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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 25 May 2008 09:00:53 -0600

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/25/t1211727770alzvzu1n68ne26c.htm/, Retrieved Wed, 15 May 2024 01:04:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13161, Retrieved Wed, 15 May 2024 01:04:32 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

165

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

-       [Classical Decomposition] [Opgave 9-classica...] [2008-05-25 15:00:53] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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0,76
0,77
0,76
0,77
0,78
0,79
0,78
0,76
0,78
0,76
0,74
0,73
0,72
0,71
0,73
0,75
0,75
0,72
0,72
0,72
0,74
0,78
0,74
0,74
0,75
0,78
0,81
0,75
0,7
0,71
0,71
0,73
0,74
0,74
0,75
0,74
0,74
0,73
0,76
0,8
0,83
0,81
0,83
0,88
0,89
0,93
0,91
0,9
0,86
0,88
0,93
0,98
0,97
1,03
1,06
1,06
1,08
1,09
1,04
1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	13 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 13 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13161&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13161&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13161&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	13 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	0.76	NA	NA	-0.0114351851851852	NA
2	0.77	NA	NA	-0.0104629629629629	NA
3	0.76	NA	NA	0.0130092592592593	NA
4	0.77	NA	NA	0.00912037037037049	NA
5	0.78	NA	NA	-0.00226851851851855	NA
6	0.79	NA	NA	-0.0203240740740741	NA
7	0.78	0.74537037037037	0.763333333333333	-0.0179629629629630	0.0346296296296296
8	0.76	0.760231481481482	0.759166666666667	0.00106481481481486	-0.000231481481481666
9	0.78	0.764675925925926	0.755416666666667	0.00925925925925925	0.0153240740740742
10	0.76	0.783287037037037	0.753333333333333	0.0299537037037036	-0.0232870370370369
11	0.74	0.758287037037037	0.75125	0.0070370370370369	-0.0182870370370370
12	0.73	0.740092592592593	0.747083333333333	-0.00699074074074066	-0.0100925925925927
13	0.72	0.730231481481481	0.741666666666667	-0.0114351851851852	-0.0102314814814815
14	0.71	0.727037037037037	0.7375	-0.0104629629629629	-0.0170370370370371
15	0.73	0.747175925925926	0.734166666666667	0.0130092592592593	-0.017175925925926
16	0.75	0.742453703703704	0.733333333333333	0.00912037037037049	0.00754629629629633
17	0.75	0.731898148148148	0.734166666666667	-0.00226851851851855	0.0181018518518518
18	0.72	0.714259259259259	0.734583333333333	-0.0203240740740741	0.00574074074074082
19	0.72	0.718287037037037	0.73625	-0.0179629629629630	0.00171296296296297
20	0.72	0.741481481481481	0.740416666666667	0.00106481481481486	-0.0214814814814814
21	0.74	0.755925925925926	0.746666666666667	0.00925925925925925	-0.015925925925926
22	0.78	0.779953703703704	0.75	0.0299537037037036	4.62962962963775e-05
23	0.74	0.754953703703704	0.747916666666667	0.0070370370370369	-0.0149537037037037
