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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 27 May 2013 03:59:09 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/27/t1369641568vyxeyr4wvklrsq4.htm/, Retrieved Thu, 02 May 2024 09:59:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210741, Retrieved Thu, 02 May 2024 09:59:23 +0000

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Estimated Impact

145

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

-       [Classical Decomposition] [Eigen reeks] [2013-05-27 07:59:09] [bc2cf5f41ec5ca561b7a550898b8dd0d] [Current]

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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	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=210741&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=210741&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210741&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	122.27	NA	NA	0.945638114178078	NA
2	124.69	NA	NA	0.966007432747006	NA
3	147.56	NA	NA	1.07545006693329	NA
4	120.03	NA	NA	1.00123882422378	NA
5	136.01	NA	NA	1.00415766980854	NA
6	138.16	NA	NA	1.07255935002183	NA
7	122.87	130.688531370186	130.504166666667	1.00141271124308	0.940174311485379
8	112.22	114.544666766789	131.175	0.873220253606167	0.979705150554745
9	137.35	140.150764828109	131.502083333333	1.06576839906675	0.980016057482498
10	139.08	141.848451350552	132.024583333333	1.07440938474629	0.980483034363838
11	139.64	133.266012204856	132.600416666667	1.00501955842162	1.04782905775964
12	121.12	121.784316013538	133.080416666667	0.915118235003558	0.994545143124471
13	132.37	126.747028570335	134.033333333333	0.945638114178078	1.04436373375447
14	130.69	130.483051475205	135.074583333333	0.966007432747006	1.0015860184327
15	149.41	145.809520074816	135.58	1.07545006693329	1.02469303734994
16	130.72	136.468434558858	136.299583333333	1.00123882422378	0.957877185464608
17	139.14	137.678384511333	137.108333333333	1.00415766980854	1.01061615804002
18	146.55	147.348203505999	137.38	1.07255935002183	0.994582875888495
19	137.35	138.018037905893	137.823333333333	1.00141271124308	0.995159778272256
20	122.73	121.062528276414	138.639166666667	0.873220253606167	1.01377364034376
21	138.97	148.028125507711	138.893333333333	1.06576839906675	0.938808078014613
22	154.73	150.000980227891	139.6125	1.07440938474629	1.03152659245909
23	143.4	141.503822518719	140.797083333333	1.00501955842162	1.01340018557471
24	123.88	129.336329247905	141.332916666667	0.915118235003558	0.957812864493421
25	140.25	134.486682519002	142.217916666667	0.945638114178078	1.04285418729237
26	142.39	137.912453639223	142.765416666667	0.966007432747006	1.03246658472548
27	143.81	154.131711176101	143.318333333333	1.07545006693329	0.933033175993819
28	153.58	143.856325533099	143.678333333333	1.00123882422378	1.06759295728476
29	144.71	143.019248117627	142.427083333333	1.00415766980854	1.01182184848981
30	153.84	151.006077789303	140.790416666667	1.07255935002183	1.01876694138531
31	151.3	138.850462222114	138.654583333333	1.00141271124308	1.08966147882152
32	121.92	118.455601977628	135.65375	0.873220253606167	1.02924638399986
33	153.05	141.696573076922	132.9525	1.06576839906675	1.08012492240666
34	149.29	139.483855362956	129.82375	1.07440938474629	1.07030307996239
35	118.81	126.820486770179	126.187083333333	1.00501955842162	0.936836019367317
