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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 01 Apr 2015 17:47:59 +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/2015/Apr/01/t1427906902r4v8drprf27i35x.htm/, Retrieved Thu, 09 May 2024 19:56:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278525, Retrieved Thu, 09 May 2024 19:56:10 +0000

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Estimated Impact

127

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-       [Classical Decomposition] [] [2015-04-01 16:47:59] [478e7c199ef13b68c565592d49c085e5] [Current]

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Dataseries X:

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4,8
4,81
5,16
5,26
5,29
5,29
5,29
5,3
5,3
5,3
5,3
5,3
5,3
5,3
5,3
5,35
5,44
5,47
5,47
5,48
5,48
5,48
5,48
5,48
5,48
5,48
5,5
5,55
5,57
5,58
5,58
5,58
5,59
5,59
5,59
5,55
5,61
5,61
5,61
5,63
5,69
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,71
5,74
5,77
5,79
5,79
5,8
5,8
5,8
5,8
5,8
5,81
5,81
5,83
5,94
5,98
5,99
6
6,02
6,02
6,02
6,02
6,02
6,02
6,02
6,04
6,06
6,06
6,07
6,14
6,19
6,2
6,22
6,22

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=278525&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=278525&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278525&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	4.8	NA	NA	-0.0210764	NA
2	4.81	NA	NA	-0.0306597	NA
3	5.16	NA	NA	-0.0393403	NA
4	5.26	NA	NA	-0.0234375	NA
5	5.29	NA	NA	0.0189236	NA
6	5.29	NA	NA	0.0261458	NA
7	5.29	5.25962	5.22083	0.0387847	0.0303819
8	5.3	5.28899	5.26208	0.0269097	0.0110069
9	5.3	5.30753	5.28833	0.0192014	-0.00753472
10	5.3	5.30573	5.29792	0.0078125	-0.00572917
11	5.3	5.30497	5.30792	-0.00295139	-0.00496528
12	5.3	5.30135	5.32167	-0.0203125	-0.00135417
13	5.3	5.31559	5.33667	-0.0210764	-0.0155903
14	5.3	5.32101	5.35167	-0.0306597	-0.0210069
15	5.3	5.32733	5.36667	-0.0393403	-0.0273264
16	5.35	5.35823	5.38167	-0.0234375	-0.00822917
17	5.44	5.41559	5.39667	0.0189236	0.0244097
18	5.47	5.43781	5.41167	0.0261458	0.0321875
19	5.47	5.46545	5.42667	0.0387847	0.00454861
20	5.48	5.46858	5.44167	0.0269097	0.0114236
21	5.48	5.4767	5.4575	0.0192014	0.00329861
22	5.48	5.48198	5.47417	0.0078125	-0.00197917
23	5.48	5.48497	5.48792	-0.00295139	-0.00496528
24	5.48	5.4776	5.49792	-0.0203125	0.00239583
25	5.48	5.48601	5.50708	-0.0210764	-0.00600694
26	5.48	5.48517	5.51583	-0.0306597	-0.00517361
27	5.5	5.48524	5.52458	-0.0393403	0.0147569
28	5.55	5.51031	5.53375	-0.0234375	0.0396875
29	5.57	5.56184	5.54292	0.0189236	0.00815972
30	5.58	5.57656	5.55042	0.0261458	0.0034375
31	5.58	5.59753	5.55875	0.0387847	-0.0175347
32	5.58	5.59649	5.56958	0.0269097	-0.0164931
33	5.59	5.59878	5.57958	0.0192014	-0.00878472
34	5.59	5.59531	5.5875	0.0078125	-0.0053125
