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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Tue, 15 Jan 2013 20:34:39 -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/2013/Jan/15/t1358300475xuvpgwmx2uph7jm.htm/, Retrieved Sun, 28 Apr 2024 07:42:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205592, Retrieved Sun, 28 Apr 2024 07:42:23 +0000

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

-       [Classical Decomposition] [Gemiddelde prijs ...] [2013-01-16 01:34:39] [d41d8cd98f00b204e9800998ecf8427e] [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	3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205592&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]3 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=205592&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205592&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	3 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	434.49	NA	NA	-0.272131944444443	NA
2	434.43	NA	NA	-0.669131944444423	NA
3	434.07	NA	NA	0.075701388888847	NA
4	434.52	NA	NA	0.37995138888886	NA
5	433.52	NA	NA	0.376618055555519	NA
6	433.52	NA	NA	-0.381798611111123	NA
7	433.52	433.072701388889	433.66625	-0.593548611111107	0.447298611111137
8	433.26	432.867118055556	433.435416666667	-0.568298611111102	0.392881944444468
9	433.63	433.230701388889	433.18625	0.0444513888889266	0.399298611111078
10	434.67	433.969868055556	433.050833333333	0.919034722222243	0.700131944444422
11	432.87	433.672868055556	433.05625	0.616618055555596	-0.802868055555564
12	432.49	433.204201388889	433.131666666667	0.072534722222206	-0.714201388888853
13	432.5	432.952868055556	433.225	-0.272131944444443	-0.452868055555598
14	430.88	432.698368055556	433.3675	-0.669131944444423	-1.8183680555556
15	431.64	433.600701388889	433.525	0.075701388888847	-1.96070138888888
16	433.7	434.058284722222	433.678333333333	0.37995138888886	-0.358284722222152
17	434.47	434.269534722222	433.892916666667	0.376618055555519	0.20046527777788
18	434.38	433.794451388889	434.17625	-0.381798611111123	0.585548611111221
19	434.9	433.881451388889	434.475	-0.593548611111107	1.01854861111116
20	435.3	434.268784722222	434.837083333333	-0.568298611111102	1.0312152777779
21	435.37	435.347784722222	435.303333333333	0.0444513888889266	0.0222152777777751
22	436.61	436.685284722222	435.76625	0.919034722222243	-0.0752847222221931
23	436.08	436.727034722222	436.110416666667	0.616618055555596	-0.647034722222202
24	436.08	436.473784722222	436.40125	0.072534722222206	-0.393784722222165
25	436.08	436.419951388889	436.692083333333	-0.272131944444443	-0.339951388888835
26	435.99	436.282951388889	436.952083333333	-0.669131944444423	-0.29295138888881
27	437.72	437.332368055555	437.256666666667	0.075701388888847	0.387631944444593
28	438.73	438.040368055555	437.660416666667	0.37995138888886	0.689631944444557
29	437.7	438.533701388889	438.157083333333	0.376618055555519	-0.833701388888812
30	438.13	438.305284722222	438.687083333333	-0.381798611111123	-0.175284722222159
31	438.13	438.609368055556	439.202916666667	-0.593548611111107	-0.479368055555597
32	438.31	439.214618055556	439.782916666667	-0.568298611111102	-0.904618055555602
33	439.67	440.404034722222	440.359583333333	0.0444513888889266	-0.734034722222248
34	442	441.753201388889	440.834166666667	0.919034722222243	0.246798611111103
35	442.61	441.975368055556	441.35875	0.616618055555596	0.634631944444493
36	442.27	442.017951388889	441.945416666667	0.072534722222206	0.252048611111206
37	442.27	442.235784722222	442.507916666667	-0.272131944444443	0.0342152777778324
38	443.72	442.412951388889	443.082083333333	-0.669131944444423	1.30704861111116