36	109.19	112.487096045167	122.920833333333	0.915118235003558	0.970689117586939
37	103.68	113.256712839823	119.7675	0.945638114178078	0.915442426327814
38	106.94	113.082842592849	117.062083333333	0.966007432747006	0.945678385403111
39	114.43	123.41820157707	114.759583333333	1.07545006693329	0.927172803831067
40	107.87	112.538409477066	112.399166666667	1.00123882422378	0.95851718983093
41	103.14	111.848938849682	111.385833333333	1.00415766980854	0.922136598350864
42	117.02	120.106536714632	111.98125	1.07255935002183	0.97430167583663
43	112.44	113.006920932004	112.8475	1.00141271124308	0.994983307860011
44	95.85	99.268769955266	113.68125	0.873220253606167	0.965560468243873
45	123.86	122.82891985211	115.249166666667	1.06576839906675	1.00839444122061
46	121.83	126.051499700742	117.321666666667	1.07440938474629	0.966509722527978
47	121.95	119.862820118856	119.264166666667	1.00501955842162	1.01741307170209
48	120.34	111.246348238208	121.565	0.915118235003558	1.08174337320557
49	113.32	116.920666516382	123.642083333333	0.945638114178078	0.969204190981262
50	117.31	121.181607407142	125.445833333333	0.966007432747006	0.968051196134621
51	141.69	137.042361508337	127.427916666667	1.07545006693329	1.03391388210557
52	130.35	129.473947005968	129.31375	1.00123882422378	1.00676624922844
53	127.28	131.609924993456	131.065	1.00415766980854	0.967100315620789
54	148.1	141.988535053994	132.382916666667	1.07255935002183	1.04304196070254
55	131.21	134.261071217546	134.071666666667	1.00141271124308	0.977275086591541
56	120.37	119.300078731219	136.620833333333	0.873220253606167	1.00896831988847
57	146.91	148.407361429712	139.249166666667	1.06576839906675	0.989910463906325
58	144.04	151.87179556908	141.35375	1.07440938474629	0.94843153371741
59	141.77	144.401628912168	143.680416666667	1.00501955842162	0.981775628626955
60	132.15	133.153516185664	145.504166666667	0.915118235003558	0.992463464620309
61	142.04	138.522981203018	146.48625	0.945638114178078	1.02538942467479
62	149.77	142.709888052103	147.731666666667	0.966007432747006	1.04947177833479
63	172.31	159.776927819112	148.5675	1.07545006693329	1.07844106375031
64	150.24	149.269690109403	149.085	1.00123882422378	1.00650038122198
65	163.23	150.362151078102	149.739583333333	1.00415766980854	1.08557904252922
66	155.92	161.314266942471	150.40125	1.07255935002183	0.966560509217732
67	146.96	NA	NA	1.00141271124308	NA
68	134.51	NA	NA	0.873220253606167	NA
69	152.83	NA	NA	1.06576839906675	NA
70	150.54	NA	NA	1.07440938474629	NA
71	150.98	NA	NA	1.00501955842162	NA
72	138.82	NA	NA	0.915118235003558	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 122.27 & NA & NA & 0.945638114178078 & NA \tabularnewline
2 & 124.69 & NA & NA & 0.966007432747006 & NA \tabularnewline
3 & 147.56 & NA & NA & 1.07545006693329 & NA \tabularnewline
4 & 120.03 & NA & NA & 1.00123882422378 & NA \tabularnewline
5 & 136.01 & NA & NA & 1.00415766980854 & NA \tabularnewline
6 & 138.16 & NA & NA & 1.07255935002183 & NA \tabularnewline
7 & 122.87 & 130.688531370186 & 130.504166666667 & 1.00141271124308 & 0.940174311485379 \tabularnewline
8 & 112.22 & 114.544666766789 & 131.175 & 0.873220253606167 & 0.979705150554745 \tabularnewline
9 & 137.35 & 140.150764828109 & 131.502083333333 & 1.06576839906675 & 0.980016057482498 \tabularnewline
10 & 139.08 & 141.848451350552 & 132.024583333333 & 1.07440938474629 & 0.980483034363838 \tabularnewline