24	0.74	0.738425925925926	0.745416666666667	-0.00699074074074066	0.00157407407407406
25	0.75	0.733148148148148	0.744583333333333	-0.0114351851851852	0.0168518518518518
26	0.78	0.73412037037037	0.744583333333333	-0.0104629629629629	0.0458796296296297
27	0.81	0.75800925925926	0.745	0.0130092592592593	0.0519907407407407
28	0.75	0.752453703703704	0.743333333333333	0.00912037037037049	-0.00245370370370368
29	0.7	0.739814814814815	0.742083333333333	-0.00226851851851855	-0.0398148148148147
30	0.71	0.722175925925926	0.7425	-0.0203240740740741	-0.0121759259259260
31	0.71	0.72412037037037	0.742083333333333	-0.0179629629629630	-0.0141203703703703
32	0.73	0.740648148148148	0.739583333333333	0.00106481481481486	-0.0106481481481482
33	0.74	0.744675925925926	0.735416666666667	0.00925925925925925	-0.00467592592592592
34	0.74	0.76537037037037	0.735416666666667	0.0299537037037036	-0.0253703703703703
35	0.75	0.749953703703704	0.742916666666667	0.0070370370370369	4.62962962963775e-05
36	0.74	0.745509259259259	0.7525	-0.00699074074074066	-0.00550925925925916
37	0.74	0.750231481481481	0.761666666666666	-0.0114351851851852	-0.0102314814814813
38	0.73	0.762453703703704	0.772916666666667	-0.0104629629629629	-0.0324537037037037
39	0.76	0.798425925925926	0.785416666666667	0.0130092592592593	-0.0384259259259259
40	0.8	0.808703703703704	0.799583333333333	0.00912037037037049	-0.00870370370370366
41	0.83	0.811898148148148	0.814166666666667	-0.00226851851851855	0.0181018518518519
42	0.81	0.807175925925926	0.8275	-0.0203240740740741	0.00282407407407415
43	0.83	0.821203703703704	0.839166666666667	-0.0179629629629630	0.0087962962962963
44	0.88	0.851481481481482	0.850416666666667	0.00106481481481486	0.0285185185185185
45	0.89	0.87300925925926	0.86375	0.00925925925925925	0.0169907407407408
46	0.93	0.908287037037037	0.878333333333334	0.0299537037037036	0.0217129629629629
47	0.91	0.898703703703704	0.891666666666667	0.0070370370370369	0.0112962962962962
48	0.9	0.899675925925926	0.906666666666667	-0.00699074074074066	0.000324074074074199
49	0.86	0.913981481481481	0.925416666666667	-0.0114351851851852	-0.0539814814814814
50	0.88	0.932037037037037	0.9425	-0.0104629629629629	-0.052037037037037
51	0.93	0.970925925925926	0.957916666666667	0.0130092592592593	-0.0409259259259259
52	0.98	0.98162037037037	0.9725	0.00912037037037049	-0.00162037037037033
53	0.97	0.982314814814815	0.984583333333333	-0.00226851851851855	-0.0123148148148149
54	1.03	0.973842592592593	0.994166666666667	-0.0203240740740741	0.0561574074074076
55	1.06	NA	NA	-0.0179629629629630	NA
56	1.06	NA	NA	0.00106481481481486	NA
57	1.08	NA	NA	0.00925925925925925	NA
58	1.09	NA	NA	0.0299537037037036	NA
59	1.04	NA	NA	0.0070370370370369	NA
60	1	NA	NA	-0.00699074074074066	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 0.76 & NA & NA & -0.0114351851851852 & NA \tabularnewline
2 & 0.77 & NA & NA & -0.0104629629629629 & NA \tabularnewline
3 & 0.76 & NA & NA & 0.0130092592592593 & NA \tabularnewline
