70	101.12	NA	NA	0.48766	NA
71	101.24	NA	NA	0.64016	NA
72	101.25	NA	NA	0.655993	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 101.68 & NA & NA & -0.0906736 & NA \tabularnewline
2 & 101.25 & NA & NA & -0.535424 & NA \tabularnewline
3 & 101.24 & NA & NA & -0.45909 & NA \tabularnewline
4 & 101.11 & NA & NA & -0.342424 & NA \tabularnewline
5 & 101.08 & NA & NA & -0.174757 & NA \tabularnewline
6 & 101.09 & NA & NA & -0.125674 & NA \tabularnewline
7 & 101.09 & 101.152 & 101.501 & -0.348757 & -0.0620764 \tabularnewline
8 & 101.62 & 101.583 & 101.526 & 0.0574097 & 0.0367569 \tabularnewline
9 & 101.66 & 101.788 & 101.552 & 0.235576 & -0.128076 \tabularnewline
10 & 101.96 & 102.086 & 101.598 & 0.48766 & -0.125993 \tabularnewline
11 & 102.04 & 102.309 & 101.669 & 0.64016 & -0.269326 \tabularnewline
12 & 102.02 & 102.41 & 101.754 & 0.655993 & -0.389743 \tabularnewline
13 & 102.02 & 101.751 & 101.841 & -0.0906736 & 0.269424 \tabularnewline
14 & 101.51 & 101.39 & 101.925 & -0.535424 & 0.120007 \tabularnewline
15 & 101.62 & 101.559 & 102.018 & -0.45909 & 0.0607569 \tabularnewline
16 & 101.83 & 101.785 & 102.127 & -0.342424 & 0.0453403 \tabularnewline
17 & 102.06 & 102.071 & 102.246 & -0.174757 & -0.0110764 \tabularnewline
18 & 102.14 & 102.248 & 102.373 & -0.125674 & -0.10766 \tabularnewline
19 & 102.14 & 102.155 & 102.503 & -0.348757 & -0.0145764 \tabularnewline
20 & 102.59 & 102.681 & 102.623 & 0.0574097 & -0.0907431 \tabularnewline
21 & 102.92 & 102.966 & 102.73 & 0.235576 & -0.0455764 \tabularnewline
22 & 103.31 & 103.319 & 102.832 & 0.48766 & -0.00932639 \tabularnewline
23 & 103.54 & 103.569 & 102.929 & 0.64016 & -0.0293264 \tabularnewline
24 & 103.58 & 103.68 & 103.024 & 0.655993 & -0.10016 \tabularnewline
25 & 103.58 & 103.028 & 103.119 & -0.0906736 & 0.551507 \tabularnewline
26 & 102.83 & 102.681 & 103.217 & -0.535424 & 0.148757 \tabularnewline
27 & 102.86 & 102.849 & 103.308 & -0.45909 & 0.0107569 \tabularnewline
28 & 103.03 & 103.047 & 103.39 & -0.342424 & -0.0171597 \tabularnewline
29 & 103.2 & 103.291 & 103.465 & -0.174757 & -0.0906597 \tabularnewline
30 & 103.28 & 103.412 & 103.538 & -0.125674 & -0.132243 \tabularnewline
31 & 103.28 & 103.073 & 103.422 & -0.348757 & 0.20709 \tabularnewline
32 & 103.79 & 103.174 & 103.117 & 0.0574097 & 0.615507 \tabularnewline
33 & 103.92 & 103.047 & 102.812 & 0.235576 & 0.872757 \tabularnewline
34 & 104.26 & 102.993 & 102.505 & 0.48766 & 1.26734 \tabularnewline
35 & 104.41 & 102.843 & 102.202 & 0.64016 & 1.56734 \tabularnewline
36 & 104.45 & 102.559 & 101.903 & 0.655993 & 1.89109 \tabularnewline
37 & 99.92 & 101.513 & 101.604 & -0.0906736 & -1.59349 \tabularnewline
38 & 99.18 & 100.766 & 101.301 & -0.535424 & -1.58583 \tabularnewline
39 & 99.18 & 100.54 & 101 & -0.45909 & -1.36049 \tabularnewline
40 & 99.35 & 100.365 & 100.707 & -0.342424 & -1.01466 \tabularnewline
41 & 99.62 & 100.246 & 100.421 & -0.174757 & -0.626076 \tabularnewline