11 & 139.64 & 133.266012204856 & 132.600416666667 & 1.00501955842162 & 1.04782905775964 \tabularnewline
12 & 121.12 & 121.784316013538 & 133.080416666667 & 0.915118235003558 & 0.994545143124471 \tabularnewline
13 & 132.37 & 126.747028570335 & 134.033333333333 & 0.945638114178078 & 1.04436373375447 \tabularnewline
14 & 130.69 & 130.483051475205 & 135.074583333333 & 0.966007432747006 & 1.0015860184327 \tabularnewline
15 & 149.41 & 145.809520074816 & 135.58 & 1.07545006693329 & 1.02469303734994 \tabularnewline
16 & 130.72 & 136.468434558858 & 136.299583333333 & 1.00123882422378 & 0.957877185464608 \tabularnewline
17 & 139.14 & 137.678384511333 & 137.108333333333 & 1.00415766980854 & 1.01061615804002 \tabularnewline
18 & 146.55 & 147.348203505999 & 137.38 & 1.07255935002183 & 0.994582875888495 \tabularnewline
19 & 137.35 & 138.018037905893 & 137.823333333333 & 1.00141271124308 & 0.995159778272256 \tabularnewline
20 & 122.73 & 121.062528276414 & 138.639166666667 & 0.873220253606167 & 1.01377364034376 \tabularnewline
21 & 138.97 & 148.028125507711 & 138.893333333333 & 1.06576839906675 & 0.938808078014613 \tabularnewline
22 & 154.73 & 150.000980227891 & 139.6125 & 1.07440938474629 & 1.03152659245909 \tabularnewline
23 & 143.4 & 141.503822518719 & 140.797083333333 & 1.00501955842162 & 1.01340018557471 \tabularnewline
24 & 123.88 & 129.336329247905 & 141.332916666667 & 0.915118235003558 & 0.957812864493421 \tabularnewline
25 & 140.25 & 134.486682519002 & 142.217916666667 & 0.945638114178078 & 1.04285418729237 \tabularnewline
26 & 142.39 & 137.912453639223 & 142.765416666667 & 0.966007432747006 & 1.03246658472548 \tabularnewline
27 & 143.81 & 154.131711176101 & 143.318333333333 & 1.07545006693329 & 0.933033175993819 \tabularnewline
28 & 153.58 & 143.856325533099 & 143.678333333333 & 1.00123882422378 & 1.06759295728476 \tabularnewline
29 & 144.71 & 143.019248117627 & 142.427083333333 & 1.00415766980854 & 1.01182184848981 \tabularnewline
30 & 153.84 & 151.006077789303 & 140.790416666667 & 1.07255935002183 & 1.01876694138531 \tabularnewline
31 & 151.3 & 138.850462222114 & 138.654583333333 & 1.00141271124308 & 1.08966147882152 \tabularnewline
32 & 121.92 & 118.455601977628 & 135.65375 & 0.873220253606167 & 1.02924638399986 \tabularnewline
33 & 153.05 & 141.696573076922 & 132.9525 & 1.06576839906675 & 1.08012492240666 \tabularnewline
34 & 149.29 & 139.483855362956 & 129.82375 & 1.07440938474629 & 1.07030307996239 \tabularnewline
35 & 118.81 & 126.820486770179 & 126.187083333333 & 1.00501955842162 & 0.936836019367317 \tabularnewline
36 & 109.19 & 112.487096045167 & 122.920833333333 & 0.915118235003558 & 0.970689117586939 \tabularnewline
37 & 103.68 & 113.256712839823 & 119.7675 & 0.945638114178078 & 0.915442426327814 \tabularnewline
38 & 106.94 & 113.082842592849 & 117.062083333333 & 0.966007432747006 & 0.945678385403111 \tabularnewline
39 & 114.43 & 123.41820157707 & 114.759583333333 & 1.07545006693329 & 0.927172803831067 \tabularnewline
40 & 107.87 & 112.538409477066 & 112.399166666667 & 1.00123882422378 & 0.95851718983093 \tabularnewline
41 & 103.14 & 111.848938849682 & 111.385833333333 & 1.00415766980854 & 0.922136598350864 \tabularnewline
42 & 117.02 & 120.106536714632 & 111.98125 & 1.07255935002183 & 0.97430167583663 \tabularnewline
