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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 02 Jan 2014 05:02:11 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Jan/02/t1388656998wkdm6ep2ahnf0lh.htm/, Retrieved Sun, 19 May 2024 07:23:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232724, Retrieved Sun, 19 May 2024 07:23:08 +0000

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Estimated Impact

143

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-       [Classical Decomposition] [Classical Deompos...] [2014-01-02 10:02:11] [a0dc50058fa7049d3ca1c49ed2014afb] [Current]

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Dataseries X:

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1,26
1,26
1,28
1,34
1,39
1,47
1,57
1,63
1,72
1,43
1,35
1,41
1,44
1,43
1,43
1,42
1,45
1,51
1,48
1,48
1,45
1,38
1,46
1,45
1,41
1,45
1,47
1,47
1,53
1,56
1,66
1,79
1,78
1,46
1,41
1,43
1,43
1,45
1,35
1,35
1,29
1,29
1,26
1,3
1,3
1,16
1,24
1,15
1,21
1,22
1,17
1,13
1,15
1,2
1,23
1,25
1,38
1,28
1,26
1,25
1,26
1,28
1,31
1,22
1,23
1,36
1,54
1,58
1,44
1,29
1,28
1,23
1,2
1,22
1,19
1,17
1,22
1,29
1,39
1,53
1,82
1,77
1,63
1,57

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 4 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232724&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232724&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232724&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	4 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.26	NA	NA	-0.0386979	NA
2	1.26	NA	NA	-0.0200868	NA
3	1.28	NA	NA	-0.0417535	NA
4	1.34	NA	NA	-0.0714757	NA
5	1.39	NA	NA	-0.0574479	NA
6	1.47	NA	NA	-0.00383681	NA
7	1.57	1.51561	1.43333	0.0822743	0.0543924
8	1.63	1.57922	1.44792	0.131302	0.0507812
9	1.72	1.60012	1.46125	0.138872	0.119878
10	1.43	1.43318	1.47083	-0.0376562	-0.00317708
11	1.35	1.44137	1.47667	-0.0352951	-0.0913715
12	1.41	1.43464	1.48083	-0.0461979	-0.0246354
13	1.44	1.44005	1.47875	-0.0386979	-5.20833e-05
14	1.43	1.44866	1.46875	-0.0200868	-0.0186632
15	1.43	1.4095	1.45125	-0.0417535	0.0205035
16	1.42	1.36644	1.43792	-0.0714757	0.053559
17	1.45	1.38297	1.44042	-0.0574479	0.0670313
18	1.51	1.44283	1.44667	-0.00383681	0.0671701
19	1.48	1.52936	1.44708	0.0822743	-0.0493576
20	1.48	1.57797	1.44667	0.131302	-0.0979687
21	1.45	1.58804	1.44917	0.138872	-0.138038
22	1.38	1.41526	1.45292	-0.0376562	-0.0352604
23	1.46	1.42304	1.45833	-0.0352951	0.0369618
24	1.45	1.41755	1.46375	-0.0461979	0.0324479
25	1.41	1.43464	1.47333	-0.0386979	-0.0246354
26	1.45	1.47366	1.49375	-0.0200868	-0.0236632
27	1.47	1.47866	1.52042	-0.0417535	-0.00866319
28	1.47	1.46602	1.5375	-0.0714757	0.00397569
29	1.53	1.4813	1.53875	-0.0574479	0.0486979
30	1.56	1.532	1.53583	-0.00383681	0.0280035
31	1.66	1.61811	1.53583	0.0822743	0.0418924
32	1.79	1.66797	1.53667	0.131302	0.122031