35	5.59	5.59288	5.59583	-0.00295139	-0.00288194
36	5.55	5.58552	5.60583	-0.0203125	-0.0355208
37	5.61	5.59476	5.61583	-0.0210764	0.0152431
38	5.61	5.59517	5.62583	-0.0306597	0.0148264
39	5.61	5.59608	5.63542	-0.0393403	0.0139236
40	5.63	5.62115	5.64458	-0.0234375	0.00885417
41	5.69	5.67267	5.65375	0.0189236	0.0173264
42	5.7	5.69073	5.66458	0.0261458	0.00927083
43	5.7	5.71337	5.67458	0.0387847	-0.0133681
44	5.7	5.70899	5.68208	0.0269097	-0.00899306
45	5.7	5.70878	5.68958	0.0192014	-0.00878472
46	5.7	5.70448	5.69667	0.0078125	-0.00447917
47	5.7	5.69913	5.70208	-0.00295139	0.000868056
48	5.7	5.68677	5.70708	-0.0203125	0.0132292
49	5.7	5.69267	5.71375	-0.0210764	0.00732639
50	5.7	5.69059	5.72125	-0.0306597	0.00940972
51	5.7	5.68983	5.72917	-0.0393403	0.0101736
52	5.71	5.71406	5.7375	-0.0234375	-0.0040625
53	5.74	5.76476	5.74583	0.0189236	-0.0247569
54	5.77	5.78031	5.75417	0.0261458	-0.0103125
55	5.79	5.80128	5.7625	0.0387847	-0.0112847
56	5.79	5.79816	5.77125	0.0269097	-0.00815972
57	5.8	5.79962	5.78042	0.0192014	0.000381944
58	5.8	5.79781	5.79	0.0078125	0.0021875
59	5.8	5.80038	5.80333	-0.00295139	-0.000381944
60	5.8	5.8001	5.82042	-0.0203125	-0.000104167
61	5.8	5.81642	5.8375	-0.0210764	-0.0164236
62	5.81	5.82392	5.85458	-0.0306597	-0.0139236
63	5.81	5.83316	5.8725	-0.0393403	-0.0231597
64	5.83	5.8674	5.89083	-0.0234375	-0.0373958
65	5.94	5.92809	5.90917	0.0189236	0.0119097
66	5.98	5.95365	5.9275	0.0261458	0.0263542
67	5.99	5.98462	5.94583	0.0387847	0.00538194
68	6	5.99066	5.96375	0.0269097	0.00934028
69	6.02	6.00045	5.98125	0.0192014	0.0195486
70	6.02	6.00656	5.99875	0.0078125	0.0134375
71	6.02	6.00955	6.0125	-0.00295139	0.0104514
72	6.02	6.00052	6.02083	-0.0203125	0.0194792
73	6.02	6.00642	6.0275	-0.0210764	0.0135764
74	6.02	6.00601	6.03667	-0.0306597	0.0139931
75	6.02	6.01024	6.04958	-0.0393403	0.00975694
76	6.04	6.04073	6.06417	-0.0234375	-0.000729167
77	6.06	6.09892	6.08	0.0189236	-0.0389236
78	6.06	6.12281	6.09667	0.0261458	-0.0628125
79	6.07	NA	NA	0.0387847	NA
80	6.14	NA	NA	0.0269097	NA
81	6.19	NA	NA	0.0192014	NA
82	6.2	NA	NA	0.0078125	NA
83	6.22	NA	NA	-0.00295139	NA
84	6.22	NA	NA	-0.0203125	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 4.8 & NA & NA & -0.0210764 & NA \tabularnewline
2 & 4.81 & NA & NA & -0.0306597 & NA \tabularnewline
3 & 5.16 & NA & NA & -0.0393403 & NA \tabularnewline
4 & 5.26 & NA & NA & -0.0234375 & NA \tabularnewline
5 & 5.29 & NA & NA & 0.0189236 & NA \tabularnewline
6 & 5.29 & NA & NA & 0.0261458 & NA \tabularnewline
7 & 5.29 & 5.25962 & 5.22083 & 0.0387847 & 0.0303819 \tabularnewline
8 & 5.3 & 5.28899 & 5.26208 & 0.0269097 & 0.0110069 \tabularnewline
9 & 5.3 & 5.30753 & 5.28833 & 0.0192014 & -0.00753472 \tabularnewline
10 & 5.3 & 5.30573 & 5.29792 & 0.0078125 & -0.00572917 \tabularnewline
11 & 5.3 & 5.30497 & 5.30792 & -0.00295139 & -0.00496528 \tabularnewline