43 & 112.44 & 113.006920932004 & 112.8475 & 1.00141271124308 & 0.994983307860011 \tabularnewline
44 & 95.85 & 99.268769955266 & 113.68125 & 0.873220253606167 & 0.965560468243873 \tabularnewline
45 & 123.86 & 122.82891985211 & 115.249166666667 & 1.06576839906675 & 1.00839444122061 \tabularnewline
46 & 121.83 & 126.051499700742 & 117.321666666667 & 1.07440938474629 & 0.966509722527978 \tabularnewline
47 & 121.95 & 119.862820118856 & 119.264166666667 & 1.00501955842162 & 1.01741307170209 \tabularnewline
48 & 120.34 & 111.246348238208 & 121.565 & 0.915118235003558 & 1.08174337320557 \tabularnewline
49 & 113.32 & 116.920666516382 & 123.642083333333 & 0.945638114178078 & 0.969204190981262 \tabularnewline
50 & 117.31 & 121.181607407142 & 125.445833333333 & 0.966007432747006 & 0.968051196134621 \tabularnewline
51 & 141.69 & 137.042361508337 & 127.427916666667 & 1.07545006693329 & 1.03391388210557 \tabularnewline
52 & 130.35 & 129.473947005968 & 129.31375 & 1.00123882422378 & 1.00676624922844 \tabularnewline
53 & 127.28 & 131.609924993456 & 131.065 & 1.00415766980854 & 0.967100315620789 \tabularnewline
54 & 148.1 & 141.988535053994 & 132.382916666667 & 1.07255935002183 & 1.04304196070254 \tabularnewline
55 & 131.21 & 134.261071217546 & 134.071666666667 & 1.00141271124308 & 0.977275086591541 \tabularnewline
56 & 120.37 & 119.300078731219 & 136.620833333333 & 0.873220253606167 & 1.00896831988847 \tabularnewline
57 & 146.91 & 148.407361429712 & 139.249166666667 & 1.06576839906675 & 0.989910463906325 \tabularnewline
58 & 144.04 & 151.87179556908 & 141.35375 & 1.07440938474629 & 0.94843153371741 \tabularnewline
59 & 141.77 & 144.401628912168 & 143.680416666667 & 1.00501955842162 & 0.981775628626955 \tabularnewline
60 & 132.15 & 133.153516185664 & 145.504166666667 & 0.915118235003558 & 0.992463464620309 \tabularnewline
61 & 142.04 & 138.522981203018 & 146.48625 & 0.945638114178078 & 1.02538942467479 \tabularnewline
62 & 149.77 & 142.709888052103 & 147.731666666667 & 0.966007432747006 & 1.04947177833479 \tabularnewline
63 & 172.31 & 159.776927819112 & 148.5675 & 1.07545006693329 & 1.07844106375031 \tabularnewline
64 & 150.24 & 149.269690109403 & 149.085 & 1.00123882422378 & 1.00650038122198 \tabularnewline
65 & 163.23 & 150.362151078102 & 149.739583333333 & 1.00415766980854 & 1.08557904252922 \tabularnewline
66 & 155.92 & 161.314266942471 & 150.40125 & 1.07255935002183 & 0.966560509217732 \tabularnewline
67 & 146.96 & NA & NA & 1.00141271124308 & NA \tabularnewline
68 & 134.51 & NA & NA & 0.873220253606167 & NA \tabularnewline
69 & 152.83 & NA & NA & 1.06576839906675 & NA \tabularnewline
70 & 150.54 & NA & NA & 1.07440938474629 & NA \tabularnewline
71 & 150.98 & NA & NA & 1.00501955842162 & NA \tabularnewline
72 & 138.82 & NA & NA & 0.915118235003558 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210741&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]122.27[/C][C]NA[/C][C]NA[/C][C]0.945638114178078[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]124.69[/C][C]NA[/C][C]NA[/C][C]0.966007432747006[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]147.56[/C][C]NA[/C][C]NA[/C][C]1.07545006693329[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]120.03[/C][C]NA[/C][C]NA[/C][C]1.00123882422378[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]136.01[/C][C]NA[/C][C]NA[/C][C]1.00415766980854[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]138.16[/C][C]NA[/C][C]NA[/C][C]1.07255935002183[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]122.87[/C][C]130.688531370186[/C][C]130.504166666667[/C][C]1.00141271124308[/C][C]0.940174311485379[/C][/ROW]