4 & 0.77 & NA & NA & 0.00912037037037049 & NA \tabularnewline
5 & 0.78 & NA & NA & -0.00226851851851855 & NA \tabularnewline
6 & 0.79 & NA & NA & -0.0203240740740741 & NA \tabularnewline
7 & 0.78 & 0.74537037037037 & 0.763333333333333 & -0.0179629629629630 & 0.0346296296296296 \tabularnewline
8 & 0.76 & 0.760231481481482 & 0.759166666666667 & 0.00106481481481486 & -0.000231481481481666 \tabularnewline
9 & 0.78 & 0.764675925925926 & 0.755416666666667 & 0.00925925925925925 & 0.0153240740740742 \tabularnewline
10 & 0.76 & 0.783287037037037 & 0.753333333333333 & 0.0299537037037036 & -0.0232870370370369 \tabularnewline
11 & 0.74 & 0.758287037037037 & 0.75125 & 0.0070370370370369 & -0.0182870370370370 \tabularnewline
12 & 0.73 & 0.740092592592593 & 0.747083333333333 & -0.00699074074074066 & -0.0100925925925927 \tabularnewline
13 & 0.72 & 0.730231481481481 & 0.741666666666667 & -0.0114351851851852 & -0.0102314814814815 \tabularnewline
14 & 0.71 & 0.727037037037037 & 0.7375 & -0.0104629629629629 & -0.0170370370370371 \tabularnewline
15 & 0.73 & 0.747175925925926 & 0.734166666666667 & 0.0130092592592593 & -0.017175925925926 \tabularnewline
16 & 0.75 & 0.742453703703704 & 0.733333333333333 & 0.00912037037037049 & 0.00754629629629633 \tabularnewline
17 & 0.75 & 0.731898148148148 & 0.734166666666667 & -0.00226851851851855 & 0.0181018518518518 \tabularnewline
18 & 0.72 & 0.714259259259259 & 0.734583333333333 & -0.0203240740740741 & 0.00574074074074082 \tabularnewline
19 & 0.72 & 0.718287037037037 & 0.73625 & -0.0179629629629630 & 0.00171296296296297 \tabularnewline
20 & 0.72 & 0.741481481481481 & 0.740416666666667 & 0.00106481481481486 & -0.0214814814814814 \tabularnewline
21 & 0.74 & 0.755925925925926 & 0.746666666666667 & 0.00925925925925925 & -0.015925925925926 \tabularnewline
22 & 0.78 & 0.779953703703704 & 0.75 & 0.0299537037037036 & 4.62962962963775e-05 \tabularnewline
23 & 0.74 & 0.754953703703704 & 0.747916666666667 & 0.0070370370370369 & -0.0149537037037037 \tabularnewline
24 & 0.74 & 0.738425925925926 & 0.745416666666667 & -0.00699074074074066 & 0.00157407407407406 \tabularnewline
25 & 0.75 & 0.733148148148148 & 0.744583333333333 & -0.0114351851851852 & 0.0168518518518518 \tabularnewline
26 & 0.78 & 0.73412037037037 & 0.744583333333333 & -0.0104629629629629 & 0.0458796296296297 \tabularnewline
27 & 0.81 & 0.75800925925926 & 0.745 & 0.0130092592592593 & 0.0519907407407407 \tabularnewline
28 & 0.75 & 0.752453703703704 & 0.743333333333333 & 0.00912037037037049 & -0.00245370370370368 \tabularnewline
29 & 0.7 & 0.739814814814815 & 0.742083333333333 & -0.00226851851851855 & -0.0398148148148147 \tabularnewline
30 & 0.71 & 0.722175925925926 & 0.7425 & -0.0203240740740741 & -0.0121759259259260 \tabularnewline
31 & 0.71 & 0.72412037037037 & 0.742083333333333 & -0.0179629629629630 & -0.0141203703703703 \tabularnewline
32 & 0.73 & 0.740648148148148 & 0.739583333333333 & 0.00106481481481486 & -0.0106481481481482 \tabularnewline