33	1.78	1.67054	1.53167	0.138872	0.109462
34	1.46	1.48401	1.52167	-0.0376562	-0.0240104
35	1.41	1.47137	1.50667	-0.0352951	-0.0613715
36	1.43	1.43922	1.48542	-0.0461979	-0.00921875
37	1.43	1.4188	1.4575	-0.0386979	0.0111979
38	1.45	1.40033	1.42042	-0.0200868	0.0496701
39	1.35	1.33825	1.38	-0.0417535	0.0117535
40	1.35	1.27602	1.3475	-0.0714757	0.0739757
41	1.29	1.27047	1.32792	-0.0574479	0.0195312
42	1.29	1.30533	1.30917	-0.00383681	-0.0153299
43	1.26	1.37061	1.28833	0.0822743	-0.110608
44	1.3	1.40089	1.26958	0.131302	-0.100885
45	1.3	1.39137	1.2525	0.138872	-0.0913715
46	1.16	1.19818	1.23583	-0.0376562	-0.0381771
47	1.24	1.18554	1.22083	-0.0352951	0.0544618
48	1.15	1.16505	1.21125	-0.0461979	-0.0150521
49	1.21	1.16755	1.20625	-0.0386979	0.0424479
50	1.22	1.18283	1.20292	-0.0200868	0.0371701
51	1.17	1.16241	1.20417	-0.0417535	0.00758681
52	1.13	1.14102	1.2125	-0.0714757	-0.0110243
53	1.15	1.16089	1.21833	-0.0574479	-0.0108854
54	1.2	1.2195	1.22333	-0.00383681	-0.0194965
55	1.23	1.31186	1.22958	0.0822743	-0.0818576
56	1.25	1.36547	1.23417	0.131302	-0.115469
57	1.38	1.38137	1.2425	0.138872	-0.00137153
58	1.28	1.21443	1.25208	-0.0376562	0.0655729
59	1.26	1.22387	1.25917	-0.0352951	0.0361285
60	1.25	1.22297	1.26917	-0.0461979	0.0270313
61	1.26	1.25005	1.28875	-0.0386979	0.00994792
62	1.28	1.29533	1.31542	-0.0200868	-0.0153299
63	1.31	1.28991	1.33167	-0.0417535	0.0200868
64	1.22	1.26311	1.33458	-0.0714757	-0.0431076
65	1.23	1.27839	1.33583	-0.0574479	-0.0483854
66	1.36	1.332	1.33583	-0.00383681	0.0280035
67	1.54	1.41477	1.3325	0.0822743	0.125226
68	1.58	1.4588	1.3275	0.131302	0.121198
69	1.44	1.45887	1.32	0.138872	-0.0188715
70	1.29	1.27526	1.31292	-0.0376562	0.0147396
71	1.28	1.27512	1.31042	-0.0352951	0.00487847
72	1.23	1.26089	1.30708	-0.0461979	-0.0308854
73	1.2	1.25922	1.29792	-0.0386979	-0.0592187
74	1.22	1.2695	1.28958	-0.0200868	-0.0494965
75	1.19	1.26158	1.30333	-0.0417535	-0.0715799
76	1.17	1.26769	1.33917	-0.0714757	-0.097691
77	1.22	1.3163	1.37375	-0.0574479	-0.0963021
78	1.29	1.39866	1.4025	-0.00383681	-0.108663
79	1.39	NA	NA	0.0822743	NA
80	1.53	NA	NA	0.131302	NA
81	1.82	NA	NA	0.138872	NA
82	1.77	NA	NA	-0.0376562	NA
83	1.63	NA	NA	-0.0352951	NA
84	1.57	NA	NA	-0.0461979	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.26 & NA & NA & -0.0386979 & NA \tabularnewline
2 & 1.26 & NA & NA & -0.0200868 & NA \tabularnewline
3 & 1.28 & NA & NA & -0.0417535 & NA \tabularnewline
4 & 1.34 & NA & NA & -0.0714757 & NA \tabularnewline
5 & 1.39 & NA & NA & -0.0574479 & NA \tabularnewline
6 & 1.47 & NA & NA & -0.00383681 & NA \tabularnewline
7 & 1.57 & 1.51561 & 1.43333 & 0.0822743 & 0.0543924 \tabularnewline
8 & 1.63 & 1.57922 & 1.44792 & 0.131302 & 0.0507812 \tabularnewline
9 & 1.72 & 1.60012 & 1.46125 & 0.138872 & 0.119878 \tabularnewline
