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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 22 Apr 2016 08:09:09 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/22/t1461309157hk9j8gkpkc4hdyq.htm/, Retrieved Mon, 06 May 2024 10:23:19 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294587, Retrieved Mon, 06 May 2024 10:23:19 +0000

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Estimated Impact

159

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [Multiplicatief Kl...] [2016-04-22 07:09:09] [8955cd9eab9a69f2891c3fcdee8de955] [Current]

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Dataseries X:

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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=294587&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=294587&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294587&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	101.68	NA	NA	0.999114	NA
2	101.25	NA	NA	0.99475	NA
3	101.24	NA	NA	0.995496	NA
4	101.11	NA	NA	0.996638	NA
5	101.08	NA	NA	0.99829	NA
6	101.09	NA	NA	0.998778	NA
7	101.09	101.154	101.501	0.99658	0.99937
8	101.62	101.582	101.526	1.00056	1.00037
9	101.66	101.786	101.552	1.0023	0.998759
10	101.96	102.083	101.598	1.00478	0.99879
11	102.04	102.307	101.669	1.00628	0.997386
12	102.02	102.409	101.754	1.00644	0.996199
13	102.02	101.751	101.841	0.999114	1.00264
14	101.51	101.39	101.925	0.99475	1.00118
15	101.62	101.559	102.018	0.995496	1.0006
16	101.83	101.784	102.127	0.996638	1.00045
17	102.06	102.071	102.246	0.99829	0.999892
18	102.14	102.248	102.373	0.998778	0.998941
19	102.14	102.153	102.503	0.99658	0.999875
20	102.59	102.68	102.623	1.00056	0.99912
21	102.92	102.967	102.73	1.0023	0.999548
22	103.31	103.323	102.832	1.00478	0.999877
23	103.54	103.575	102.929	1.00628	0.999659
24	103.58	103.688	103.024	1.00644	0.99896
25	103.58	103.028	103.119	0.999114	1.00536
26	102.83	102.675	103.217	0.99475	1.00151
27	102.86	102.843	103.308	0.995496	1.00017
28	103.03	103.042	103.39	0.996638	0.999884
29	103.2	103.288	103.465	0.99829	0.999143
30	103.28	103.411	103.538	0.998778	0.998729
31	103.28	103.068	103.422	0.99658	1.00206
32	103.79	103.174	103.117	1.00056	1.00597
33	103.92	103.048	102.812	1.0023	1.00846
34	104.26	102.994	102.505	1.00478	1.01229
35	104.41	102.844	102.202	1.00628	1.01523
36	104.45	102.559	101.903	1.00644	1.01843
37	99.92	101.514	101.604	0.999114	0.984296
38	99.18	100.769	101.301	0.99475	0.984227
39	99.18	100.545	101	0.995496	0.986427
40	99.35	100.368	100.707	0.996638	0.989852
41	99.62	100.249	100.421	0.99829	0.993725
42	99.67	100.017	100.139	0.998778	0.996532
43	99.72	99.7132	100.055	0.99658	1.00007
44	100.08	100.248	100.192	1.00056	0.998322
45	100.39	100.588	100.357	1.0023	0.998034
46	100.77	100.996	100.516	1.00478	0.997764
47	101.03	101.29	100.658	1.00628	0.997431
48	101.07	101.437	100.788	1.00644	0.99638
49	101.29	100.806	100.895	0.999114	1.0048
50	101.1	100.45	100.98	0.99475	1.00647
51	101.2	100.596	101.051	0.995496	1.00601
52	101.15	100.755	101.095	0.996638	1.00392