42 & 99.67 & 100.013 & 100.139 & -0.125674 & -0.343493 \tabularnewline
43 & 99.72 & 99.7067 & 100.055 & -0.348757 & 0.0133403 \tabularnewline
44 & 100.08 & 100.25 & 100.192 & 0.0574097 & -0.16991 \tabularnewline
45 & 100.39 & 100.592 & 100.357 & 0.235576 & -0.202243 \tabularnewline
46 & 100.77 & 101.003 & 100.516 & 0.48766 & -0.233493 \tabularnewline
47 & 101.03 & 101.298 & 100.658 & 0.64016 & -0.268493 \tabularnewline
48 & 101.07 & 101.444 & 100.788 & 0.655993 & -0.37391 \tabularnewline
49 & 101.29 & 100.805 & 100.895 & -0.0906736 & 0.485257 \tabularnewline
50 & 101.1 & 100.445 & 100.98 & -0.535424 & 0.655424 \tabularnewline
51 & 101.2 & 100.592 & 101.051 & -0.45909 & 0.608257 \tabularnewline
52 & 101.15 & 100.752 & 101.095 & -0.342424 & 0.39784 \tabularnewline
53 & 101.24 & 100.938 & 101.112 & -0.174757 & 0.302257 \tabularnewline
54 & 101.16 & 100.999 & 101.125 & -0.125674 & 0.16109 \tabularnewline
55 & 100.81 & 100.805 & 101.154 & -0.348757 & 0.00500694 \tabularnewline
56 & 101.02 & 101.263 & 101.205 & 0.0574097 & -0.242826 \tabularnewline
57 & 101.15 & 101.498 & 101.263 & 0.235576 & -0.348076 \tabularnewline
58 & 101.06 & 101.81 & 101.322 & 0.48766 & -0.749743 \tabularnewline
59 & 101.17 & 102.021 & 101.381 & 0.64016 & -0.85141 \tabularnewline
60 & 101.22 & 102.098 & 101.443 & 0.655993 & -0.878493 \tabularnewline
61 & 101.84 & 101.404 & 101.495 & -0.0906736 & 0.43609 \tabularnewline
62 & 101.79 & 100.98 & 101.515 & -0.535424 & 0.810424 \tabularnewline
63 & 101.88 & 101.05 & 101.51 & -0.45909 & 0.829507 \tabularnewline
64 & 101.9 & 101.163 & 101.505 & -0.342424 & 0.737424 \tabularnewline
65 & 101.91 & 101.336 & 101.51 & -0.174757 & 0.57434 \tabularnewline
66 & 101.96 & 101.389 & 101.515 & -0.125674 & 0.57109 \tabularnewline
67 & 101.26 & NA & NA & -0.348757 & NA \tabularnewline
68 & 101.06 & NA & NA & 0.0574097 & NA \tabularnewline
69 & 100.98 & NA & NA & 0.235576 & NA \tabularnewline
70 & 101.12 & NA & NA & 0.48766 & NA \tabularnewline
71 & 101.24 & NA & NA & 0.64016 & NA \tabularnewline
72 & 101.25 & NA & NA & 0.655993 & 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]101.68[/C][C]NA[/C][C]NA[/C][C]-0.0906736[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]101.25[/C][C]NA[/C][C]NA[/C][C]-0.535424[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]101.24[/C][C]NA[/C][C]NA[/C][C]-0.45909[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]101.11[/C][C]NA[/C][C]NA[/C][C]-0.342424[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]101.08[/C][C]NA[/C][C]NA[/C][C]-0.174757[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]101.09[/C][C]NA[/C][C]NA[/C][C]-0.125674[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]101.09[/C][C]101.152[/C][C]101.501[/C][C]-0.348757[/C][C]-0.0620764[/C][/ROW]
[ROW][C]8[/C][C]101.62[/C][C]101.583[/C][C]101.526[/C][C]0.0574097[/C][C]0.0367569[/C][/ROW]
[ROW][C]9[/C][C]101.66[/C][C]101.788[/C][C]101.552[/C][C]0.235576[/C][C]-0.128076[/C][/ROW]