33 & 0.74 & 0.744675925925926 & 0.735416666666667 & 0.00925925925925925 & -0.00467592592592592 \tabularnewline
34 & 0.74 & 0.76537037037037 & 0.735416666666667 & 0.0299537037037036 & -0.0253703703703703 \tabularnewline
35 & 0.75 & 0.749953703703704 & 0.742916666666667 & 0.0070370370370369 & 4.62962962963775e-05 \tabularnewline
36 & 0.74 & 0.745509259259259 & 0.7525 & -0.00699074074074066 & -0.00550925925925916 \tabularnewline
37 & 0.74 & 0.750231481481481 & 0.761666666666666 & -0.0114351851851852 & -0.0102314814814813 \tabularnewline
38 & 0.73 & 0.762453703703704 & 0.772916666666667 & -0.0104629629629629 & -0.0324537037037037 \tabularnewline
39 & 0.76 & 0.798425925925926 & 0.785416666666667 & 0.0130092592592593 & -0.0384259259259259 \tabularnewline
40 & 0.8 & 0.808703703703704 & 0.799583333333333 & 0.00912037037037049 & -0.00870370370370366 \tabularnewline
41 & 0.83 & 0.811898148148148 & 0.814166666666667 & -0.00226851851851855 & 0.0181018518518519 \tabularnewline
42 & 0.81 & 0.807175925925926 & 0.8275 & -0.0203240740740741 & 0.00282407407407415 \tabularnewline
43 & 0.83 & 0.821203703703704 & 0.839166666666667 & -0.0179629629629630 & 0.0087962962962963 \tabularnewline
44 & 0.88 & 0.851481481481482 & 0.850416666666667 & 0.00106481481481486 & 0.0285185185185185 \tabularnewline
45 & 0.89 & 0.87300925925926 & 0.86375 & 0.00925925925925925 & 0.0169907407407408 \tabularnewline
46 & 0.93 & 0.908287037037037 & 0.878333333333334 & 0.0299537037037036 & 0.0217129629629629 \tabularnewline
47 & 0.91 & 0.898703703703704 & 0.891666666666667 & 0.0070370370370369 & 0.0112962962962962 \tabularnewline
48 & 0.9 & 0.899675925925926 & 0.906666666666667 & -0.00699074074074066 & 0.000324074074074199 \tabularnewline
49 & 0.86 & 0.913981481481481 & 0.925416666666667 & -0.0114351851851852 & -0.0539814814814814 \tabularnewline
50 & 0.88 & 0.932037037037037 & 0.9425 & -0.0104629629629629 & -0.052037037037037 \tabularnewline
51 & 0.93 & 0.970925925925926 & 0.957916666666667 & 0.0130092592592593 & -0.0409259259259259 \tabularnewline
52 & 0.98 & 0.98162037037037 & 0.9725 & 0.00912037037037049 & -0.00162037037037033 \tabularnewline
53 & 0.97 & 0.982314814814815 & 0.984583333333333 & -0.00226851851851855 & -0.0123148148148149 \tabularnewline
54 & 1.03 & 0.973842592592593 & 0.994166666666667 & -0.0203240740740741 & 0.0561574074074076 \tabularnewline
55 & 1.06 & NA & NA & -0.0179629629629630 & NA \tabularnewline
56 & 1.06 & NA & NA & 0.00106481481481486 & NA \tabularnewline
57 & 1.08 & NA & NA & 0.00925925925925925 & NA \tabularnewline
58 & 1.09 & NA & NA & 0.0299537037037036 & NA \tabularnewline
59 & 1.04 & NA & NA & 0.0070370370370369 & NA \tabularnewline