53	101.24	100.94	101.112	0.99829	1.00298
54	101.16	101.001	101.125	0.998778	1.00157
55	100.81	100.808	101.154	0.99658	1.00002
56	101.02	101.262	101.205	1.00056	0.997613
57	101.15	101.496	101.263	1.0023	0.996594
58	101.06	101.806	101.322	1.00478	0.992673
59	101.17	102.018	101.381	1.00628	0.991691
60	101.22	102.096	101.443	1.00644	0.99142
61	101.84	101.405	101.495	0.999114	1.00429
62	101.79	100.982	101.515	0.99475	1.008
63	101.88	101.052	101.51	0.995496	1.00819
64	101.9	101.164	101.505	0.996638	1.00728
65	101.91	101.337	101.51	0.99829	1.00566
66	101.96	101.391	101.515	0.998778	1.00562
67	101.26	NA	NA	0.99658	NA
68	101.06	NA	NA	1.00056	NA
69	100.98	NA	NA	1.0023	NA
70	101.12	NA	NA	1.00478	NA
71	101.24	NA	NA	1.00628	NA
72	101.25	NA	NA	1.00644	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 101.68 & NA & NA & 0.999114 & NA \tabularnewline
2 & 101.25 & NA & NA & 0.99475 & NA \tabularnewline
3 & 101.24 & NA & NA & 0.995496 & NA \tabularnewline
4 & 101.11 & NA & NA & 0.996638 & NA \tabularnewline
5 & 101.08 & NA & NA & 0.99829 & NA \tabularnewline
6 & 101.09 & NA & NA & 0.998778 & NA \tabularnewline
7 & 101.09 & 101.154 & 101.501 & 0.99658 & 0.99937 \tabularnewline
8 & 101.62 & 101.582 & 101.526 & 1.00056 & 1.00037 \tabularnewline
9 & 101.66 & 101.786 & 101.552 & 1.0023 & 0.998759 \tabularnewline
10 & 101.96 & 102.083 & 101.598 & 1.00478 & 0.99879 \tabularnewline
11 & 102.04 & 102.307 & 101.669 & 1.00628 & 0.997386 \tabularnewline
12 & 102.02 & 102.409 & 101.754 & 1.00644 & 0.996199 \tabularnewline
13 & 102.02 & 101.751 & 101.841 & 0.999114 & 1.00264 \tabularnewline
14 & 101.51 & 101.39 & 101.925 & 0.99475 & 1.00118 \tabularnewline
15 & 101.62 & 101.559 & 102.018 & 0.995496 & 1.0006 \tabularnewline
16 & 101.83 & 101.784 & 102.127 & 0.996638 & 1.00045 \tabularnewline
17 & 102.06 & 102.071 & 102.246 & 0.99829 & 0.999892 \tabularnewline
18 & 102.14 & 102.248 & 102.373 & 0.998778 & 0.998941 \tabularnewline
19 & 102.14 & 102.153 & 102.503 & 0.99658 & 0.999875 \tabularnewline
20 & 102.59 & 102.68 & 102.623 & 1.00056 & 0.99912 \tabularnewline
21 & 102.92 & 102.967 & 102.73 & 1.0023 & 0.999548 \tabularnewline
22 & 103.31 & 103.323 & 102.832 & 1.00478 & 0.999877 \tabularnewline
23 & 103.54 & 103.575 & 102.929 & 1.00628 & 0.999659 \tabularnewline
24 & 103.58 & 103.688 & 103.024 & 1.00644 & 0.99896 \tabularnewline
25 & 103.58 & 103.028 & 103.119 & 0.999114 & 1.00536 \tabularnewline
26 & 102.83 & 102.675 & 103.217 & 0.99475 & 1.00151 \tabularnewline
27 & 102.86 & 102.843 & 103.308 & 0.995496 & 1.00017 \tabularnewline
28 & 103.03 & 103.042 & 103.39 & 0.996638 & 0.999884 \tabularnewline
29 & 103.2 & 103.288 & 103.465 & 0.99829 & 0.999143 \tabularnewline
30 & 103.28 & 103.411 & 103.538 & 0.998778 & 0.998729 \tabularnewline
31 & 103.28 & 103.068 & 103.422 & 0.99658 & 1.00206 \tabularnewline
32 & 103.79 & 103.174 & 103.117 & 1.00056 & 1.00597 \tabularnewline
33 & 103.92 & 103.048 & 102.812 & 1.0023 & 1.00846 \tabularnewline
34 & 104.26 & 102.994 & 102.505 & 1.00478 & 1.01229 \tabularnewline