[ROW][C]8[/C][C]112.22[/C][C]114.544666766789[/C][C]131.175[/C][C]0.873220253606167[/C][C]0.979705150554745[/C][/ROW]
[ROW][C]9[/C][C]137.35[/C][C]140.150764828109[/C][C]131.502083333333[/C][C]1.06576839906675[/C][C]0.980016057482498[/C][/ROW]
[ROW][C]10[/C][C]139.08[/C][C]141.848451350552[/C][C]132.024583333333[/C][C]1.07440938474629[/C][C]0.980483034363838[/C][/ROW]
[ROW][C]11[/C][C]139.64[/C][C]133.266012204856[/C][C]132.600416666667[/C][C]1.00501955842162[/C][C]1.04782905775964[/C][/ROW]
[ROW][C]12[/C][C]121.12[/C][C]121.784316013538[/C][C]133.080416666667[/C][C]0.915118235003558[/C][C]0.994545143124471[/C][/ROW]
[ROW][C]13[/C][C]132.37[/C][C]126.747028570335[/C][C]134.033333333333[/C][C]0.945638114178078[/C][C]1.04436373375447[/C][/ROW]
[ROW][C]14[/C][C]130.69[/C][C]130.483051475205[/C][C]135.074583333333[/C][C]0.966007432747006[/C][C]1.0015860184327[/C][/ROW]
[ROW][C]15[/C][C]149.41[/C][C]145.809520074816[/C][C]135.58[/C][C]1.07545006693329[/C][C]1.02469303734994[/C][/ROW]
[ROW][C]16[/C][C]130.72[/C][C]136.468434558858[/C][C]136.299583333333[/C][C]1.00123882422378[/C][C]0.957877185464608[/C][/ROW]
[ROW][C]17[/C][C]139.14[/C][C]137.678384511333[/C][C]137.108333333333[/C][C]1.00415766980854[/C][C]1.01061615804002[/C][/ROW]
[ROW][C]18[/C][C]146.55[/C][C]147.348203505999[/C][C]137.38[/C][C]1.07255935002183[/C][C]0.994582875888495[/C][/ROW]
[ROW][C]19[/C][C]137.35[/C][C]138.018037905893[/C][C]137.823333333333[/C][C]1.00141271124308[/C][C]0.995159778272256[/C][/ROW]
[ROW][C]20[/C][C]122.73[/C][C]121.062528276414[/C][C]138.639166666667[/C][C]0.873220253606167[/C][C]1.01377364034376[/C][/ROW]
[ROW][C]21[/C][C]138.97[/C][C]148.028125507711[/C][C]138.893333333333[/C][C]1.06576839906675[/C][C]0.938808078014613[/C][/ROW]
[ROW][C]22[/C][C]154.73[/C][C]150.000980227891[/C][C]139.6125[/C][C]1.07440938474629[/C][C]1.03152659245909[/C][/ROW]
[ROW][C]23[/C][C]143.4[/C][C]141.503822518719[/C][C]140.797083333333[/C][C]1.00501955842162[/C][C]1.01340018557471[/C][/ROW]
[ROW][C]24[/C][C]123.88[/C][C]129.336329247905[/C][C]141.332916666667[/C][C]0.915118235003558[/C][C]0.957812864493421[/C][/ROW]
[ROW][C]25[/C][C]140.25[/C][C]134.486682519002[/C][C]142.217916666667[/C][C]0.945638114178078[/C][C]1.04285418729237[/C][/ROW]
[ROW][C]26[/C][C]142.39[/C][C]137.912453639223[/C][C]142.765416666667[/C][C]0.966007432747006[/C][C]1.03246658472548[/C][/ROW]
[ROW][C]27[/C][C]143.81[/C][C]154.131711176101[/C][C]143.318333333333[/C][C]1.07545006693329[/C][C]0.933033175993819[/C][/ROW]
[ROW][C]28[/C][C]153.58[/C][C]143.856325533099[/C][C]143.678333333333[/C][C]1.00123882422378[/C][C]1.06759295728476[/C][/ROW]
[ROW][C]29[/C][C]144.71[/C][C]143.019248117627[/C][C]142.427083333333[/C][C]1.00415766980854[/C][C]1.01182184848981[/C][/ROW]
[ROW][C]30[/C][C]153.84[/C][C]151.006077789303[/C][C]140.790416666667[/C][C]1.07255935002183[/C][C]1.01876694138531[/C][/ROW]
[ROW][C]31[/C][C]151.3[/C][C]138.850462222114[/C][C]138.654583333333[/C][C]1.00141271124308[/C][C]1.08966147882152[/C][/ROW]
[ROW][C]32[/C][C]121.92[/C][C]118.455601977628[/C][C]135.65375[/C][C]0.873220253606167[/C][C]1.02924638399986[/C][/ROW]