10 & 1.43 & 1.43318 & 1.47083 & -0.0376562 & -0.00317708 \tabularnewline
11 & 1.35 & 1.44137 & 1.47667 & -0.0352951 & -0.0913715 \tabularnewline
12 & 1.41 & 1.43464 & 1.48083 & -0.0461979 & -0.0246354 \tabularnewline
13 & 1.44 & 1.44005 & 1.47875 & -0.0386979 & -5.20833e-05 \tabularnewline
14 & 1.43 & 1.44866 & 1.46875 & -0.0200868 & -0.0186632 \tabularnewline
15 & 1.43 & 1.4095 & 1.45125 & -0.0417535 & 0.0205035 \tabularnewline
16 & 1.42 & 1.36644 & 1.43792 & -0.0714757 & 0.053559 \tabularnewline
17 & 1.45 & 1.38297 & 1.44042 & -0.0574479 & 0.0670313 \tabularnewline
18 & 1.51 & 1.44283 & 1.44667 & -0.00383681 & 0.0671701 \tabularnewline
19 & 1.48 & 1.52936 & 1.44708 & 0.0822743 & -0.0493576 \tabularnewline
20 & 1.48 & 1.57797 & 1.44667 & 0.131302 & -0.0979687 \tabularnewline
21 & 1.45 & 1.58804 & 1.44917 & 0.138872 & -0.138038 \tabularnewline
22 & 1.38 & 1.41526 & 1.45292 & -0.0376562 & -0.0352604 \tabularnewline
23 & 1.46 & 1.42304 & 1.45833 & -0.0352951 & 0.0369618 \tabularnewline
24 & 1.45 & 1.41755 & 1.46375 & -0.0461979 & 0.0324479 \tabularnewline
25 & 1.41 & 1.43464 & 1.47333 & -0.0386979 & -0.0246354 \tabularnewline
26 & 1.45 & 1.47366 & 1.49375 & -0.0200868 & -0.0236632 \tabularnewline
27 & 1.47 & 1.47866 & 1.52042 & -0.0417535 & -0.00866319 \tabularnewline
28 & 1.47 & 1.46602 & 1.5375 & -0.0714757 & 0.00397569 \tabularnewline
29 & 1.53 & 1.4813 & 1.53875 & -0.0574479 & 0.0486979 \tabularnewline
30 & 1.56 & 1.532 & 1.53583 & -0.00383681 & 0.0280035 \tabularnewline
31 & 1.66 & 1.61811 & 1.53583 & 0.0822743 & 0.0418924 \tabularnewline
32 & 1.79 & 1.66797 & 1.53667 & 0.131302 & 0.122031 \tabularnewline
33 & 1.78 & 1.67054 & 1.53167 & 0.138872 & 0.109462 \tabularnewline
34 & 1.46 & 1.48401 & 1.52167 & -0.0376562 & -0.0240104 \tabularnewline
35 & 1.41 & 1.47137 & 1.50667 & -0.0352951 & -0.0613715 \tabularnewline
36 & 1.43 & 1.43922 & 1.48542 & -0.0461979 & -0.00921875 \tabularnewline
37 & 1.43 & 1.4188 & 1.4575 & -0.0386979 & 0.0111979 \tabularnewline
38 & 1.45 & 1.40033 & 1.42042 & -0.0200868 & 0.0496701 \tabularnewline
39 & 1.35 & 1.33825 & 1.38 & -0.0417535 & 0.0117535 \tabularnewline
40 & 1.35 & 1.27602 & 1.3475 & -0.0714757 & 0.0739757 \tabularnewline
41 & 1.29 & 1.27047 & 1.32792 & -0.0574479 & 0.0195312 \tabularnewline
42 & 1.29 & 1.30533 & 1.30917 & -0.00383681 & -0.0153299 \tabularnewline
43 & 1.26 & 1.37061 & 1.28833 & 0.0822743 & -0.110608 \tabularnewline
44 & 1.3 & 1.40089 & 1.26958 & 0.131302 & -0.100885 \tabularnewline
45 & 1.3 & 1.39137 & 1.2525 & 0.138872 & -0.0913715 \tabularnewline
46 & 1.16 & 1.19818 & 1.23583 & -0.0376562 & -0.0381771 \tabularnewline
47 & 1.24 & 1.18554 & 1.22083 & -0.0352951 & 0.0544618 \tabularnewline
48 & 1.15 & 1.16505 & 1.21125 & -0.0461979 & -0.0150521 \tabularnewline