35 & 104.41 & 102.844 & 102.202 & 1.00628 & 1.01523 \tabularnewline
36 & 104.45 & 102.559 & 101.903 & 1.00644 & 1.01843 \tabularnewline
37 & 99.92 & 101.514 & 101.604 & 0.999114 & 0.984296 \tabularnewline
38 & 99.18 & 100.769 & 101.301 & 0.99475 & 0.984227 \tabularnewline
39 & 99.18 & 100.545 & 101 & 0.995496 & 0.986427 \tabularnewline
40 & 99.35 & 100.368 & 100.707 & 0.996638 & 0.989852 \tabularnewline
41 & 99.62 & 100.249 & 100.421 & 0.99829 & 0.993725 \tabularnewline
42 & 99.67 & 100.017 & 100.139 & 0.998778 & 0.996532 \tabularnewline
43 & 99.72 & 99.7132 & 100.055 & 0.99658 & 1.00007 \tabularnewline
44 & 100.08 & 100.248 & 100.192 & 1.00056 & 0.998322 \tabularnewline
45 & 100.39 & 100.588 & 100.357 & 1.0023 & 0.998034 \tabularnewline
46 & 100.77 & 100.996 & 100.516 & 1.00478 & 0.997764 \tabularnewline
47 & 101.03 & 101.29 & 100.658 & 1.00628 & 0.997431 \tabularnewline
48 & 101.07 & 101.437 & 100.788 & 1.00644 & 0.99638 \tabularnewline
49 & 101.29 & 100.806 & 100.895 & 0.999114 & 1.0048 \tabularnewline
50 & 101.1 & 100.45 & 100.98 & 0.99475 & 1.00647 \tabularnewline
51 & 101.2 & 100.596 & 101.051 & 0.995496 & 1.00601 \tabularnewline
52 & 101.15 & 100.755 & 101.095 & 0.996638 & 1.00392 \tabularnewline
53 & 101.24 & 100.94 & 101.112 & 0.99829 & 1.00298 \tabularnewline
54 & 101.16 & 101.001 & 101.125 & 0.998778 & 1.00157 \tabularnewline
55 & 100.81 & 100.808 & 101.154 & 0.99658 & 1.00002 \tabularnewline
56 & 101.02 & 101.262 & 101.205 & 1.00056 & 0.997613 \tabularnewline
57 & 101.15 & 101.496 & 101.263 & 1.0023 & 0.996594 \tabularnewline
58 & 101.06 & 101.806 & 101.322 & 1.00478 & 0.992673 \tabularnewline
59 & 101.17 & 102.018 & 101.381 & 1.00628 & 0.991691 \tabularnewline
60 & 101.22 & 102.096 & 101.443 & 1.00644 & 0.99142 \tabularnewline
61 & 101.84 & 101.405 & 101.495 & 0.999114 & 1.00429 \tabularnewline
62 & 101.79 & 100.982 & 101.515 & 0.99475 & 1.008 \tabularnewline
63 & 101.88 & 101.052 & 101.51 & 0.995496 & 1.00819 \tabularnewline
64 & 101.9 & 101.164 & 101.505 & 0.996638 & 1.00728 \tabularnewline
65 & 101.91 & 101.337 & 101.51 & 0.99829 & 1.00566 \tabularnewline
66 & 101.96 & 101.391 & 101.515 & 0.998778 & 1.00562 \tabularnewline
67 & 101.26 & NA & NA & 0.99658 & NA \tabularnewline
68 & 101.06 & NA & NA & 1.00056 & NA \tabularnewline
69 & 100.98 & NA & NA & 1.0023 & NA \tabularnewline
70 & 101.12 & NA & NA & 1.00478 & NA \tabularnewline
71 & 101.24 & NA & NA & 1.00628 & NA \tabularnewline
72 & 101.25 & NA & NA & 1.00644 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294587&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]0.999114[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]101.25[/C][C]NA[/C][C]NA[/C][C]0.99475[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]101.24[/C][C]NA[/C][C]NA[/C][C]0.995496[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]101.11[/C][C]NA[/C][C]NA[/C][C]0.996638[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]101.08[/C][C]NA[/C][C]NA[/C][C]0.99829[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]101.09[/C][C]NA[/C][C]NA[/C][C]0.998778[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]101.09[/C][C]101.154[/C][C]101.501[/C][C]0.99658[/C][C]0.99937[/C][/ROW]