12 & 5.3 & 5.30135 & 5.32167 & -0.0203125 & -0.00135417 \tabularnewline
13 & 5.3 & 5.31559 & 5.33667 & -0.0210764 & -0.0155903 \tabularnewline
14 & 5.3 & 5.32101 & 5.35167 & -0.0306597 & -0.0210069 \tabularnewline
15 & 5.3 & 5.32733 & 5.36667 & -0.0393403 & -0.0273264 \tabularnewline
16 & 5.35 & 5.35823 & 5.38167 & -0.0234375 & -0.00822917 \tabularnewline
17 & 5.44 & 5.41559 & 5.39667 & 0.0189236 & 0.0244097 \tabularnewline
18 & 5.47 & 5.43781 & 5.41167 & 0.0261458 & 0.0321875 \tabularnewline
19 & 5.47 & 5.46545 & 5.42667 & 0.0387847 & 0.00454861 \tabularnewline
20 & 5.48 & 5.46858 & 5.44167 & 0.0269097 & 0.0114236 \tabularnewline
21 & 5.48 & 5.4767 & 5.4575 & 0.0192014 & 0.00329861 \tabularnewline
22 & 5.48 & 5.48198 & 5.47417 & 0.0078125 & -0.00197917 \tabularnewline
23 & 5.48 & 5.48497 & 5.48792 & -0.00295139 & -0.00496528 \tabularnewline
24 & 5.48 & 5.4776 & 5.49792 & -0.0203125 & 0.00239583 \tabularnewline
25 & 5.48 & 5.48601 & 5.50708 & -0.0210764 & -0.00600694 \tabularnewline
26 & 5.48 & 5.48517 & 5.51583 & -0.0306597 & -0.00517361 \tabularnewline
27 & 5.5 & 5.48524 & 5.52458 & -0.0393403 & 0.0147569 \tabularnewline
28 & 5.55 & 5.51031 & 5.53375 & -0.0234375 & 0.0396875 \tabularnewline
29 & 5.57 & 5.56184 & 5.54292 & 0.0189236 & 0.00815972 \tabularnewline
30 & 5.58 & 5.57656 & 5.55042 & 0.0261458 & 0.0034375 \tabularnewline
31 & 5.58 & 5.59753 & 5.55875 & 0.0387847 & -0.0175347 \tabularnewline
32 & 5.58 & 5.59649 & 5.56958 & 0.0269097 & -0.0164931 \tabularnewline
33 & 5.59 & 5.59878 & 5.57958 & 0.0192014 & -0.00878472 \tabularnewline
34 & 5.59 & 5.59531 & 5.5875 & 0.0078125 & -0.0053125 \tabularnewline
35 & 5.59 & 5.59288 & 5.59583 & -0.00295139 & -0.00288194 \tabularnewline
36 & 5.55 & 5.58552 & 5.60583 & -0.0203125 & -0.0355208 \tabularnewline
37 & 5.61 & 5.59476 & 5.61583 & -0.0210764 & 0.0152431 \tabularnewline
38 & 5.61 & 5.59517 & 5.62583 & -0.0306597 & 0.0148264 \tabularnewline
39 & 5.61 & 5.59608 & 5.63542 & -0.0393403 & 0.0139236 \tabularnewline
40 & 5.63 & 5.62115 & 5.64458 & -0.0234375 & 0.00885417 \tabularnewline
41 & 5.69 & 5.67267 & 5.65375 & 0.0189236 & 0.0173264 \tabularnewline
42 & 5.7 & 5.69073 & 5.66458 & 0.0261458 & 0.00927083 \tabularnewline
43 & 5.7 & 5.71337 & 5.67458 & 0.0387847 & -0.0133681 \tabularnewline
44 & 5.7 & 5.70899 & 5.68208 & 0.0269097 & -0.00899306 \tabularnewline
45 & 5.7 & 5.70878 & 5.68958 & 0.0192014 & -0.00878472 \tabularnewline
46 & 5.7 & 5.70448 & 5.69667 & 0.0078125 & -0.00447917 \tabularnewline
47 & 5.7 & 5.69913 & 5.70208 & -0.00295139 & 0.000868056 \tabularnewline
48 & 5.7 & 5.68677 & 5.70708 & -0.0203125 & 0.0132292 \tabularnewline
49 & 5.7 & 5.69267 & 5.71375 & -0.0210764 & 0.00732639 \tabularnewline
50 & 5.7 & 5.69059 & 5.72125 & -0.0306597 & 0.00940972 \tabularnewline