49 & 1.21 & 1.16755 & 1.20625 & -0.0386979 & 0.0424479 \tabularnewline
50 & 1.22 & 1.18283 & 1.20292 & -0.0200868 & 0.0371701 \tabularnewline
51 & 1.17 & 1.16241 & 1.20417 & -0.0417535 & 0.00758681 \tabularnewline
52 & 1.13 & 1.14102 & 1.2125 & -0.0714757 & -0.0110243 \tabularnewline
53 & 1.15 & 1.16089 & 1.21833 & -0.0574479 & -0.0108854 \tabularnewline
54 & 1.2 & 1.2195 & 1.22333 & -0.00383681 & -0.0194965 \tabularnewline
55 & 1.23 & 1.31186 & 1.22958 & 0.0822743 & -0.0818576 \tabularnewline
56 & 1.25 & 1.36547 & 1.23417 & 0.131302 & -0.115469 \tabularnewline
57 & 1.38 & 1.38137 & 1.2425 & 0.138872 & -0.00137153 \tabularnewline
58 & 1.28 & 1.21443 & 1.25208 & -0.0376562 & 0.0655729 \tabularnewline
59 & 1.26 & 1.22387 & 1.25917 & -0.0352951 & 0.0361285 \tabularnewline
60 & 1.25 & 1.22297 & 1.26917 & -0.0461979 & 0.0270313 \tabularnewline
61 & 1.26 & 1.25005 & 1.28875 & -0.0386979 & 0.00994792 \tabularnewline
62 & 1.28 & 1.29533 & 1.31542 & -0.0200868 & -0.0153299 \tabularnewline
63 & 1.31 & 1.28991 & 1.33167 & -0.0417535 & 0.0200868 \tabularnewline
64 & 1.22 & 1.26311 & 1.33458 & -0.0714757 & -0.0431076 \tabularnewline
65 & 1.23 & 1.27839 & 1.33583 & -0.0574479 & -0.0483854 \tabularnewline
66 & 1.36 & 1.332 & 1.33583 & -0.00383681 & 0.0280035 \tabularnewline
67 & 1.54 & 1.41477 & 1.3325 & 0.0822743 & 0.125226 \tabularnewline
68 & 1.58 & 1.4588 & 1.3275 & 0.131302 & 0.121198 \tabularnewline
69 & 1.44 & 1.45887 & 1.32 & 0.138872 & -0.0188715 \tabularnewline
70 & 1.29 & 1.27526 & 1.31292 & -0.0376562 & 0.0147396 \tabularnewline
71 & 1.28 & 1.27512 & 1.31042 & -0.0352951 & 0.00487847 \tabularnewline
72 & 1.23 & 1.26089 & 1.30708 & -0.0461979 & -0.0308854 \tabularnewline
73 & 1.2 & 1.25922 & 1.29792 & -0.0386979 & -0.0592187 \tabularnewline
74 & 1.22 & 1.2695 & 1.28958 & -0.0200868 & -0.0494965 \tabularnewline
75 & 1.19 & 1.26158 & 1.30333 & -0.0417535 & -0.0715799 \tabularnewline
76 & 1.17 & 1.26769 & 1.33917 & -0.0714757 & -0.097691 \tabularnewline
77 & 1.22 & 1.3163 & 1.37375 & -0.0574479 & -0.0963021 \tabularnewline
78 & 1.29 & 1.39866 & 1.4025 & -0.00383681 & -0.108663 \tabularnewline
79 & 1.39 & NA & NA & 0.0822743 & NA \tabularnewline
80 & 1.53 & NA & NA & 0.131302 & NA \tabularnewline
81 & 1.82 & NA & NA & 0.138872 & NA \tabularnewline
82 & 1.77 & NA & NA & -0.0376562 & NA \tabularnewline
83 & 1.63 & NA & NA & -0.0352951 & NA \tabularnewline
84 & 1.57 & NA & NA & -0.0461979 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232724&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]1.26[/C][C]NA[/C][C]NA[/C][C]-0.0386979[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.26[/C][C]NA[/C][C]NA[/C][C]-0.0200868[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.28[/C][C]NA[/C][C]NA[/C][C]-0.0417535[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.34[/C][C]NA[/C][C]NA[/C][C]-0.0714757[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.39[/C][C]NA[/C][C]NA[/C][C]-0.0574479[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.47[/C][C]NA[/C][C]NA[/C][C]-0.00383681[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.57[/C][C]1.51561[/C][C]1.43333[/C][C]0.0822743[/C][C]0.0543924[/C][/ROW]