39	443.83	443.798201388889	443.7225	0.075701388888847	0.0317986111111281
40	444.01	444.744118055556	444.364166666667	0.37995138888886	-0.734118055555598
41	445.01	445.287868055556	444.91125	0.376618055555519	-0.277868055555587
42	444.9	445.005701388889	445.3875	-0.381798611111123	-0.10570138888886
43	444.86	445.243951388889	445.8375	-0.593548611111107	-0.383951388888875
44	445.36	445.680451388889	446.24875	-0.568298611111102	-0.320451388888841
45	447.99	446.761534722222	446.717083333333	0.0444513888889266	1.22846527777784
46	449.08	448.184451388889	447.265416666667	0.919034722222243	0.895548611111167
47	448.66	448.321201388889	447.704583333333	0.616618055555596	0.338798611111145
48	447.65	448.110451388889	448.037916666667	0.072534722222206	-0.460451388888941
49	447.69	448.086618055556	448.35875	-0.272131944444443	-0.396618055555564
50	448.17	448.025451388889	448.694583333333	-0.669131944444423	0.144548611111134
51	450.62	449.016534722222	448.940833333333	0.075701388888847	1.60346527777779
52	450.38	449.427868055556	449.047916666667	0.37995138888886	0.952131944444432
53	449.18	449.608701388889	449.232083333333	0.376618055555519	-0.428701388888896
54	448.73	449.221118055556	449.602916666667	-0.381798611111123	-0.491118055555546
55	448.73	449.447701388889	450.04125	-0.593548611111107	-0.717701388888884
56	449.55	449.864201388889	450.4325	-0.568298611111102	-0.314201388888819
57	449.71	450.741118055555	450.696666666667	0.0444513888889266	-1.03111805555551
58	449.93	451.812368055556	450.893333333333	0.919034722222243	-1.8823680555555
59	452.23	451.868701388889	451.252083333333	0.616618055555596	0.361298611111181
60	452.98	451.778784722222	451.70625	0.072534722222206	1.20121527777781
61	452.88	451.839951388889	452.112083333333	-0.272131944444443	1.0400486111111
62	452.37	451.825451388889	452.494583333333	-0.669131944444423	0.544548611111111
63	452.76	452.937368055556	452.861666666667	0.075701388888847	-0.177368055555519
64	452.96	453.624534722222	453.244583333333	0.37995138888886	-0.664534722222186
65	455.21	453.985368055556	453.60875	0.376618055555519	1.22463194444441
66	453.6	453.528618055556	453.910416666667	-0.381798611111123	0.0713819444445107
67	453.6	NA	NA	-0.593548611111107	NA
68	453.86	NA	NA	-0.568298611111102	NA
69	454.21	NA	NA	0.0444513888889266	NA
70	454.62	NA	NA	0.919034722222243	NA
71	456.28	NA	NA	0.616618055555596	NA
72	456.17	NA	NA	0.072534722222206	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 434.49 & NA & NA & -0.272131944444443 & NA \tabularnewline
2 & 434.43 & NA & NA & -0.669131944444423 & NA \tabularnewline
3 & 434.07 & NA & NA & 0.075701388888847 & NA \tabularnewline
4 & 434.52 & NA & NA & 0.37995138888886 & NA \tabularnewline
5 & 433.52 & NA & NA & 0.376618055555519 & NA \tabularnewline
6 & 433.52 & NA & NA & -0.381798611111123 & NA \tabularnewline
7 & 433.52 & 433.072701388889 & 433.66625 & -0.593548611111107 & 0.447298611111137 \tabularnewline
8 & 433.26 & 432.867118055556 & 433.435416666667 & -0.568298611111102 & 0.392881944444468 \tabularnewline
9 & 433.63 & 433.230701388889 & 433.18625 & 0.0444513888889266 & 0.399298611111078 \tabularnewline
10 & 434.67 & 433.969868055556 & 433.050833333333 & 0.919034722222243 & 0.700131944444422 \tabularnewline
11 & 432.87 & 433.672868055556 & 433.05625 & 0.616618055555596 & -0.802868055555564 \tabularnewline
12 & 432.49 & 433.204201388889 & 433.131666666667 & 0.072534722222206 & -0.714201388888853 \tabularnewline
13 & 432.5 & 432.952868055556 & 433.225 & -0.272131944444443 & -0.452868055555598 \tabularnewline
14 & 430.88 & 432.698368055556 & 433.3675 & -0.669131944444423 & -1.8183680555556 \tabularnewline