51 & 5.7 & 5.68983 & 5.72917 & -0.0393403 & 0.0101736 \tabularnewline
52 & 5.71 & 5.71406 & 5.7375 & -0.0234375 & -0.0040625 \tabularnewline
53 & 5.74 & 5.76476 & 5.74583 & 0.0189236 & -0.0247569 \tabularnewline
54 & 5.77 & 5.78031 & 5.75417 & 0.0261458 & -0.0103125 \tabularnewline
55 & 5.79 & 5.80128 & 5.7625 & 0.0387847 & -0.0112847 \tabularnewline
56 & 5.79 & 5.79816 & 5.77125 & 0.0269097 & -0.00815972 \tabularnewline
57 & 5.8 & 5.79962 & 5.78042 & 0.0192014 & 0.000381944 \tabularnewline
58 & 5.8 & 5.79781 & 5.79 & 0.0078125 & 0.0021875 \tabularnewline
59 & 5.8 & 5.80038 & 5.80333 & -0.00295139 & -0.000381944 \tabularnewline
60 & 5.8 & 5.8001 & 5.82042 & -0.0203125 & -0.000104167 \tabularnewline
61 & 5.8 & 5.81642 & 5.8375 & -0.0210764 & -0.0164236 \tabularnewline
62 & 5.81 & 5.82392 & 5.85458 & -0.0306597 & -0.0139236 \tabularnewline
63 & 5.81 & 5.83316 & 5.8725 & -0.0393403 & -0.0231597 \tabularnewline
64 & 5.83 & 5.8674 & 5.89083 & -0.0234375 & -0.0373958 \tabularnewline
65 & 5.94 & 5.92809 & 5.90917 & 0.0189236 & 0.0119097 \tabularnewline
66 & 5.98 & 5.95365 & 5.9275 & 0.0261458 & 0.0263542 \tabularnewline
67 & 5.99 & 5.98462 & 5.94583 & 0.0387847 & 0.00538194 \tabularnewline
68 & 6 & 5.99066 & 5.96375 & 0.0269097 & 0.00934028 \tabularnewline
69 & 6.02 & 6.00045 & 5.98125 & 0.0192014 & 0.0195486 \tabularnewline
70 & 6.02 & 6.00656 & 5.99875 & 0.0078125 & 0.0134375 \tabularnewline
71 & 6.02 & 6.00955 & 6.0125 & -0.00295139 & 0.0104514 \tabularnewline
72 & 6.02 & 6.00052 & 6.02083 & -0.0203125 & 0.0194792 \tabularnewline
73 & 6.02 & 6.00642 & 6.0275 & -0.0210764 & 0.0135764 \tabularnewline
74 & 6.02 & 6.00601 & 6.03667 & -0.0306597 & 0.0139931 \tabularnewline
75 & 6.02 & 6.01024 & 6.04958 & -0.0393403 & 0.00975694 \tabularnewline
76 & 6.04 & 6.04073 & 6.06417 & -0.0234375 & -0.000729167 \tabularnewline
77 & 6.06 & 6.09892 & 6.08 & 0.0189236 & -0.0389236 \tabularnewline
78 & 6.06 & 6.12281 & 6.09667 & 0.0261458 & -0.0628125 \tabularnewline
79 & 6.07 & NA & NA & 0.0387847 & NA \tabularnewline
80 & 6.14 & NA & NA & 0.0269097 & NA \tabularnewline
81 & 6.19 & NA & NA & 0.0192014 & NA \tabularnewline
82 & 6.2 & NA & NA & 0.0078125 & NA \tabularnewline
83 & 6.22 & NA & NA & -0.00295139 & NA \tabularnewline
84 & 6.22 & NA & NA & -0.0203125 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278525&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]4.8[/C][C]NA[/C][C]NA[/C][C]-0.0210764[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]4.81[/C][C]NA[/C][C]NA[/C][C]-0.0306597[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]5.16[/C][C]NA[/C][C]NA[/C][C]-0.0393403[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.26[/C][C]NA[/C][C]NA[/C][C]-0.0234375[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]5.29[/C][C]NA[/C][C]NA[/C][C]0.0189236[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5.29[/C][C]NA[/C][C]NA[/C][C]0.0261458[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.29[/C][C]5.25962[/C][C]5.22083[/C][C]0.0387847[/C][C]0.0303819[/C][/ROW]