60 & 1 & NA & NA & -0.00699074074074066 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13161&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]0.76[/C][C]NA[/C][C]NA[/C][C]-0.0114351851851852[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]0.77[/C][C]NA[/C][C]NA[/C][C]-0.0104629629629629[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]0.76[/C][C]NA[/C][C]NA[/C][C]0.0130092592592593[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]0.77[/C][C]NA[/C][C]NA[/C][C]0.00912037037037049[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]0.78[/C][C]NA[/C][C]NA[/C][C]-0.00226851851851855[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]0.79[/C][C]NA[/C][C]NA[/C][C]-0.0203240740740741[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]0.78[/C][C]0.74537037037037[/C][C]0.763333333333333[/C][C]-0.0179629629629630[/C][C]0.0346296296296296[/C][/ROW]
[ROW][C]8[/C][C]0.76[/C][C]0.760231481481482[/C][C]0.759166666666667[/C][C]0.00106481481481486[/C][C]-0.000231481481481666[/C][/ROW]
[ROW][C]9[/C][C]0.78[/C][C]0.764675925925926[/C][C]0.755416666666667[/C][C]0.00925925925925925[/C][C]0.0153240740740742[/C][/ROW]
[ROW][C]10[/C][C]0.76[/C][C]0.783287037037037[/C][C]0.753333333333333[/C][C]0.0299537037037036[/C][C]-0.0232870370370369[/C][/ROW]
[ROW][C]11[/C][C]0.74[/C][C]0.758287037037037[/C][C]0.75125[/C][C]0.0070370370370369[/C][C]-0.0182870370370370[/C][/ROW]
[ROW][C]12[/C][C]0.73[/C][C]0.740092592592593[/C][C]0.747083333333333[/C][C]-0.00699074074074066[/C][C]-0.0100925925925927[/C][/ROW]
[ROW][C]13[/C][C]0.72[/C][C]0.730231481481481[/C][C]0.741666666666667[/C][C]-0.0114351851851852[/C][C]-0.0102314814814815[/C][/ROW]
[ROW][C]14[/C][C]0.71[/C][C]0.727037037037037[/C][C]0.7375[/C][C]-0.0104629629629629[/C][C]-0.0170370370370371[/C][/ROW]
[ROW][C]15[/C][C]0.73[/C][C]0.747175925925926[/C][C]0.734166666666667[/C][C]0.0130092592592593[/C][C]-0.017175925925926[/C][/ROW]
[ROW][C]16[/C][C]0.75[/C][C]0.742453703703704[/C][C]0.733333333333333[/C][C]0.00912037037037049[/C][C]0.00754629629629633[/C][/ROW]
[ROW][C]17[/C][C]0.75[/C][C]0.731898148148148[/C][C]0.734166666666667[/C][C]-0.00226851851851855[/C][C]0.0181018518518518[/C][/ROW]
[ROW][C]18[/C][C]0.72[/C][C]0.714259259259259[/C][C]0.734583333333333[/C][C]-0.0203240740740741[/C][C]0.00574074074074082[/C][/ROW]
[ROW][C]19[/C][C]0.72[/C][C]0.718287037037037[/C][C]0.73625[/C][C]-0.0179629629629630[/C][C]0.00171296296296297[/C][/ROW]
[ROW][C]20[/C][C]0.72[/C][C]0.741481481481481[/C][C]0.740416666666667[/C][C]0.00106481481481486[/C][C]-0.0214814814814814[/C][/ROW]
[ROW][C]21[/C][C]0.74[/C][C]0.755925925925926[/C][C]0.746666666666667[/C][C]0.00925925925925925[/C][C]-0.015925925925926[/C][/ROW]
[ROW][C]22[/C][C]0.78[/C][C]0.779953703703704[/C][C]0.75[/C][C]0.0299537037037036[/C][C]4.62962962963775e-05[/C][/ROW]
[ROW][C]23[/C][C]0.74[/C][C]0.754953703703704[/C][C]0.747916666666667[/C][C]0.0070370370370369[/C][C]-0.0149537037037037[/C][/ROW]
[ROW][C]24[/C][C]0.74[/C][C]0.738425925925926[/C][C]0.745416666666667[/C][C]-0.00699074074074066[/C][C]0.00157407407407406[/C][/ROW]
[ROW][C]25[/C][C]0.75[/C][C]0.733148148148148[/C][C]0.744583333333333[/C][C]-0.0114351851851852[/C][C]0.0168518518518518[/C][/ROW]