15 & 431.64 & 433.600701388889 & 433.525 & 0.075701388888847 & -1.96070138888888 \tabularnewline
16 & 433.7 & 434.058284722222 & 433.678333333333 & 0.37995138888886 & -0.358284722222152 \tabularnewline
17 & 434.47 & 434.269534722222 & 433.892916666667 & 0.376618055555519 & 0.20046527777788 \tabularnewline
18 & 434.38 & 433.794451388889 & 434.17625 & -0.381798611111123 & 0.585548611111221 \tabularnewline
19 & 434.9 & 433.881451388889 & 434.475 & -0.593548611111107 & 1.01854861111116 \tabularnewline
20 & 435.3 & 434.268784722222 & 434.837083333333 & -0.568298611111102 & 1.0312152777779 \tabularnewline
21 & 435.37 & 435.347784722222 & 435.303333333333 & 0.0444513888889266 & 0.0222152777777751 \tabularnewline
22 & 436.61 & 436.685284722222 & 435.76625 & 0.919034722222243 & -0.0752847222221931 \tabularnewline
23 & 436.08 & 436.727034722222 & 436.110416666667 & 0.616618055555596 & -0.647034722222202 \tabularnewline
24 & 436.08 & 436.473784722222 & 436.40125 & 0.072534722222206 & -0.393784722222165 \tabularnewline
25 & 436.08 & 436.419951388889 & 436.692083333333 & -0.272131944444443 & -0.339951388888835 \tabularnewline
26 & 435.99 & 436.282951388889 & 436.952083333333 & -0.669131944444423 & -0.29295138888881 \tabularnewline
27 & 437.72 & 437.332368055555 & 437.256666666667 & 0.075701388888847 & 0.387631944444593 \tabularnewline
28 & 438.73 & 438.040368055555 & 437.660416666667 & 0.37995138888886 & 0.689631944444557 \tabularnewline
29 & 437.7 & 438.533701388889 & 438.157083333333 & 0.376618055555519 & -0.833701388888812 \tabularnewline
30 & 438.13 & 438.305284722222 & 438.687083333333 & -0.381798611111123 & -0.175284722222159 \tabularnewline
31 & 438.13 & 438.609368055556 & 439.202916666667 & -0.593548611111107 & -0.479368055555597 \tabularnewline
32 & 438.31 & 439.214618055556 & 439.782916666667 & -0.568298611111102 & -0.904618055555602 \tabularnewline
33 & 439.67 & 440.404034722222 & 440.359583333333 & 0.0444513888889266 & -0.734034722222248 \tabularnewline
34 & 442 & 441.753201388889 & 440.834166666667 & 0.919034722222243 & 0.246798611111103 \tabularnewline
35 & 442.61 & 441.975368055556 & 441.35875 & 0.616618055555596 & 0.634631944444493 \tabularnewline
36 & 442.27 & 442.017951388889 & 441.945416666667 & 0.072534722222206 & 0.252048611111206 \tabularnewline
37 & 442.27 & 442.235784722222 & 442.507916666667 & -0.272131944444443 & 0.0342152777778324 \tabularnewline
38 & 443.72 & 442.412951388889 & 443.082083333333 & -0.669131944444423 & 1.30704861111116 \tabularnewline
39 & 443.83 & 443.798201388889 & 443.7225 & 0.075701388888847 & 0.0317986111111281 \tabularnewline
40 & 444.01 & 444.744118055556 & 444.364166666667 & 0.37995138888886 & -0.734118055555598 \tabularnewline
41 & 445.01 & 445.287868055556 & 444.91125 & 0.376618055555519 & -0.277868055555587 \tabularnewline
42 & 444.9 & 445.005701388889 & 445.3875 & -0.381798611111123 & -0.10570138888886 \tabularnewline
43 & 444.86 & 445.243951388889 & 445.8375 & -0.593548611111107 & -0.383951388888875 \tabularnewline
44 & 445.36 & 445.680451388889 & 446.24875 & -0.568298611111102 & -0.320451388888841 \tabularnewline
45 & 447.99 & 446.761534722222 & 446.717083333333 & 0.0444513888889266 & 1.22846527777784 \tabularnewline
46 & 449.08 & 448.184451388889 & 447.265416666667 & 0.919034722222243 & 0.895548611111167 \tabularnewline
47 & 448.66 & 448.321201388889 & 447.704583333333 & 0.616618055555596 & 0.338798611111145 \tabularnewline
48 & 447.65 & 448.110451388889 & 448.037916666667 & 0.072534722222206 & -0.460451388888941 \tabularnewline
49 & 447.69 & 448.086618055556 & 448.35875 & -0.272131944444443 & -0.396618055555564 \tabularnewline