[ROW][C]8[/C][C]5.3[/C][C]5.28899[/C][C]5.26208[/C][C]0.0269097[/C][C]0.0110069[/C][/ROW]
[ROW][C]9[/C][C]5.3[/C][C]5.30753[/C][C]5.28833[/C][C]0.0192014[/C][C]-0.00753472[/C][/ROW]
[ROW][C]10[/C][C]5.3[/C][C]5.30573[/C][C]5.29792[/C][C]0.0078125[/C][C]-0.00572917[/C][/ROW]
[ROW][C]11[/C][C]5.3[/C][C]5.30497[/C][C]5.30792[/C][C]-0.00295139[/C][C]-0.00496528[/C][/ROW]
[ROW][C]12[/C][C]5.3[/C][C]5.30135[/C][C]5.32167[/C][C]-0.0203125[/C][C]-0.00135417[/C][/ROW]
[ROW][C]13[/C][C]5.3[/C][C]5.31559[/C][C]5.33667[/C][C]-0.0210764[/C][C]-0.0155903[/C][/ROW]
[ROW][C]14[/C][C]5.3[/C][C]5.32101[/C][C]5.35167[/C][C]-0.0306597[/C][C]-0.0210069[/C][/ROW]
[ROW][C]15[/C][C]5.3[/C][C]5.32733[/C][C]5.36667[/C][C]-0.0393403[/C][C]-0.0273264[/C][/ROW]
[ROW][C]16[/C][C]5.35[/C][C]5.35823[/C][C]5.38167[/C][C]-0.0234375[/C][C]-0.00822917[/C][/ROW]
[ROW][C]17[/C][C]5.44[/C][C]5.41559[/C][C]5.39667[/C][C]0.0189236[/C][C]0.0244097[/C][/ROW]
[ROW][C]18[/C][C]5.47[/C][C]5.43781[/C][C]5.41167[/C][C]0.0261458[/C][C]0.0321875[/C][/ROW]
[ROW][C]19[/C][C]5.47[/C][C]5.46545[/C][C]5.42667[/C][C]0.0387847[/C][C]0.00454861[/C][/ROW]
[ROW][C]20[/C][C]5.48[/C][C]5.46858[/C][C]5.44167[/C][C]0.0269097[/C][C]0.0114236[/C][/ROW]
[ROW][C]21[/C][C]5.48[/C][C]5.4767[/C][C]5.4575[/C][C]0.0192014[/C][C]0.00329861[/C][/ROW]
[ROW][C]22[/C][C]5.48[/C][C]5.48198[/C][C]5.47417[/C][C]0.0078125[/C][C]-0.00197917[/C][/ROW]
[ROW][C]23[/C][C]5.48[/C][C]5.48497[/C][C]5.48792[/C][C]-0.00295139[/C][C]-0.00496528[/C][/ROW]
[ROW][C]24[/C][C]5.48[/C][C]5.4776[/C][C]5.49792[/C][C]-0.0203125[/C][C]0.00239583[/C][/ROW]
[ROW][C]25[/C][C]5.48[/C][C]5.48601[/C][C]5.50708[/C][C]-0.0210764[/C][C]-0.00600694[/C][/ROW]
[ROW][C]26[/C][C]5.48[/C][C]5.48517[/C][C]5.51583[/C][C]-0.0306597[/C][C]-0.00517361[/C][/ROW]
[ROW][C]27[/C][C]5.5[/C][C]5.48524[/C][C]5.52458[/C][C]-0.0393403[/C][C]0.0147569[/C][/ROW]
[ROW][C]28[/C][C]5.55[/C][C]5.51031[/C][C]5.53375[/C][C]-0.0234375[/C][C]0.0396875[/C][/ROW]
[ROW][C]29[/C][C]5.57[/C][C]5.56184[/C][C]5.54292[/C][C]0.0189236[/C][C]0.00815972[/C][/ROW]
[ROW][C]30[/C][C]5.58[/C][C]5.57656[/C][C]5.55042[/C][C]0.0261458[/C][C]0.0034375[/C][/ROW]
[ROW][C]31[/C][C]5.58[/C][C]5.59753[/C][C]5.55875[/C][C]0.0387847[/C][C]-0.0175347[/C][/ROW]
[ROW][C]32[/C][C]5.58[/C][C]5.59649[/C][C]5.56958[/C][C]0.0269097[/C][C]-0.0164931[/C][/ROW]
[ROW][C]33[/C][C]5.59[/C][C]5.59878[/C][C]5.57958[/C][C]0.0192014[/C][C]-0.00878472[/C][/ROW]
[ROW][C]34[/C][C]5.59[/C][C]5.59531[/C][C]5.5875[/C][C]0.0078125[/C][C]-0.0053125[/C][/ROW]
[ROW][C]35[/C][C]5.59[/C][C]5.59288[/C][C]5.59583[/C][C]-0.00295139[/C][C]-0.00288194[/C][/ROW]