[ROW][C]8[/C][C]101.62[/C][C]101.582[/C][C]101.526[/C][C]1.00056[/C][C]1.00037[/C][/ROW]
[ROW][C]9[/C][C]101.66[/C][C]101.786[/C][C]101.552[/C][C]1.0023[/C][C]0.998759[/C][/ROW]
[ROW][C]10[/C][C]101.96[/C][C]102.083[/C][C]101.598[/C][C]1.00478[/C][C]0.99879[/C][/ROW]
[ROW][C]11[/C][C]102.04[/C][C]102.307[/C][C]101.669[/C][C]1.00628[/C][C]0.997386[/C][/ROW]
[ROW][C]12[/C][C]102.02[/C][C]102.409[/C][C]101.754[/C][C]1.00644[/C][C]0.996199[/C][/ROW]
[ROW][C]13[/C][C]102.02[/C][C]101.751[/C][C]101.841[/C][C]0.999114[/C][C]1.00264[/C][/ROW]
[ROW][C]14[/C][C]101.51[/C][C]101.39[/C][C]101.925[/C][C]0.99475[/C][C]1.00118[/C][/ROW]
[ROW][C]15[/C][C]101.62[/C][C]101.559[/C][C]102.018[/C][C]0.995496[/C][C]1.0006[/C][/ROW]
[ROW][C]16[/C][C]101.83[/C][C]101.784[/C][C]102.127[/C][C]0.996638[/C][C]1.00045[/C][/ROW]
[ROW][C]17[/C][C]102.06[/C][C]102.071[/C][C]102.246[/C][C]0.99829[/C][C]0.999892[/C][/ROW]
[ROW][C]18[/C][C]102.14[/C][C]102.248[/C][C]102.373[/C][C]0.998778[/C][C]0.998941[/C][/ROW]
[ROW][C]19[/C][C]102.14[/C][C]102.153[/C][C]102.503[/C][C]0.99658[/C][C]0.999875[/C][/ROW]
[ROW][C]20[/C][C]102.59[/C][C]102.68[/C][C]102.623[/C][C]1.00056[/C][C]0.99912[/C][/ROW]
[ROW][C]21[/C][C]102.92[/C][C]102.967[/C][C]102.73[/C][C]1.0023[/C][C]0.999548[/C][/ROW]
[ROW][C]22[/C][C]103.31[/C][C]103.323[/C][C]102.832[/C][C]1.00478[/C][C]0.999877[/C][/ROW]
[ROW][C]23[/C][C]103.54[/C][C]103.575[/C][C]102.929[/C][C]1.00628[/C][C]0.999659[/C][/ROW]
[ROW][C]24[/C][C]103.58[/C][C]103.688[/C][C]103.024[/C][C]1.00644[/C][C]0.99896[/C][/ROW]
[ROW][C]25[/C][C]103.58[/C][C]103.028[/C][C]103.119[/C][C]0.999114[/C][C]1.00536[/C][/ROW]
[ROW][C]26[/C][C]102.83[/C][C]102.675[/C][C]103.217[/C][C]0.99475[/C][C]1.00151[/C][/ROW]
[ROW][C]27[/C][C]102.86[/C][C]102.843[/C][C]103.308[/C][C]0.995496[/C][C]1.00017[/C][/ROW]
[ROW][C]28[/C][C]103.03[/C][C]103.042[/C][C]103.39[/C][C]0.996638[/C][C]0.999884[/C][/ROW]
[ROW][C]29[/C][C]103.2[/C][C]103.288[/C][C]103.465[/C][C]0.99829[/C][C]0.999143[/C][/ROW]
[ROW][C]30[/C][C]103.28[/C][C]103.411[/C][C]103.538[/C][C]0.998778[/C][C]0.998729[/C][/ROW]
[ROW][C]31[/C][C]103.28[/C][C]103.068[/C][C]103.422[/C][C]0.99658[/C][C]1.00206[/C][/ROW]
[ROW][C]32[/C][C]103.79[/C][C]103.174[/C][C]103.117[/C][C]1.00056[/C][C]1.00597[/C][/ROW]
[ROW][C]33[/C][C]103.92[/C][C]103.048[/C][C]102.812[/C][C]1.0023[/C][C]1.00846[/C][/ROW]
[ROW][C]34[/C][C]104.26[/C][C]102.994[/C][C]102.505[/C][C]1.00478[/C][C]1.01229[/C][/ROW]
[ROW][C]35[/C][C]104.41[/C][C]102.844[/C][C]102.202[/C][C]1.00628[/C][C]1.01523[/C][/ROW]
[ROW][C]36[/C][C]104.45[/C][C]102.559[/C][C]101.903[/C][C]1.00644[/C][C]1.01843[/C][/ROW]
[ROW][C]37[/C][C]99.92[/C][C]101.514[/C][C]101.604[/C][C]0.999114[/C][C]0.984296[/C][/ROW]
[ROW][C]38[/C][C]99.18[/C][C]100.769[/C][C]101.301[/C][C]0.99475[/C][C]0.984227[/C][/ROW]
[ROW][C]39[/C][C]99.18[/C][C]100.545[/C][C]101[/C][C]0.995496[/C][C]0.986427[/C][/ROW]