[ROW][C]26[/C][C]0.78[/C][C]0.73412037037037[/C][C]0.744583333333333[/C][C]-0.0104629629629629[/C][C]0.0458796296296297[/C][/ROW]
[ROW][C]27[/C][C]0.81[/C][C]0.75800925925926[/C][C]0.745[/C][C]0.0130092592592593[/C][C]0.0519907407407407[/C][/ROW]
[ROW][C]28[/C][C]0.75[/C][C]0.752453703703704[/C][C]0.743333333333333[/C][C]0.00912037037037049[/C][C]-0.00245370370370368[/C][/ROW]
[ROW][C]29[/C][C]0.7[/C][C]0.739814814814815[/C][C]0.742083333333333[/C][C]-0.00226851851851855[/C][C]-0.0398148148148147[/C][/ROW]
[ROW][C]30[/C][C]0.71[/C][C]0.722175925925926[/C][C]0.7425[/C][C]-0.0203240740740741[/C][C]-0.0121759259259260[/C][/ROW]
[ROW][C]31[/C][C]0.71[/C][C]0.72412037037037[/C][C]0.742083333333333[/C][C]-0.0179629629629630[/C][C]-0.0141203703703703[/C][/ROW]
[ROW][C]32[/C][C]0.73[/C][C]0.740648148148148[/C][C]0.739583333333333[/C][C]0.00106481481481486[/C][C]-0.0106481481481482[/C][/ROW]
[ROW][C]33[/C][C]0.74[/C][C]0.744675925925926[/C][C]0.735416666666667[/C][C]0.00925925925925925[/C][C]-0.00467592592592592[/C][/ROW]
[ROW][C]34[/C][C]0.74[/C][C]0.76537037037037[/C][C]0.735416666666667[/C][C]0.0299537037037036[/C][C]-0.0253703703703703[/C][/ROW]
[ROW][C]35[/C][C]0.75[/C][C]0.749953703703704[/C][C]0.742916666666667[/C][C]0.0070370370370369[/C][C]4.62962962963775e-05[/C][/ROW]
[ROW][C]36[/C][C]0.74[/C][C]0.745509259259259[/C][C]0.7525[/C][C]-0.00699074074074066[/C][C]-0.00550925925925916[/C][/ROW]
[ROW][C]37[/C][C]0.74[/C][C]0.750231481481481[/C][C]0.761666666666666[/C][C]-0.0114351851851852[/C][C]-0.0102314814814813[/C][/ROW]
[ROW][C]38[/C][C]0.73[/C][C]0.762453703703704[/C][C]0.772916666666667[/C][C]-0.0104629629629629[/C][C]-0.0324537037037037[/C][/ROW]
[ROW][C]39[/C][C]0.76[/C][C]0.798425925925926[/C][C]0.785416666666667[/C][C]0.0130092592592593[/C][C]-0.0384259259259259[/C][/ROW]
[ROW][C]40[/C][C]0.8[/C][C]0.808703703703704[/C][C]0.799583333333333[/C][C]0.00912037037037049[/C][C]-0.00870370370370366[/C][/ROW]
[ROW][C]41[/C][C]0.83[/C][C]0.811898148148148[/C][C]0.814166666666667[/C][C]-0.00226851851851855[/C][C]0.0181018518518519[/C][/ROW]
[ROW][C]42[/C][C]0.81[/C][C]0.807175925925926[/C][C]0.8275[/C][C]-0.0203240740740741[/C][C]0.00282407407407415[/C][/ROW]
[ROW][C]43[/C][C]0.83[/C][C]0.821203703703704[/C][C]0.839166666666667[/C][C]-0.0179629629629630[/C][C]0.0087962962962963[/C][/ROW]
[ROW][C]44[/C][C]0.88[/C][C]0.851481481481482[/C][C]0.850416666666667[/C][C]0.00106481481481486[/C][C]0.0285185185185185[/C][/ROW]
[ROW][C]45[/C][C]0.89[/C][C]0.87300925925926[/C][C]0.86375[/C][C]0.00925925925925925[/C][C]0.0169907407407408[/C][/ROW]
[ROW][C]46[/C][C]0.93[/C][C]0.908287037037037[/C][C]0.878333333333334[/C][C]0.0299537037037036[/C][C]0.0217129629629629[/C][/ROW]
[ROW][C]47[/C][C]0.91[/C][C]0.898703703703704[/C][C]0.891666666666667[/C][C]0.0070370370370369[/C][C]0.0112962962962962[/C][/ROW]
[ROW][C]48[/C][C]0.9[/C][C]0.899675925925926[/C][C]0.906666666666667[/C][C]-0.00699074074074066[/C][C]0.000324074074074199[/C][/ROW]