[ROW][C]36[/C][C]5.55[/C][C]5.58552[/C][C]5.60583[/C][C]-0.0203125[/C][C]-0.0355208[/C][/ROW]
[ROW][C]37[/C][C]5.61[/C][C]5.59476[/C][C]5.61583[/C][C]-0.0210764[/C][C]0.0152431[/C][/ROW]
[ROW][C]38[/C][C]5.61[/C][C]5.59517[/C][C]5.62583[/C][C]-0.0306597[/C][C]0.0148264[/C][/ROW]
[ROW][C]39[/C][C]5.61[/C][C]5.59608[/C][C]5.63542[/C][C]-0.0393403[/C][C]0.0139236[/C][/ROW]
[ROW][C]40[/C][C]5.63[/C][C]5.62115[/C][C]5.64458[/C][C]-0.0234375[/C][C]0.00885417[/C][/ROW]
[ROW][C]41[/C][C]5.69[/C][C]5.67267[/C][C]5.65375[/C][C]0.0189236[/C][C]0.0173264[/C][/ROW]
[ROW][C]42[/C][C]5.7[/C][C]5.69073[/C][C]5.66458[/C][C]0.0261458[/C][C]0.00927083[/C][/ROW]
[ROW][C]43[/C][C]5.7[/C][C]5.71337[/C][C]5.67458[/C][C]0.0387847[/C][C]-0.0133681[/C][/ROW]
[ROW][C]44[/C][C]5.7[/C][C]5.70899[/C][C]5.68208[/C][C]0.0269097[/C][C]-0.00899306[/C][/ROW]
[ROW][C]45[/C][C]5.7[/C][C]5.70878[/C][C]5.68958[/C][C]0.0192014[/C][C]-0.00878472[/C][/ROW]
[ROW][C]46[/C][C]5.7[/C][C]5.70448[/C][C]5.69667[/C][C]0.0078125[/C][C]-0.00447917[/C][/ROW]
[ROW][C]47[/C][C]5.7[/C][C]5.69913[/C][C]5.70208[/C][C]-0.00295139[/C][C]0.000868056[/C][/ROW]
[ROW][C]48[/C][C]5.7[/C][C]5.68677[/C][C]5.70708[/C][C]-0.0203125[/C][C]0.0132292[/C][/ROW]
[ROW][C]49[/C][C]5.7[/C][C]5.69267[/C][C]5.71375[/C][C]-0.0210764[/C][C]0.00732639[/C][/ROW]
[ROW][C]50[/C][C]5.7[/C][C]5.69059[/C][C]5.72125[/C][C]-0.0306597[/C][C]0.00940972[/C][/ROW]
[ROW][C]51[/C][C]5.7[/C][C]5.68983[/C][C]5.72917[/C][C]-0.0393403[/C][C]0.0101736[/C][/ROW]
[ROW][C]52[/C][C]5.71[/C][C]5.71406[/C][C]5.7375[/C][C]-0.0234375[/C][C]-0.0040625[/C][/ROW]
[ROW][C]53[/C][C]5.74[/C][C]5.76476[/C][C]5.74583[/C][C]0.0189236[/C][C]-0.0247569[/C][/ROW]
[ROW][C]54[/C][C]5.77[/C][C]5.78031[/C][C]5.75417[/C][C]0.0261458[/C][C]-0.0103125[/C][/ROW]
[ROW][C]55[/C][C]5.79[/C][C]5.80128[/C][C]5.7625[/C][C]0.0387847[/C][C]-0.0112847[/C][/ROW]
[ROW][C]56[/C][C]5.79[/C][C]5.79816[/C][C]5.77125[/C][C]0.0269097[/C][C]-0.00815972[/C][/ROW]
[ROW][C]57[/C][C]5.8[/C][C]5.79962[/C][C]5.78042[/C][C]0.0192014[/C][C]0.000381944[/C][/ROW]
[ROW][C]58[/C][C]5.8[/C][C]5.79781[/C][C]5.79[/C][C]0.0078125[/C][C]0.0021875[/C][/ROW]
[ROW][C]59[/C][C]5.8[/C][C]5.80038[/C][C]5.80333[/C][C]-0.00295139[/C][C]-0.000381944[/C][/ROW]
[ROW][C]60[/C][C]5.8[/C][C]5.8001[/C][C]5.82042[/C][C]-0.0203125[/C][C]-0.000104167[/C][/ROW]
[ROW][C]61[/C][C]5.8[/C][C]5.81642[/C][C]5.8375[/C][C]-0.0210764[/C][C]-0.0164236[/C][/ROW]
[ROW][C]62[/C][C]5.81[/C][C]5.82392[/C][C]5.85458[/C][C]-0.0306597[/C][C]-0.0139236[/C][/ROW]
[ROW][C]63[/C][C]5.81[/C][C]5.83316[/C][C]5.8725[/C][C]-0.0393403[/C][C]-0.0231597[/C][/ROW]
[ROW][C]64[/C][C]5.83[/C][C]5.8674[/C][C]5.89083[/C][C]-0.0234375[/C][C]-0.0373958[/C][/ROW]
[ROW][C]65[/C][C]5.94[/C][C]5.92809[/C][C]5.90917[/C][C]0.0189236[/C][C]0.0119097[/C][/ROW]