[ROW][C]33[/C][C]153.05[/C][C]141.696573076922[/C][C]132.9525[/C][C]1.06576839906675[/C][C]1.08012492240666[/C][/ROW]
[ROW][C]34[/C][C]149.29[/C][C]139.483855362956[/C][C]129.82375[/C][C]1.07440938474629[/C][C]1.07030307996239[/C][/ROW]
[ROW][C]35[/C][C]118.81[/C][C]126.820486770179[/C][C]126.187083333333[/C][C]1.00501955842162[/C][C]0.936836019367317[/C][/ROW]
[ROW][C]36[/C][C]109.19[/C][C]112.487096045167[/C][C]122.920833333333[/C][C]0.915118235003558[/C][C]0.970689117586939[/C][/ROW]
[ROW][C]37[/C][C]103.68[/C][C]113.256712839823[/C][C]119.7675[/C][C]0.945638114178078[/C][C]0.915442426327814[/C][/ROW]
[ROW][C]38[/C][C]106.94[/C][C]113.082842592849[/C][C]117.062083333333[/C][C]0.966007432747006[/C][C]0.945678385403111[/C][/ROW]
[ROW][C]39[/C][C]114.43[/C][C]123.41820157707[/C][C]114.759583333333[/C][C]1.07545006693329[/C][C]0.927172803831067[/C][/ROW]
[ROW][C]40[/C][C]107.87[/C][C]112.538409477066[/C][C]112.399166666667[/C][C]1.00123882422378[/C][C]0.95851718983093[/C][/ROW]
[ROW][C]41[/C][C]103.14[/C][C]111.848938849682[/C][C]111.385833333333[/C][C]1.00415766980854[/C][C]0.922136598350864[/C][/ROW]
[ROW][C]42[/C][C]117.02[/C][C]120.106536714632[/C][C]111.98125[/C][C]1.07255935002183[/C][C]0.97430167583663[/C][/ROW]
[ROW][C]43[/C][C]112.44[/C][C]113.006920932004[/C][C]112.8475[/C][C]1.00141271124308[/C][C]0.994983307860011[/C][/ROW]
[ROW][C]44[/C][C]95.85[/C][C]99.268769955266[/C][C]113.68125[/C][C]0.873220253606167[/C][C]0.965560468243873[/C][/ROW]
[ROW][C]45[/C][C]123.86[/C][C]122.82891985211[/C][C]115.249166666667[/C][C]1.06576839906675[/C][C]1.00839444122061[/C][/ROW]
[ROW][C]46[/C][C]121.83[/C][C]126.051499700742[/C][C]117.321666666667[/C][C]1.07440938474629[/C][C]0.966509722527978[/C][/ROW]
[ROW][C]47[/C][C]121.95[/C][C]119.862820118856[/C][C]119.264166666667[/C][C]1.00501955842162[/C][C]1.01741307170209[/C][/ROW]
[ROW][C]48[/C][C]120.34[/C][C]111.246348238208[/C][C]121.565[/C][C]0.915118235003558[/C][C]1.08174337320557[/C][/ROW]
[ROW][C]49[/C][C]113.32[/C][C]116.920666516382[/C][C]123.642083333333[/C][C]0.945638114178078[/C][C]0.969204190981262[/C][/ROW]
[ROW][C]50[/C][C]117.31[/C][C]121.181607407142[/C][C]125.445833333333[/C][C]0.966007432747006[/C][C]0.968051196134621[/C][/ROW]
[ROW][C]51[/C][C]141.69[/C][C]137.042361508337[/C][C]127.427916666667[/C][C]1.07545006693329[/C][C]1.03391388210557[/C][/ROW]
[ROW][C]52[/C][C]130.35[/C][C]129.473947005968[/C][C]129.31375[/C][C]1.00123882422378[/C][C]1.00676624922844[/C][/ROW]
[ROW][C]53[/C][C]127.28[/C][C]131.609924993456[/C][C]131.065[/C][C]1.00415766980854[/C][C]0.967100315620789[/C][/ROW]
[ROW][C]54[/C][C]148.1[/C][C]141.988535053994[/C][C]132.382916666667[/C][C]1.07255935002183[/C][C]1.04304196070254[/C][/ROW]
[ROW][C]55[/C][C]131.21[/C][C]134.261071217546[/C][C]134.071666666667[/C][C]1.00141271124308[/C][C]0.977275086591541[/C][/ROW]
[ROW][C]56[/C][C]120.37[/C][C]119.300078731219[/C][C]136.620833333333[/C][C]0.873220253606167[/C][C]1.00896831988847[/C][/ROW]
[ROW][C]57[/C][C]146.91[/C][C]148.407361429712[/C][C]139.249166666667[/C][C]1.06576839906675[/C][C]0.989910463906325[/C][/ROW]
[ROW][C]58[/C][C]144.04[/C][C]151.87179556908[/C][C]141.35375[/C][C]1.07440938474629[/C][C]0.94843153371741[/C][/ROW]
[ROW][C]59[/C][C]141.77[/C][C]144.401628912168[/C][C]143.680416666667[/C][C]1.00501955842162[/C][C]0.981775628626955[/C][/ROW]