[ROW][C]8[/C][C]1.63[/C][C]1.57922[/C][C]1.44792[/C][C]0.131302[/C][C]0.0507812[/C][/ROW]
[ROW][C]9[/C][C]1.72[/C][C]1.60012[/C][C]1.46125[/C][C]0.138872[/C][C]0.119878[/C][/ROW]
[ROW][C]10[/C][C]1.43[/C][C]1.43318[/C][C]1.47083[/C][C]-0.0376562[/C][C]-0.00317708[/C][/ROW]
[ROW][C]11[/C][C]1.35[/C][C]1.44137[/C][C]1.47667[/C][C]-0.0352951[/C][C]-0.0913715[/C][/ROW]
[ROW][C]12[/C][C]1.41[/C][C]1.43464[/C][C]1.48083[/C][C]-0.0461979[/C][C]-0.0246354[/C][/ROW]
[ROW][C]13[/C][C]1.44[/C][C]1.44005[/C][C]1.47875[/C][C]-0.0386979[/C][C]-5.20833e-05[/C][/ROW]
[ROW][C]14[/C][C]1.43[/C][C]1.44866[/C][C]1.46875[/C][C]-0.0200868[/C][C]-0.0186632[/C][/ROW]
[ROW][C]15[/C][C]1.43[/C][C]1.4095[/C][C]1.45125[/C][C]-0.0417535[/C][C]0.0205035[/C][/ROW]
[ROW][C]16[/C][C]1.42[/C][C]1.36644[/C][C]1.43792[/C][C]-0.0714757[/C][C]0.053559[/C][/ROW]
[ROW][C]17[/C][C]1.45[/C][C]1.38297[/C][C]1.44042[/C][C]-0.0574479[/C][C]0.0670313[/C][/ROW]
[ROW][C]18[/C][C]1.51[/C][C]1.44283[/C][C]1.44667[/C][C]-0.00383681[/C][C]0.0671701[/C][/ROW]
[ROW][C]19[/C][C]1.48[/C][C]1.52936[/C][C]1.44708[/C][C]0.0822743[/C][C]-0.0493576[/C][/ROW]
[ROW][C]20[/C][C]1.48[/C][C]1.57797[/C][C]1.44667[/C][C]0.131302[/C][C]-0.0979687[/C][/ROW]
[ROW][C]21[/C][C]1.45[/C][C]1.58804[/C][C]1.44917[/C][C]0.138872[/C][C]-0.138038[/C][/ROW]
[ROW][C]22[/C][C]1.38[/C][C]1.41526[/C][C]1.45292[/C][C]-0.0376562[/C][C]-0.0352604[/C][/ROW]
[ROW][C]23[/C][C]1.46[/C][C]1.42304[/C][C]1.45833[/C][C]-0.0352951[/C][C]0.0369618[/C][/ROW]
[ROW][C]24[/C][C]1.45[/C][C]1.41755[/C][C]1.46375[/C][C]-0.0461979[/C][C]0.0324479[/C][/ROW]
[ROW][C]25[/C][C]1.41[/C][C]1.43464[/C][C]1.47333[/C][C]-0.0386979[/C][C]-0.0246354[/C][/ROW]
[ROW][C]26[/C][C]1.45[/C][C]1.47366[/C][C]1.49375[/C][C]-0.0200868[/C][C]-0.0236632[/C][/ROW]
[ROW][C]27[/C][C]1.47[/C][C]1.47866[/C][C]1.52042[/C][C]-0.0417535[/C][C]-0.00866319[/C][/ROW]
[ROW][C]28[/C][C]1.47[/C][C]1.46602[/C][C]1.5375[/C][C]-0.0714757[/C][C]0.00397569[/C][/ROW]
[ROW][C]29[/C][C]1.53[/C][C]1.4813[/C][C]1.53875[/C][C]-0.0574479[/C][C]0.0486979[/C][/ROW]
[ROW][C]30[/C][C]1.56[/C][C]1.532[/C][C]1.53583[/C][C]-0.00383681[/C][C]0.0280035[/C][/ROW]
[ROW][C]31[/C][C]1.66[/C][C]1.61811[/C][C]1.53583[/C][C]0.0822743[/C][C]0.0418924[/C][/ROW]
[ROW][C]32[/C][C]1.79[/C][C]1.66797[/C][C]1.53667[/C][C]0.131302[/C][C]0.122031[/C][/ROW]
[ROW][C]33[/C][C]1.78[/C][C]1.67054[/C][C]1.53167[/C][C]0.138872[/C][C]0.109462[/C][/ROW]
[ROW][C]34[/C][C]1.46[/C][C]1.48401[/C][C]1.52167[/C][C]-0.0376562[/C][C]-0.0240104[/C][/ROW]