[ROW][C]66[/C][C]5.98[/C][C]5.95365[/C][C]5.9275[/C][C]0.0261458[/C][C]0.0263542[/C][/ROW]
[ROW][C]67[/C][C]5.99[/C][C]5.98462[/C][C]5.94583[/C][C]0.0387847[/C][C]0.00538194[/C][/ROW]
[ROW][C]68[/C][C]6[/C][C]5.99066[/C][C]5.96375[/C][C]0.0269097[/C][C]0.00934028[/C][/ROW]
[ROW][C]69[/C][C]6.02[/C][C]6.00045[/C][C]5.98125[/C][C]0.0192014[/C][C]0.0195486[/C][/ROW]
[ROW][C]70[/C][C]6.02[/C][C]6.00656[/C][C]5.99875[/C][C]0.0078125[/C][C]0.0134375[/C][/ROW]
[ROW][C]71[/C][C]6.02[/C][C]6.00955[/C][C]6.0125[/C][C]-0.00295139[/C][C]0.0104514[/C][/ROW]
[ROW][C]72[/C][C]6.02[/C][C]6.00052[/C][C]6.02083[/C][C]-0.0203125[/C][C]0.0194792[/C][/ROW]
[ROW][C]73[/C][C]6.02[/C][C]6.00642[/C][C]6.0275[/C][C]-0.0210764[/C][C]0.0135764[/C][/ROW]
[ROW][C]74[/C][C]6.02[/C][C]6.00601[/C][C]6.03667[/C][C]-0.0306597[/C][C]0.0139931[/C][/ROW]
[ROW][C]75[/C][C]6.02[/C][C]6.01024[/C][C]6.04958[/C][C]-0.0393403[/C][C]0.00975694[/C][/ROW]
[ROW][C]76[/C][C]6.04[/C][C]6.04073[/C][C]6.06417[/C][C]-0.0234375[/C][C]-0.000729167[/C][/ROW]
[ROW][C]77[/C][C]6.06[/C][C]6.09892[/C][C]6.08[/C][C]0.0189236[/C][C]-0.0389236[/C][/ROW]
[ROW][C]78[/C][C]6.06[/C][C]6.12281[/C][C]6.09667[/C][C]0.0261458[/C][C]-0.0628125[/C][/ROW]
[ROW][C]79[/C][C]6.07[/C][C]NA[/C][C]NA[/C][C]0.0387847[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]6.14[/C][C]NA[/C][C]NA[/C][C]0.0269097[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]6.19[/C][C]NA[/C][C]NA[/C][C]0.0192014[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]6.2[/C][C]NA[/C][C]NA[/C][C]0.0078125[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]6.22[/C][C]NA[/C][C]NA[/C][C]-0.00295139[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]6.22[/C][C]NA[/C][C]NA[/C][C]-0.0203125[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278525&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278525&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	4.8	NA	NA	-0.0210764	NA
2	4.81	NA	NA	-0.0306597	NA
3	5.16	NA	NA	-0.0393403	NA
4	5.26	NA	NA	-0.0234375	NA
5	5.29	NA	NA	0.0189236	NA
6	5.29	NA	NA	0.0261458	NA
7	5.29	5.25962	5.22083	0.0387847	0.0303819
8	5.3	5.28899	5.26208	0.0269097	0.0110069
9	5.3	5.30753	5.28833	0.0192014	-0.00753472
10	5.3	5.30573	5.29792	0.0078125	-0.00572917
11	5.3	5.30497	5.30792	-0.00295139	-0.00496528
12	5.3	5.30135	5.32167	-0.0203125	-0.00135417
13	5.3	5.31559	5.33667	-0.0210764	-0.0155903
14	5.3	5.32101	5.35167	-0.0306597	-0.0210069
15	5.3	5.32733	5.36667	-0.0393403	-0.0273264
16	5.35	5.35823	5.38167	-0.0234375	-0.00822917
17	5.44	5.41559	5.39667	0.0189236	0.0244097
18	5.47	5.43781	5.41167	0.0261458	0.0321875
19	5.47	5.46545	5.42667	0.0387847	0.00454861
20	5.48	5.46858	5.44167	0.0269097	0.0114236
21	5.48	5.4767	5.4575	0.0192014	0.00329861
22	5.48	5.48198	5.47417	0.0078125	-0.00197917