[ROW][C]10[/C][C]101.96[/C][C]102.086[/C][C]101.598[/C][C]0.48766[/C][C]-0.125993[/C][/ROW]
[ROW][C]11[/C][C]102.04[/C][C]102.309[/C][C]101.669[/C][C]0.64016[/C][C]-0.269326[/C][/ROW]
[ROW][C]12[/C][C]102.02[/C][C]102.41[/C][C]101.754[/C][C]0.655993[/C][C]-0.389743[/C][/ROW]
[ROW][C]13[/C][C]102.02[/C][C]101.751[/C][C]101.841[/C][C]-0.0906736[/C][C]0.269424[/C][/ROW]
[ROW][C]14[/C][C]101.51[/C][C]101.39[/C][C]101.925[/C][C]-0.535424[/C][C]0.120007[/C][/ROW]
[ROW][C]15[/C][C]101.62[/C][C]101.559[/C][C]102.018[/C][C]-0.45909[/C][C]0.0607569[/C][/ROW]
[ROW][C]16[/C][C]101.83[/C][C]101.785[/C][C]102.127[/C][C]-0.342424[/C][C]0.0453403[/C][/ROW]
[ROW][C]17[/C][C]102.06[/C][C]102.071[/C][C]102.246[/C][C]-0.174757[/C][C]-0.0110764[/C][/ROW]
[ROW][C]18[/C][C]102.14[/C][C]102.248[/C][C]102.373[/C][C]-0.125674[/C][C]-0.10766[/C][/ROW]
[ROW][C]19[/C][C]102.14[/C][C]102.155[/C][C]102.503[/C][C]-0.348757[/C][C]-0.0145764[/C][/ROW]
[ROW][C]20[/C][C]102.59[/C][C]102.681[/C][C]102.623[/C][C]0.0574097[/C][C]-0.0907431[/C][/ROW]
[ROW][C]21[/C][C]102.92[/C][C]102.966[/C][C]102.73[/C][C]0.235576[/C][C]-0.0455764[/C][/ROW]
[ROW][C]22[/C][C]103.31[/C][C]103.319[/C][C]102.832[/C][C]0.48766[/C][C]-0.00932639[/C][/ROW]
[ROW][C]23[/C][C]103.54[/C][C]103.569[/C][C]102.929[/C][C]0.64016[/C][C]-0.0293264[/C][/ROW]
[ROW][C]24[/C][C]103.58[/C][C]103.68[/C][C]103.024[/C][C]0.655993[/C][C]-0.10016[/C][/ROW]
[ROW][C]25[/C][C]103.58[/C][C]103.028[/C][C]103.119[/C][C]-0.0906736[/C][C]0.551507[/C][/ROW]
[ROW][C]26[/C][C]102.83[/C][C]102.681[/C][C]103.217[/C][C]-0.535424[/C][C]0.148757[/C][/ROW]
[ROW][C]27[/C][C]102.86[/C][C]102.849[/C][C]103.308[/C][C]-0.45909[/C][C]0.0107569[/C][/ROW]
[ROW][C]28[/C][C]103.03[/C][C]103.047[/C][C]103.39[/C][C]-0.342424[/C][C]-0.0171597[/C][/ROW]
[ROW][C]29[/C][C]103.2[/C][C]103.291[/C][C]103.465[/C][C]-0.174757[/C][C]-0.0906597[/C][/ROW]
[ROW][C]30[/C][C]103.28[/C][C]103.412[/C][C]103.538[/C][C]-0.125674[/C][C]-0.132243[/C][/ROW]
[ROW][C]31[/C][C]103.28[/C][C]103.073[/C][C]103.422[/C][C]-0.348757[/C][C]0.20709[/C][/ROW]
[ROW][C]32[/C][C]103.79[/C][C]103.174[/C][C]103.117[/C][C]0.0574097[/C][C]0.615507[/C][/ROW]
[ROW][C]33[/C][C]103.92[/C][C]103.047[/C][C]102.812[/C][C]0.235576[/C][C]0.872757[/C][/ROW]
[ROW][C]34[/C][C]104.26[/C][C]102.993[/C][C]102.505[/C][C]0.48766[/C][C]1.26734[/C][/ROW]
[ROW][C]35[/C][C]104.41[/C][C]102.843[/C][C]102.202[/C][C]0.64016[/C][C]1.56734[/C][/ROW]
[ROW][C]36[/C][C]104.45[/C][C]102.559[/C][C]101.903[/C][C]0.655993[/C][C]1.89109[/C][/ROW]
[ROW][C]37[/C][C]99.92[/C][C]101.513[/C][C]101.604[/C][C]-0.0906736[/C][C]-1.59349[/C][/ROW]
[ROW][C]38[/C][C]99.18[/C][C]100.766[/C][C]101.301[/C][C]-0.535424[/C][C]-1.58583[/C][/ROW]
[ROW][C]39[/C][C]99.18[/C][C]100.54[/C][C]101[/C][C]-0.45909[/C][C]-1.36049[/C][/ROW]
[ROW][C]40[/C][C]99.35[/C][C]100.365[/C][C]100.707[/C][C]-0.342424[/C][C]-1.01466[/C][/ROW]
[ROW][C]41[/C][C]99.62[/C][C]100.246[/C][C]100.421[/C][C]-0.174757[/C][C]-0.626076[/C][/ROW]