[ROW][C]40[/C][C]99.35[/C][C]100.368[/C][C]100.707[/C][C]0.996638[/C][C]0.989852[/C][/ROW]
[ROW][C]41[/C][C]99.62[/C][C]100.249[/C][C]100.421[/C][C]0.99829[/C][C]0.993725[/C][/ROW]
[ROW][C]42[/C][C]99.67[/C][C]100.017[/C][C]100.139[/C][C]0.998778[/C][C]0.996532[/C][/ROW]
[ROW][C]43[/C][C]99.72[/C][C]99.7132[/C][C]100.055[/C][C]0.99658[/C][C]1.00007[/C][/ROW]
[ROW][C]44[/C][C]100.08[/C][C]100.248[/C][C]100.192[/C][C]1.00056[/C][C]0.998322[/C][/ROW]
[ROW][C]45[/C][C]100.39[/C][C]100.588[/C][C]100.357[/C][C]1.0023[/C][C]0.998034[/C][/ROW]
[ROW][C]46[/C][C]100.77[/C][C]100.996[/C][C]100.516[/C][C]1.00478[/C][C]0.997764[/C][/ROW]
[ROW][C]47[/C][C]101.03[/C][C]101.29[/C][C]100.658[/C][C]1.00628[/C][C]0.997431[/C][/ROW]
[ROW][C]48[/C][C]101.07[/C][C]101.437[/C][C]100.788[/C][C]1.00644[/C][C]0.99638[/C][/ROW]
[ROW][C]49[/C][C]101.29[/C][C]100.806[/C][C]100.895[/C][C]0.999114[/C][C]1.0048[/C][/ROW]
[ROW][C]50[/C][C]101.1[/C][C]100.45[/C][C]100.98[/C][C]0.99475[/C][C]1.00647[/C][/ROW]
[ROW][C]51[/C][C]101.2[/C][C]100.596[/C][C]101.051[/C][C]0.995496[/C][C]1.00601[/C][/ROW]
[ROW][C]52[/C][C]101.15[/C][C]100.755[/C][C]101.095[/C][C]0.996638[/C][C]1.00392[/C][/ROW]
[ROW][C]53[/C][C]101.24[/C][C]100.94[/C][C]101.112[/C][C]0.99829[/C][C]1.00298[/C][/ROW]
[ROW][C]54[/C][C]101.16[/C][C]101.001[/C][C]101.125[/C][C]0.998778[/C][C]1.00157[/C][/ROW]
[ROW][C]55[/C][C]100.81[/C][C]100.808[/C][C]101.154[/C][C]0.99658[/C][C]1.00002[/C][/ROW]
[ROW][C]56[/C][C]101.02[/C][C]101.262[/C][C]101.205[/C][C]1.00056[/C][C]0.997613[/C][/ROW]
[ROW][C]57[/C][C]101.15[/C][C]101.496[/C][C]101.263[/C][C]1.0023[/C][C]0.996594[/C][/ROW]
[ROW][C]58[/C][C]101.06[/C][C]101.806[/C][C]101.322[/C][C]1.00478[/C][C]0.992673[/C][/ROW]
[ROW][C]59[/C][C]101.17[/C][C]102.018[/C][C]101.381[/C][C]1.00628[/C][C]0.991691[/C][/ROW]
[ROW][C]60[/C][C]101.22[/C][C]102.096[/C][C]101.443[/C][C]1.00644[/C][C]0.99142[/C][/ROW]
[ROW][C]61[/C][C]101.84[/C][C]101.405[/C][C]101.495[/C][C]0.999114[/C][C]1.00429[/C][/ROW]
[ROW][C]62[/C][C]101.79[/C][C]100.982[/C][C]101.515[/C][C]0.99475[/C][C]1.008[/C][/ROW]
[ROW][C]63[/C][C]101.88[/C][C]101.052[/C][C]101.51[/C][C]0.995496[/C][C]1.00819[/C][/ROW]
[ROW][C]64[/C][C]101.9[/C][C]101.164[/C][C]101.505[/C][C]0.996638[/C][C]1.00728[/C][/ROW]
[ROW][C]65[/C][C]101.91[/C][C]101.337[/C][C]101.51[/C][C]0.99829[/C][C]1.00566[/C][/ROW]
[ROW][C]66[/C][C]101.96[/C][C]101.391[/C][C]101.515[/C][C]0.998778[/C][C]1.00562[/C][/ROW]
[ROW][C]67[/C][C]101.26[/C][C]NA[/C][C]NA[/C][C]0.99658[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.06[/C][C]NA[/C][C]NA[/C][C]1.00056[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]100.98[/C][C]NA[/C][C]NA[/C][C]1.0023[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]101.12[/C][C]NA[/C][C]NA[/C][C]1.00478[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]101.24[/C][C]NA[/C][C]NA[/C][C]1.00628[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]101.25[/C][C]NA[/C][C]NA[/C][C]1.00644[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294587&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294587&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	0.999114	NA