[ROW][C]35[/C][C]1.41[/C][C]1.47137[/C][C]1.50667[/C][C]-0.0352951[/C][C]-0.0613715[/C][/ROW]
[ROW][C]36[/C][C]1.43[/C][C]1.43922[/C][C]1.48542[/C][C]-0.0461979[/C][C]-0.00921875[/C][/ROW]
[ROW][C]37[/C][C]1.43[/C][C]1.4188[/C][C]1.4575[/C][C]-0.0386979[/C][C]0.0111979[/C][/ROW]
[ROW][C]38[/C][C]1.45[/C][C]1.40033[/C][C]1.42042[/C][C]-0.0200868[/C][C]0.0496701[/C][/ROW]
[ROW][C]39[/C][C]1.35[/C][C]1.33825[/C][C]1.38[/C][C]-0.0417535[/C][C]0.0117535[/C][/ROW]
[ROW][C]40[/C][C]1.35[/C][C]1.27602[/C][C]1.3475[/C][C]-0.0714757[/C][C]0.0739757[/C][/ROW]
[ROW][C]41[/C][C]1.29[/C][C]1.27047[/C][C]1.32792[/C][C]-0.0574479[/C][C]0.0195312[/C][/ROW]
[ROW][C]42[/C][C]1.29[/C][C]1.30533[/C][C]1.30917[/C][C]-0.00383681[/C][C]-0.0153299[/C][/ROW]
[ROW][C]43[/C][C]1.26[/C][C]1.37061[/C][C]1.28833[/C][C]0.0822743[/C][C]-0.110608[/C][/ROW]
[ROW][C]44[/C][C]1.3[/C][C]1.40089[/C][C]1.26958[/C][C]0.131302[/C][C]-0.100885[/C][/ROW]
[ROW][C]45[/C][C]1.3[/C][C]1.39137[/C][C]1.2525[/C][C]0.138872[/C][C]-0.0913715[/C][/ROW]
[ROW][C]46[/C][C]1.16[/C][C]1.19818[/C][C]1.23583[/C][C]-0.0376562[/C][C]-0.0381771[/C][/ROW]
[ROW][C]47[/C][C]1.24[/C][C]1.18554[/C][C]1.22083[/C][C]-0.0352951[/C][C]0.0544618[/C][/ROW]
[ROW][C]48[/C][C]1.15[/C][C]1.16505[/C][C]1.21125[/C][C]-0.0461979[/C][C]-0.0150521[/C][/ROW]
[ROW][C]49[/C][C]1.21[/C][C]1.16755[/C][C]1.20625[/C][C]-0.0386979[/C][C]0.0424479[/C][/ROW]
[ROW][C]50[/C][C]1.22[/C][C]1.18283[/C][C]1.20292[/C][C]-0.0200868[/C][C]0.0371701[/C][/ROW]
[ROW][C]51[/C][C]1.17[/C][C]1.16241[/C][C]1.20417[/C][C]-0.0417535[/C][C]0.00758681[/C][/ROW]
[ROW][C]52[/C][C]1.13[/C][C]1.14102[/C][C]1.2125[/C][C]-0.0714757[/C][C]-0.0110243[/C][/ROW]
[ROW][C]53[/C][C]1.15[/C][C]1.16089[/C][C]1.21833[/C][C]-0.0574479[/C][C]-0.0108854[/C][/ROW]
[ROW][C]54[/C][C]1.2[/C][C]1.2195[/C][C]1.22333[/C][C]-0.00383681[/C][C]-0.0194965[/C][/ROW]
[ROW][C]55[/C][C]1.23[/C][C]1.31186[/C][C]1.22958[/C][C]0.0822743[/C][C]-0.0818576[/C][/ROW]
[ROW][C]56[/C][C]1.25[/C][C]1.36547[/C][C]1.23417[/C][C]0.131302[/C][C]-0.115469[/C][/ROW]
[ROW][C]57[/C][C]1.38[/C][C]1.38137[/C][C]1.2425[/C][C]0.138872[/C][C]-0.00137153[/C][/ROW]
[ROW][C]58[/C][C]1.28[/C][C]1.21443[/C][C]1.25208[/C][C]-0.0376562[/C][C]0.0655729[/C][/ROW]
[ROW][C]59[/C][C]1.26[/C][C]1.22387[/C][C]1.25917[/C][C]-0.0352951[/C][C]0.0361285[/C][/ROW]
[ROW][C]60[/C][C]1.25[/C][C]1.22297[/C][C]1.26917[/C][C]-0.0461979[/C][C]0.0270313[/C][/ROW]
[ROW][C]61[/C][C]1.26[/C][C]1.25005[/C][C]1.28875[/C][C]-0.0386979[/C][C]0.00994792[/C][/ROW]
[ROW][C]62[/C][C]1.28[/C][C]1.29533[/C][C]1.31542[/C][C]-0.0200868[/C][C]-0.0153299[/C][/ROW]
[ROW][C]63[/C][C]1.31[/C][C]1.28991[/C][C]1.33167[/C][C]-0.0417535[/C][C]0.0200868[/C][/ROW]
[ROW][C]64[/C][C]1.22[/C][C]1.26311[/C][C]1.33458[/C][C]-0.0714757[/C][C]-0.0431076[/C][/ROW]