23	5.48	5.48497	5.48792	-0.00295139	-0.00496528
24	5.48	5.4776	5.49792	-0.0203125	0.00239583
25	5.48	5.48601	5.50708	-0.0210764	-0.00600694
26	5.48	5.48517	5.51583	-0.0306597	-0.00517361
27	5.5	5.48524	5.52458	-0.0393403	0.0147569
28	5.55	5.51031	5.53375	-0.0234375	0.0396875
29	5.57	5.56184	5.54292	0.0189236	0.00815972
30	5.58	5.57656	5.55042	0.0261458	0.0034375
31	5.58	5.59753	5.55875	0.0387847	-0.0175347
32	5.58	5.59649	5.56958	0.0269097	-0.0164931
33	5.59	5.59878	5.57958	0.0192014	-0.00878472
34	5.59	5.59531	5.5875	0.0078125	-0.0053125
35	5.59	5.59288	5.59583	-0.00295139	-0.00288194
36	5.55	5.58552	5.60583	-0.0203125	-0.0355208
37	5.61	5.59476	5.61583	-0.0210764	0.0152431
38	5.61	5.59517	5.62583	-0.0306597	0.0148264
39	5.61	5.59608	5.63542	-0.0393403	0.0139236
40	5.63	5.62115	5.64458	-0.0234375	0.00885417
41	5.69	5.67267	5.65375	0.0189236	0.0173264
42	5.7	5.69073	5.66458	0.0261458	0.00927083
43	5.7	5.71337	5.67458	0.0387847	-0.0133681
44	5.7	5.70899	5.68208	0.0269097	-0.00899306
45	5.7	5.70878	5.68958	0.0192014	-0.00878472
46	5.7	5.70448	5.69667	0.0078125	-0.00447917
47	5.7	5.69913	5.70208	-0.00295139	0.000868056
48	5.7	5.68677	5.70708	-0.0203125	0.0132292
49	5.7	5.69267	5.71375	-0.0210764	0.00732639
50	5.7	5.69059	5.72125	-0.0306597	0.00940972
51	5.7	5.68983	5.72917	-0.0393403	0.0101736
52	5.71	5.71406	5.7375	-0.0234375	-0.0040625
53	5.74	5.76476	5.74583	0.0189236	-0.0247569
54	5.77	5.78031	5.75417	0.0261458	-0.0103125
55	5.79	5.80128	5.7625	0.0387847	-0.0112847
56	5.79	5.79816	5.77125	0.0269097	-0.00815972
57	5.8	5.79962	5.78042	0.0192014	0.000381944
58	5.8	5.79781	5.79	0.0078125	0.0021875
59	5.8	5.80038	5.80333	-0.00295139	-0.000381944
60	5.8	5.8001	5.82042	-0.0203125	-0.000104167
61	5.8	5.81642	5.8375	-0.0210764	-0.0164236
62	5.81	5.82392	5.85458	-0.0306597	-0.0139236
63	5.81	5.83316	5.8725	-0.0393403	-0.0231597
64	5.83	5.8674	5.89083	-0.0234375	-0.0373958
65	5.94	5.92809	5.90917	0.0189236	0.0119097
66	5.98	5.95365	5.9275	0.0261458	0.0263542
67	5.99	5.98462	5.94583	0.0387847	0.00538194
68	6	5.99066	5.96375	0.0269097	0.00934028
69	6.02	6.00045	5.98125	0.0192014	0.0195486
70	6.02	6.00656	5.99875	0.0078125	0.0134375
71	6.02	6.00955	6.0125	-0.00295139	0.0104514
72	6.02	6.00052	6.02083	-0.0203125	0.0194792
73	6.02	6.00642	6.0275	-0.0210764	0.0135764
74	6.02	6.00601	6.03667	-0.0306597	0.0139931
75	6.02	6.01024	6.04958	-0.0393403	0.00975694
76	6.04	6.04073	6.06417	-0.0234375	-0.000729167
77	6.06	6.09892	6.08	0.0189236	-0.0389236
78	6.06	6.12281	6.09667	0.0261458	-0.0628125
79	6.07	NA	NA	0.0387847	NA
80	6.14	NA	NA	0.0269097	NA
81	6.19	NA	NA	0.0192014	NA
82	6.2	NA	NA	0.0078125	NA
83	6.22	NA	NA	-0.00295139	NA
84	6.22	NA	NA	-0.0203125	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 <- '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