[ROW][C]60[/C][C]132.15[/C][C]133.153516185664[/C][C]145.504166666667[/C][C]0.915118235003558[/C][C]0.992463464620309[/C][/ROW]
[ROW][C]61[/C][C]142.04[/C][C]138.522981203018[/C][C]146.48625[/C][C]0.945638114178078[/C][C]1.02538942467479[/C][/ROW]
[ROW][C]62[/C][C]149.77[/C][C]142.709888052103[/C][C]147.731666666667[/C][C]0.966007432747006[/C][C]1.04947177833479[/C][/ROW]
[ROW][C]63[/C][C]172.31[/C][C]159.776927819112[/C][C]148.5675[/C][C]1.07545006693329[/C][C]1.07844106375031[/C][/ROW]
[ROW][C]64[/C][C]150.24[/C][C]149.269690109403[/C][C]149.085[/C][C]1.00123882422378[/C][C]1.00650038122198[/C][/ROW]
[ROW][C]65[/C][C]163.23[/C][C]150.362151078102[/C][C]149.739583333333[/C][C]1.00415766980854[/C][C]1.08557904252922[/C][/ROW]
[ROW][C]66[/C][C]155.92[/C][C]161.314266942471[/C][C]150.40125[/C][C]1.07255935002183[/C][C]0.966560509217732[/C][/ROW]
[ROW][C]67[/C][C]146.96[/C][C]NA[/C][C]NA[/C][C]1.00141271124308[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]134.51[/C][C]NA[/C][C]NA[/C][C]0.873220253606167[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]152.83[/C][C]NA[/C][C]NA[/C][C]1.06576839906675[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]150.54[/C][C]NA[/C][C]NA[/C][C]1.07440938474629[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]150.98[/C][C]NA[/C][C]NA[/C][C]1.00501955842162[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]138.82[/C][C]NA[/C][C]NA[/C][C]0.915118235003558[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210741&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210741&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	122.27	NA	NA	0.945638114178078	NA
2	124.69	NA	NA	0.966007432747006	NA
3	147.56	NA	NA	1.07545006693329	NA
4	120.03	NA	NA	1.00123882422378	NA
5	136.01	NA	NA	1.00415766980854	NA
6	138.16	NA	NA	1.07255935002183	NA
7	122.87	130.688531370186	130.504166666667	1.00141271124308	0.940174311485379
8	112.22	114.544666766789	131.175	0.873220253606167	0.979705150554745
9	137.35	140.150764828109	131.502083333333	1.06576839906675	0.980016057482498
10	139.08	141.848451350552	132.024583333333	1.07440938474629	0.980483034363838
11	139.64	133.266012204856	132.600416666667	1.00501955842162	1.04782905775964
12	121.12	121.784316013538	133.080416666667	0.915118235003558	0.994545143124471
13	132.37	126.747028570335	134.033333333333	0.945638114178078	1.04436373375447
14	130.69	130.483051475205	135.074583333333	0.966007432747006	1.0015860184327
15	149.41	145.809520074816	135.58	1.07545006693329	1.02469303734994
16	130.72	136.468434558858	136.299583333333	1.00123882422378	0.957877185464608
17	139.14	137.678384511333	137.108333333333	1.00415766980854	1.01061615804002
18	146.55	147.348203505999	137.38	1.07255935002183	0.994582875888495
19	137.35	138.018037905893	137.823333333333	1.00141271124308	0.995159778272256
20	122.73	121.062528276414	138.639166666667	0.873220253606167	1.01377364034376
21	138.97	148.028125507711	138.893333333333	1.06576839906675	0.938808078014613
22	154.73	150.000980227891	139.6125	1.07440938474629	1.03152659245909
23	143.4	141.503822518719	140.797083333333	1.00501955842162	1.01340018557471
24	123.88	129.336329247905	141.332916666667	0.915118235003558	0.957812864493421
25	140.25	134.486682519002	142.217916666667	0.945638114178078	1.04285418729237
26	142.39	137.912453639223	142.765416666667	0.966007432747006	1.03246658472548