[ROW][C]65[/C][C]1.23[/C][C]1.27839[/C][C]1.33583[/C][C]-0.0574479[/C][C]-0.0483854[/C][/ROW]
[ROW][C]66[/C][C]1.36[/C][C]1.332[/C][C]1.33583[/C][C]-0.00383681[/C][C]0.0280035[/C][/ROW]
[ROW][C]67[/C][C]1.54[/C][C]1.41477[/C][C]1.3325[/C][C]0.0822743[/C][C]0.125226[/C][/ROW]
[ROW][C]68[/C][C]1.58[/C][C]1.4588[/C][C]1.3275[/C][C]0.131302[/C][C]0.121198[/C][/ROW]
[ROW][C]69[/C][C]1.44[/C][C]1.45887[/C][C]1.32[/C][C]0.138872[/C][C]-0.0188715[/C][/ROW]
[ROW][C]70[/C][C]1.29[/C][C]1.27526[/C][C]1.31292[/C][C]-0.0376562[/C][C]0.0147396[/C][/ROW]
[ROW][C]71[/C][C]1.28[/C][C]1.27512[/C][C]1.31042[/C][C]-0.0352951[/C][C]0.00487847[/C][/ROW]
[ROW][C]72[/C][C]1.23[/C][C]1.26089[/C][C]1.30708[/C][C]-0.0461979[/C][C]-0.0308854[/C][/ROW]
[ROW][C]73[/C][C]1.2[/C][C]1.25922[/C][C]1.29792[/C][C]-0.0386979[/C][C]-0.0592187[/C][/ROW]
[ROW][C]74[/C][C]1.22[/C][C]1.2695[/C][C]1.28958[/C][C]-0.0200868[/C][C]-0.0494965[/C][/ROW]
[ROW][C]75[/C][C]1.19[/C][C]1.26158[/C][C]1.30333[/C][C]-0.0417535[/C][C]-0.0715799[/C][/ROW]
[ROW][C]76[/C][C]1.17[/C][C]1.26769[/C][C]1.33917[/C][C]-0.0714757[/C][C]-0.097691[/C][/ROW]
[ROW][C]77[/C][C]1.22[/C][C]1.3163[/C][C]1.37375[/C][C]-0.0574479[/C][C]-0.0963021[/C][/ROW]
[ROW][C]78[/C][C]1.29[/C][C]1.39866[/C][C]1.4025[/C][C]-0.00383681[/C][C]-0.108663[/C][/ROW]
[ROW][C]79[/C][C]1.39[/C][C]NA[/C][C]NA[/C][C]0.0822743[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]1.53[/C][C]NA[/C][C]NA[/C][C]0.131302[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]1.82[/C][C]NA[/C][C]NA[/C][C]0.138872[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]1.77[/C][C]NA[/C][C]NA[/C][C]-0.0376562[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]1.63[/C][C]NA[/C][C]NA[/C][C]-0.0352951[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]1.57[/C][C]NA[/C][C]NA[/C][C]-0.0461979[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232724&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232724&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	1.26	NA	NA	-0.0386979	NA
2	1.26	NA	NA	-0.0200868	NA
3	1.28	NA	NA	-0.0417535	NA
4	1.34	NA	NA	-0.0714757	NA
5	1.39	NA	NA	-0.0574479	NA
6	1.47	NA	NA	-0.00383681	NA
7	1.57	1.51561	1.43333	0.0822743	0.0543924
8	1.63	1.57922	1.44792	0.131302	0.0507812
9	1.72	1.60012	1.46125	0.138872	0.119878
10	1.43	1.43318	1.47083	-0.0376562	-0.00317708
11	1.35	1.44137	1.47667	-0.0352951	-0.0913715
12	1.41	1.43464	1.48083	-0.0461979	-0.0246354
13	1.44	1.44005	1.47875	-0.0386979	-5.20833e-05
14	1.43	1.44866	1.46875	-0.0200868	-0.0186632
15	1.43	1.4095	1.45125	-0.0417535	0.0205035
16	1.42	1.36644	1.43792	-0.0714757	0.053559
17	1.45	1.38297	1.44042	-0.0574479	0.0670313
18	1.51	1.44283	1.44667	-0.00383681	0.0671701
19	1.48	1.52936	1.44708	0.0822743	-0.0493576
20	1.48	1.57797	1.44667	0.131302	-0.0979687