[ROW][C]42[/C][C]99.67[/C][C]100.013[/C][C]100.139[/C][C]-0.125674[/C][C]-0.343493[/C][/ROW]
[ROW][C]43[/C][C]99.72[/C][C]99.7067[/C][C]100.055[/C][C]-0.348757[/C][C]0.0133403[/C][/ROW]
[ROW][C]44[/C][C]100.08[/C][C]100.25[/C][C]100.192[/C][C]0.0574097[/C][C]-0.16991[/C][/ROW]
[ROW][C]45[/C][C]100.39[/C][C]100.592[/C][C]100.357[/C][C]0.235576[/C][C]-0.202243[/C][/ROW]
[ROW][C]46[/C][C]100.77[/C][C]101.003[/C][C]100.516[/C][C]0.48766[/C][C]-0.233493[/C][/ROW]
[ROW][C]47[/C][C]101.03[/C][C]101.298[/C][C]100.658[/C][C]0.64016[/C][C]-0.268493[/C][/ROW]
[ROW][C]48[/C][C]101.07[/C][C]101.444[/C][C]100.788[/C][C]0.655993[/C][C]-0.37391[/C][/ROW]
[ROW][C]49[/C][C]101.29[/C][C]100.805[/C][C]100.895[/C][C]-0.0906736[/C][C]0.485257[/C][/ROW]
[ROW][C]50[/C][C]101.1[/C][C]100.445[/C][C]100.98[/C][C]-0.535424[/C][C]0.655424[/C][/ROW]
[ROW][C]51[/C][C]101.2[/C][C]100.592[/C][C]101.051[/C][C]-0.45909[/C][C]0.608257[/C][/ROW]
[ROW][C]52[/C][C]101.15[/C][C]100.752[/C][C]101.095[/C][C]-0.342424[/C][C]0.39784[/C][/ROW]
[ROW][C]53[/C][C]101.24[/C][C]100.938[/C][C]101.112[/C][C]-0.174757[/C][C]0.302257[/C][/ROW]
[ROW][C]54[/C][C]101.16[/C][C]100.999[/C][C]101.125[/C][C]-0.125674[/C][C]0.16109[/C][/ROW]
[ROW][C]55[/C][C]100.81[/C][C]100.805[/C][C]101.154[/C][C]-0.348757[/C][C]0.00500694[/C][/ROW]
[ROW][C]56[/C][C]101.02[/C][C]101.263[/C][C]101.205[/C][C]0.0574097[/C][C]-0.242826[/C][/ROW]
[ROW][C]57[/C][C]101.15[/C][C]101.498[/C][C]101.263[/C][C]0.235576[/C][C]-0.348076[/C][/ROW]
[ROW][C]58[/C][C]101.06[/C][C]101.81[/C][C]101.322[/C][C]0.48766[/C][C]-0.749743[/C][/ROW]
[ROW][C]59[/C][C]101.17[/C][C]102.021[/C][C]101.381[/C][C]0.64016[/C][C]-0.85141[/C][/ROW]
[ROW][C]60[/C][C]101.22[/C][C]102.098[/C][C]101.443[/C][C]0.655993[/C][C]-0.878493[/C][/ROW]
[ROW][C]61[/C][C]101.84[/C][C]101.404[/C][C]101.495[/C][C]-0.0906736[/C][C]0.43609[/C][/ROW]
[ROW][C]62[/C][C]101.79[/C][C]100.98[/C][C]101.515[/C][C]-0.535424[/C][C]0.810424[/C][/ROW]
[ROW][C]63[/C][C]101.88[/C][C]101.05[/C][C]101.51[/C][C]-0.45909[/C][C]0.829507[/C][/ROW]
[ROW][C]64[/C][C]101.9[/C][C]101.163[/C][C]101.505[/C][C]-0.342424[/C][C]0.737424[/C][/ROW]
[ROW][C]65[/C][C]101.91[/C][C]101.336[/C][C]101.51[/C][C]-0.174757[/C][C]0.57434[/C][/ROW]
[ROW][C]66[/C][C]101.96[/C][C]101.389[/C][C]101.515[/C][C]-0.125674[/C][C]0.57109[/C][/ROW]
[ROW][C]67[/C][C]101.26[/C][C]NA[/C][C]NA[/C][C]-0.348757[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.06[/C][C]NA[/C][C]NA[/C][C]0.0574097[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]100.98[/C][C]NA[/C][C]NA[/C][C]0.235576[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]101.12[/C][C]NA[/C][C]NA[/C][C]0.48766[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]101.24[/C][C]NA[/C][C]NA[/C][C]0.64016[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]101.25[/C][C]NA[/C][C]NA[/C][C]0.655993[/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	101.68	NA	NA	-0.0906736	NA
2	101.25	NA	NA	-0.535424	NA
3	101.24	NA	NA	-0.45909	NA
4	101.11	NA	NA	-0.342424	NA