27	143.81	154.131711176101	143.318333333333	1.07545006693329	0.933033175993819
28	153.58	143.856325533099	143.678333333333	1.00123882422378	1.06759295728476
29	144.71	143.019248117627	142.427083333333	1.00415766980854	1.01182184848981
30	153.84	151.006077789303	140.790416666667	1.07255935002183	1.01876694138531
31	151.3	138.850462222114	138.654583333333	1.00141271124308	1.08966147882152
32	121.92	118.455601977628	135.65375	0.873220253606167	1.02924638399986
33	153.05	141.696573076922	132.9525	1.06576839906675	1.08012492240666
34	149.29	139.483855362956	129.82375	1.07440938474629	1.07030307996239
35	118.81	126.820486770179	126.187083333333	1.00501955842162	0.936836019367317
36	109.19	112.487096045167	122.920833333333	0.915118235003558	0.970689117586939
37	103.68	113.256712839823	119.7675	0.945638114178078	0.915442426327814
38	106.94	113.082842592849	117.062083333333	0.966007432747006	0.945678385403111
39	114.43	123.41820157707	114.759583333333	1.07545006693329	0.927172803831067
40	107.87	112.538409477066	112.399166666667	1.00123882422378	0.95851718983093
41	103.14	111.848938849682	111.385833333333	1.00415766980854	0.922136598350864
42	117.02	120.106536714632	111.98125	1.07255935002183	0.97430167583663
43	112.44	113.006920932004	112.8475	1.00141271124308	0.994983307860011
44	95.85	99.268769955266	113.68125	0.873220253606167	0.965560468243873
45	123.86	122.82891985211	115.249166666667	1.06576839906675	1.00839444122061
46	121.83	126.051499700742	117.321666666667	1.07440938474629	0.966509722527978
47	121.95	119.862820118856	119.264166666667	1.00501955842162	1.01741307170209
48	120.34	111.246348238208	121.565	0.915118235003558	1.08174337320557
49	113.32	116.920666516382	123.642083333333	0.945638114178078	0.969204190981262
50	117.31	121.181607407142	125.445833333333	0.966007432747006	0.968051196134621
51	141.69	137.042361508337	127.427916666667	1.07545006693329	1.03391388210557
52	130.35	129.473947005968	129.31375	1.00123882422378	1.00676624922844
53	127.28	131.609924993456	131.065	1.00415766980854	0.967100315620789
54	148.1	141.988535053994	132.382916666667	1.07255935002183	1.04304196070254
55	131.21	134.261071217546	134.071666666667	1.00141271124308	0.977275086591541
56	120.37	119.300078731219	136.620833333333	0.873220253606167	1.00896831988847
57	146.91	148.407361429712	139.249166666667	1.06576839906675	0.989910463906325
58	144.04	151.87179556908	141.35375	1.07440938474629	0.94843153371741
59	141.77	144.401628912168	143.680416666667	1.00501955842162	0.981775628626955
60	132.15	133.153516185664	145.504166666667	0.915118235003558	0.992463464620309
61	142.04	138.522981203018	146.48625	0.945638114178078	1.02538942467479
62	149.77	142.709888052103	147.731666666667	0.966007432747006	1.04947177833479
63	172.31	159.776927819112	148.5675	1.07545006693329	1.07844106375031
64	150.24	149.269690109403	149.085	1.00123882422378	1.00650038122198
65	163.23	150.362151078102	149.739583333333	1.00415766980854	1.08557904252922
66	155.92	161.314266942471	150.40125	1.07255935002183	0.966560509217732
67	146.96	NA	NA	1.00141271124308	NA
68	134.51	NA	NA	0.873220253606167	NA
69	152.83	NA	NA	1.06576839906675	NA
70	150.54	NA	NA	1.07440938474629	NA
71	150.98	NA	NA	1.00501955842162	NA
72	138.82	NA	NA	0.915118235003558	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 <- 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