[ROW][C]49[/C][C]0.86[/C][C]0.913981481481481[/C][C]0.925416666666667[/C][C]-0.0114351851851852[/C][C]-0.0539814814814814[/C][/ROW]
[ROW][C]50[/C][C]0.88[/C][C]0.932037037037037[/C][C]0.9425[/C][C]-0.0104629629629629[/C][C]-0.052037037037037[/C][/ROW]
[ROW][C]51[/C][C]0.93[/C][C]0.970925925925926[/C][C]0.957916666666667[/C][C]0.0130092592592593[/C][C]-0.0409259259259259[/C][/ROW]
[ROW][C]52[/C][C]0.98[/C][C]0.98162037037037[/C][C]0.9725[/C][C]0.00912037037037049[/C][C]-0.00162037037037033[/C][/ROW]
[ROW][C]53[/C][C]0.97[/C][C]0.982314814814815[/C][C]0.984583333333333[/C][C]-0.00226851851851855[/C][C]-0.0123148148148149[/C][/ROW]
[ROW][C]54[/C][C]1.03[/C][C]0.973842592592593[/C][C]0.994166666666667[/C][C]-0.0203240740740741[/C][C]0.0561574074074076[/C][/ROW]
[ROW][C]55[/C][C]1.06[/C][C]NA[/C][C]NA[/C][C]-0.0179629629629630[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]1.06[/C][C]NA[/C][C]NA[/C][C]0.00106481481481486[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]1.08[/C][C]NA[/C][C]NA[/C][C]0.00925925925925925[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]1.09[/C][C]NA[/C][C]NA[/C][C]0.0299537037037036[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]1.04[/C][C]NA[/C][C]NA[/C][C]0.0070370370370369[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]NA[/C][C]NA[/C][C]-0.00699074074074066[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13161&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13161&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	0.76	NA	NA	-0.0114351851851852	NA
2	0.77	NA	NA	-0.0104629629629629	NA
3	0.76	NA	NA	0.0130092592592593	NA
4	0.77	NA	NA	0.00912037037037049	NA
5	0.78	NA	NA	-0.00226851851851855	NA
6	0.79	NA	NA	-0.0203240740740741	NA
7	0.78	0.74537037037037	0.763333333333333	-0.0179629629629630	0.0346296296296296
8	0.76	0.760231481481482	0.759166666666667	0.00106481481481486	-0.000231481481481666
9	0.78	0.764675925925926	0.755416666666667	0.00925925925925925	0.0153240740740742
10	0.76	0.783287037037037	0.753333333333333	0.0299537037037036	-0.0232870370370369
11	0.74	0.758287037037037	0.75125	0.0070370370370369	-0.0182870370370370
12	0.73	0.740092592592593	0.747083333333333	-0.00699074074074066	-0.0100925925925927
13	0.72	0.730231481481481	0.741666666666667	-0.0114351851851852	-0.0102314814814815
14	0.71	0.727037037037037	0.7375	-0.0104629629629629	-0.0170370370370371
15	0.73	0.747175925925926	0.734166666666667	0.0130092592592593	-0.017175925925926
16	0.75	0.742453703703704	0.733333333333333	0.00912037037037049	0.00754629629629633
17	0.75	0.731898148148148	0.734166666666667	-0.00226851851851855	0.0181018518518518
18	0.72	0.714259259259259	0.734583333333333	-0.0203240740740741	0.00574074074074082
19	0.72	0.718287037037037	0.73625	-0.0179629629629630	0.00171296296296297
20	0.72	0.741481481481481	0.740416666666667	0.00106481481481486	-0.0214814814814814
21	0.74	0.755925925925926	0.746666666666667	0.00925925925925925	-0.015925925925926