21	1.45	1.58804	1.44917	0.138872	-0.138038
22	1.38	1.41526	1.45292	-0.0376562	-0.0352604
23	1.46	1.42304	1.45833	-0.0352951	0.0369618
24	1.45	1.41755	1.46375	-0.0461979	0.0324479
25	1.41	1.43464	1.47333	-0.0386979	-0.0246354
26	1.45	1.47366	1.49375	-0.0200868	-0.0236632
27	1.47	1.47866	1.52042	-0.0417535	-0.00866319
28	1.47	1.46602	1.5375	-0.0714757	0.00397569
29	1.53	1.4813	1.53875	-0.0574479	0.0486979
30	1.56	1.532	1.53583	-0.00383681	0.0280035
31	1.66	1.61811	1.53583	0.0822743	0.0418924
32	1.79	1.66797	1.53667	0.131302	0.122031
33	1.78	1.67054	1.53167	0.138872	0.109462
34	1.46	1.48401	1.52167	-0.0376562	-0.0240104
35	1.41	1.47137	1.50667	-0.0352951	-0.0613715
36	1.43	1.43922	1.48542	-0.0461979	-0.00921875
37	1.43	1.4188	1.4575	-0.0386979	0.0111979
38	1.45	1.40033	1.42042	-0.0200868	0.0496701
39	1.35	1.33825	1.38	-0.0417535	0.0117535
40	1.35	1.27602	1.3475	-0.0714757	0.0739757
41	1.29	1.27047	1.32792	-0.0574479	0.0195312
42	1.29	1.30533	1.30917	-0.00383681	-0.0153299
43	1.26	1.37061	1.28833	0.0822743	-0.110608
44	1.3	1.40089	1.26958	0.131302	-0.100885
45	1.3	1.39137	1.2525	0.138872	-0.0913715
46	1.16	1.19818	1.23583	-0.0376562	-0.0381771
47	1.24	1.18554	1.22083	-0.0352951	0.0544618
48	1.15	1.16505	1.21125	-0.0461979	-0.0150521
49	1.21	1.16755	1.20625	-0.0386979	0.0424479
50	1.22	1.18283	1.20292	-0.0200868	0.0371701
51	1.17	1.16241	1.20417	-0.0417535	0.00758681
52	1.13	1.14102	1.2125	-0.0714757	-0.0110243
53	1.15	1.16089	1.21833	-0.0574479	-0.0108854
54	1.2	1.2195	1.22333	-0.00383681	-0.0194965
55	1.23	1.31186	1.22958	0.0822743	-0.0818576
56	1.25	1.36547	1.23417	0.131302	-0.115469
57	1.38	1.38137	1.2425	0.138872	-0.00137153
58	1.28	1.21443	1.25208	-0.0376562	0.0655729
59	1.26	1.22387	1.25917	-0.0352951	0.0361285
60	1.25	1.22297	1.26917	-0.0461979	0.0270313
61	1.26	1.25005	1.28875	-0.0386979	0.00994792
62	1.28	1.29533	1.31542	-0.0200868	-0.0153299
63	1.31	1.28991	1.33167	-0.0417535	0.0200868
64	1.22	1.26311	1.33458	-0.0714757	-0.0431076
65	1.23	1.27839	1.33583	-0.0574479	-0.0483854
66	1.36	1.332	1.33583	-0.00383681	0.0280035
67	1.54	1.41477	1.3325	0.0822743	0.125226
68	1.58	1.4588	1.3275	0.131302	0.121198
69	1.44	1.45887	1.32	0.138872	-0.0188715
70	1.29	1.27526	1.31292	-0.0376562	0.0147396
71	1.28	1.27512	1.31042	-0.0352951	0.00487847
72	1.23	1.26089	1.30708	-0.0461979	-0.0308854
73	1.2	1.25922	1.29792	-0.0386979	-0.0592187
74	1.22	1.2695	1.28958	-0.0200868	-0.0494965
75	1.19	1.26158	1.30333	-0.0417535	-0.0715799
76	1.17	1.26769	1.33917	-0.0714757	-0.097691
77	1.22	1.3163	1.37375	-0.0574479	-0.0963021
78	1.29	1.39866	1.4025	-0.00383681	-0.108663
79	1.39	NA	NA	0.0822743	NA
80	1.53	NA	NA	0.131302	NA
81	1.82	NA	NA	0.138872	NA
82	1.77	NA	NA	-0.0376562	NA
83	1.63	NA	NA	-0.0352951	NA
84	1.57	NA	NA	-0.0461979	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