2	101.25	NA	NA	0.99475	NA
3	101.24	NA	NA	0.995496	NA
4	101.11	NA	NA	0.996638	NA
5	101.08	NA	NA	0.99829	NA
6	101.09	NA	NA	0.998778	NA
7	101.09	101.154	101.501	0.99658	0.99937
8	101.62	101.582	101.526	1.00056	1.00037
9	101.66	101.786	101.552	1.0023	0.998759
10	101.96	102.083	101.598	1.00478	0.99879
11	102.04	102.307	101.669	1.00628	0.997386
12	102.02	102.409	101.754	1.00644	0.996199
13	102.02	101.751	101.841	0.999114	1.00264
14	101.51	101.39	101.925	0.99475	1.00118
15	101.62	101.559	102.018	0.995496	1.0006
16	101.83	101.784	102.127	0.996638	1.00045
17	102.06	102.071	102.246	0.99829	0.999892
18	102.14	102.248	102.373	0.998778	0.998941
19	102.14	102.153	102.503	0.99658	0.999875
20	102.59	102.68	102.623	1.00056	0.99912
21	102.92	102.967	102.73	1.0023	0.999548
22	103.31	103.323	102.832	1.00478	0.999877
23	103.54	103.575	102.929	1.00628	0.999659
24	103.58	103.688	103.024	1.00644	0.99896
25	103.58	103.028	103.119	0.999114	1.00536
26	102.83	102.675	103.217	0.99475	1.00151
27	102.86	102.843	103.308	0.995496	1.00017
28	103.03	103.042	103.39	0.996638	0.999884
29	103.2	103.288	103.465	0.99829	0.999143
30	103.28	103.411	103.538	0.998778	0.998729
31	103.28	103.068	103.422	0.99658	1.00206
32	103.79	103.174	103.117	1.00056	1.00597
33	103.92	103.048	102.812	1.0023	1.00846
34	104.26	102.994	102.505	1.00478	1.01229
35	104.41	102.844	102.202	1.00628	1.01523
36	104.45	102.559	101.903	1.00644	1.01843
37	99.92	101.514	101.604	0.999114	0.984296
38	99.18	100.769	101.301	0.99475	0.984227
39	99.18	100.545	101	0.995496	0.986427
40	99.35	100.368	100.707	0.996638	0.989852
41	99.62	100.249	100.421	0.99829	0.993725
42	99.67	100.017	100.139	0.998778	0.996532
43	99.72	99.7132	100.055	0.99658	1.00007
44	100.08	100.248	100.192	1.00056	0.998322
45	100.39	100.588	100.357	1.0023	0.998034
46	100.77	100.996	100.516	1.00478	0.997764
47	101.03	101.29	100.658	1.00628	0.997431
48	101.07	101.437	100.788	1.00644	0.99638
49	101.29	100.806	100.895	0.999114	1.0048
50	101.1	100.45	100.98	0.99475	1.00647
51	101.2	100.596	101.051	0.995496	1.00601
52	101.15	100.755	101.095	0.996638	1.00392
53	101.24	100.94	101.112	0.99829	1.00298
54	101.16	101.001	101.125	0.998778	1.00157
55	100.81	100.808	101.154	0.99658	1.00002
56	101.02	101.262	101.205	1.00056	0.997613
57	101.15	101.496	101.263	1.0023	0.996594
58	101.06	101.806	101.322	1.00478	0.992673
59	101.17	102.018	101.381	1.00628	0.991691
60	101.22	102.096	101.443	1.00644	0.99142
61	101.84	101.405	101.495	0.999114	1.00429
62	101.79	100.982	101.515	0.99475	1.008
63	101.88	101.052	101.51	0.995496	1.00819
64	101.9	101.164	101.505	0.996638	1.00728
65	101.91	101.337	101.51	0.99829	1.00566
66	101.96	101.391	101.515	0.998778	1.00562
67	101.26	NA	NA	0.99658	NA
68	101.06	NA	NA	1.00056	NA
69	100.98	NA	NA	1.0023	NA
70	101.12	NA	NA	1.00478	NA
71	101.24	NA	NA	1.00628	NA
72	101.25	NA	NA	1.00644	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- '12'
par1 <- 'multiplicative'
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