5	101.08	NA	NA	-0.174757	NA
6	101.09	NA	NA	-0.125674	NA
7	101.09	101.152	101.501	-0.348757	-0.0620764
8	101.62	101.583	101.526	0.0574097	0.0367569
9	101.66	101.788	101.552	0.235576	-0.128076
10	101.96	102.086	101.598	0.48766	-0.125993
11	102.04	102.309	101.669	0.64016	-0.269326
12	102.02	102.41	101.754	0.655993	-0.389743
13	102.02	101.751	101.841	-0.0906736	0.269424
14	101.51	101.39	101.925	-0.535424	0.120007
15	101.62	101.559	102.018	-0.45909	0.0607569
16	101.83	101.785	102.127	-0.342424	0.0453403
17	102.06	102.071	102.246	-0.174757	-0.0110764
18	102.14	102.248	102.373	-0.125674	-0.10766
19	102.14	102.155	102.503	-0.348757	-0.0145764
20	102.59	102.681	102.623	0.0574097	-0.0907431
21	102.92	102.966	102.73	0.235576	-0.0455764
22	103.31	103.319	102.832	0.48766	-0.00932639
23	103.54	103.569	102.929	0.64016	-0.0293264
24	103.58	103.68	103.024	0.655993	-0.10016
25	103.58	103.028	103.119	-0.0906736	0.551507
26	102.83	102.681	103.217	-0.535424	0.148757
27	102.86	102.849	103.308	-0.45909	0.0107569
28	103.03	103.047	103.39	-0.342424	-0.0171597
29	103.2	103.291	103.465	-0.174757	-0.0906597
30	103.28	103.412	103.538	-0.125674	-0.132243
31	103.28	103.073	103.422	-0.348757	0.20709
32	103.79	103.174	103.117	0.0574097	0.615507
33	103.92	103.047	102.812	0.235576	0.872757
34	104.26	102.993	102.505	0.48766	1.26734
35	104.41	102.843	102.202	0.64016	1.56734
36	104.45	102.559	101.903	0.655993	1.89109
37	99.92	101.513	101.604	-0.0906736	-1.59349
38	99.18	100.766	101.301	-0.535424	-1.58583
39	99.18	100.54	101	-0.45909	-1.36049
40	99.35	100.365	100.707	-0.342424	-1.01466
41	99.62	100.246	100.421	-0.174757	-0.626076
42	99.67	100.013	100.139	-0.125674	-0.343493
43	99.72	99.7067	100.055	-0.348757	0.0133403
44	100.08	100.25	100.192	0.0574097	-0.16991
45	100.39	100.592	100.357	0.235576	-0.202243
46	100.77	101.003	100.516	0.48766	-0.233493
47	101.03	101.298	100.658	0.64016	-0.268493
48	101.07	101.444	100.788	0.655993	-0.37391
49	101.29	100.805	100.895	-0.0906736	0.485257
50	101.1	100.445	100.98	-0.535424	0.655424
51	101.2	100.592	101.051	-0.45909	0.608257
52	101.15	100.752	101.095	-0.342424	0.39784
53	101.24	100.938	101.112	-0.174757	0.302257
54	101.16	100.999	101.125	-0.125674	0.16109
55	100.81	100.805	101.154	-0.348757	0.00500694
56	101.02	101.263	101.205	0.0574097	-0.242826
57	101.15	101.498	101.263	0.235576	-0.348076
58	101.06	101.81	101.322	0.48766	-0.749743
59	101.17	102.021	101.381	0.64016	-0.85141
60	101.22	102.098	101.443	0.655993	-0.878493
61	101.84	101.404	101.495	-0.0906736	0.43609
62	101.79	100.98	101.515	-0.535424	0.810424
63	101.88	101.05	101.51	-0.45909	0.829507
64	101.9	101.163	101.505	-0.342424	0.737424
65	101.91	101.336	101.51	-0.174757	0.57434
66	101.96	101.389	101.515	-0.125674	0.57109
67	101.26	NA	NA	-0.348757	NA
68	101.06	NA	NA	0.0574097	NA
69	100.98	NA	NA	0.235576	NA
70	101.12	NA	NA	0.48766	NA
71	101.24	NA	NA	0.64016	NA
72	101.25	NA	NA	0.655993	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