22	0.78	0.779953703703704	0.75	0.0299537037037036	4.62962962963775e-05
23	0.74	0.754953703703704	0.747916666666667	0.0070370370370369	-0.0149537037037037
24	0.74	0.738425925925926	0.745416666666667	-0.00699074074074066	0.00157407407407406
25	0.75	0.733148148148148	0.744583333333333	-0.0114351851851852	0.0168518518518518
26	0.78	0.73412037037037	0.744583333333333	-0.0104629629629629	0.0458796296296297
27	0.81	0.75800925925926	0.745	0.0130092592592593	0.0519907407407407
28	0.75	0.752453703703704	0.743333333333333	0.00912037037037049	-0.00245370370370368
29	0.7	0.739814814814815	0.742083333333333	-0.00226851851851855	-0.0398148148148147
30	0.71	0.722175925925926	0.7425	-0.0203240740740741	-0.0121759259259260
31	0.71	0.72412037037037	0.742083333333333	-0.0179629629629630	-0.0141203703703703
32	0.73	0.740648148148148	0.739583333333333	0.00106481481481486	-0.0106481481481482
33	0.74	0.744675925925926	0.735416666666667	0.00925925925925925	-0.00467592592592592
34	0.74	0.76537037037037	0.735416666666667	0.0299537037037036	-0.0253703703703703
35	0.75	0.749953703703704	0.742916666666667	0.0070370370370369	4.62962962963775e-05
36	0.74	0.745509259259259	0.7525	-0.00699074074074066	-0.00550925925925916
37	0.74	0.750231481481481	0.761666666666666	-0.0114351851851852	-0.0102314814814813
38	0.73	0.762453703703704	0.772916666666667	-0.0104629629629629	-0.0324537037037037
39	0.76	0.798425925925926	0.785416666666667	0.0130092592592593	-0.0384259259259259
40	0.8	0.808703703703704	0.799583333333333	0.00912037037037049	-0.00870370370370366
41	0.83	0.811898148148148	0.814166666666667	-0.00226851851851855	0.0181018518518519
42	0.81	0.807175925925926	0.8275	-0.0203240740740741	0.00282407407407415
43	0.83	0.821203703703704	0.839166666666667	-0.0179629629629630	0.0087962962962963
44	0.88	0.851481481481482	0.850416666666667	0.00106481481481486	0.0285185185185185
45	0.89	0.87300925925926	0.86375	0.00925925925925925	0.0169907407407408
46	0.93	0.908287037037037	0.878333333333334	0.0299537037037036	0.0217129629629629
47	0.91	0.898703703703704	0.891666666666667	0.0070370370370369	0.0112962962962962
48	0.9	0.899675925925926	0.906666666666667	-0.00699074074074066	0.000324074074074199
49	0.86	0.913981481481481	0.925416666666667	-0.0114351851851852	-0.0539814814814814
50	0.88	0.932037037037037	0.9425	-0.0104629629629629	-0.052037037037037
51	0.93	0.970925925925926	0.957916666666667	0.0130092592592593	-0.0409259259259259
52	0.98	0.98162037037037	0.9725	0.00912037037037049	-0.00162037037037033
53	0.97	0.982314814814815	0.984583333333333	-0.00226851851851855	-0.0123148148148149
54	1.03	0.973842592592593	0.994166666666667	-0.0203240740740741	0.0561574074074076
55	1.06	NA	NA	-0.0179629629629630	NA
56	1.06	NA	NA	0.00106481481481486	NA
57	1.08	NA	NA	0.00925925925925925	NA
58	1.09	NA	NA	0.0299537037037036	NA
59	1.04	NA	NA	0.0070370370370369	NA
60	1	NA	NA	-0.00699074074074066	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
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