50 & 448.17 & 448.025451388889 & 448.694583333333 & -0.669131944444423 & 0.144548611111134 \tabularnewline
51 & 450.62 & 449.016534722222 & 448.940833333333 & 0.075701388888847 & 1.60346527777779 \tabularnewline
52 & 450.38 & 449.427868055556 & 449.047916666667 & 0.37995138888886 & 0.952131944444432 \tabularnewline
53 & 449.18 & 449.608701388889 & 449.232083333333 & 0.376618055555519 & -0.428701388888896 \tabularnewline
54 & 448.73 & 449.221118055556 & 449.602916666667 & -0.381798611111123 & -0.491118055555546 \tabularnewline
55 & 448.73 & 449.447701388889 & 450.04125 & -0.593548611111107 & -0.717701388888884 \tabularnewline
56 & 449.55 & 449.864201388889 & 450.4325 & -0.568298611111102 & -0.314201388888819 \tabularnewline
57 & 449.71 & 450.741118055555 & 450.696666666667 & 0.0444513888889266 & -1.03111805555551 \tabularnewline
58 & 449.93 & 451.812368055556 & 450.893333333333 & 0.919034722222243 & -1.8823680555555 \tabularnewline
59 & 452.23 & 451.868701388889 & 451.252083333333 & 0.616618055555596 & 0.361298611111181 \tabularnewline
60 & 452.98 & 451.778784722222 & 451.70625 & 0.072534722222206 & 1.20121527777781 \tabularnewline
61 & 452.88 & 451.839951388889 & 452.112083333333 & -0.272131944444443 & 1.0400486111111 \tabularnewline
62 & 452.37 & 451.825451388889 & 452.494583333333 & -0.669131944444423 & 0.544548611111111 \tabularnewline
63 & 452.76 & 452.937368055556 & 452.861666666667 & 0.075701388888847 & -0.177368055555519 \tabularnewline
64 & 452.96 & 453.624534722222 & 453.244583333333 & 0.37995138888886 & -0.664534722222186 \tabularnewline
65 & 455.21 & 453.985368055556 & 453.60875 & 0.376618055555519 & 1.22463194444441 \tabularnewline
66 & 453.6 & 453.528618055556 & 453.910416666667 & -0.381798611111123 & 0.0713819444445107 \tabularnewline
67 & 453.6 & NA & NA & -0.593548611111107 & NA \tabularnewline
68 & 453.86 & NA & NA & -0.568298611111102 & NA \tabularnewline
69 & 454.21 & NA & NA & 0.0444513888889266 & NA \tabularnewline
70 & 454.62 & NA & NA & 0.919034722222243 & NA \tabularnewline
71 & 456.28 & NA & NA & 0.616618055555596 & NA \tabularnewline
72 & 456.17 & NA & NA & 0.072534722222206 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205592&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]434.49[/C][C]NA[/C][C]NA[/C][C]-0.272131944444443[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]434.43[/C][C]NA[/C][C]NA[/C][C]-0.669131944444423[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]434.07[/C][C]NA[/C][C]NA[/C][C]0.075701388888847[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]434.52[/C][C]NA[/C][C]NA[/C][C]0.37995138888886[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]433.52[/C][C]NA[/C][C]NA[/C][C]0.376618055555519[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]433.52[/C][C]NA[/C][C]NA[/C][C]-0.381798611111123[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]433.52[/C][C]433.072701388889[/C][C]433.66625[/C][C]-0.593548611111107[/C][C]0.447298611111137[/C][/ROW]
[ROW][C]8[/C][C]433.26[/C][C]432.867118055556[/C][C]433.435416666667[/C][C]-0.568298611111102[/C][C]0.392881944444468[/C][/ROW]
[ROW][C]9[/C][C]433.63[/C][C]433.230701388889[/C][C]433.18625[/C][C]0.0444513888889266[/C][C]0.399298611111078[/C][/ROW]
[ROW][C]10[/C][C]434.67[/C][C]433.969868055556[/C][C]433.050833333333[/C][C]0.919034722222243[/C][C]0.700131944444422[/C][/ROW]
[ROW][C]11[/C][C]432.87[/C][C]433.672868055556[/C][C]433.05625[/C][C]0.616618055555596[/C][C]-0.802868055555564[/C][/ROW]
[ROW][C]12[/C][C]432.49[/C][C]433.204201388889[/C][C]433.131666666667[/C][C]0.072534722222206[/C][C]-0.714201388888853[/C][/ROW]
[ROW][C]13[/C][C]432.5[/C][C]432.952868055556[/C][C]433.225[/C][C]-0.272131944444443[/C][C]-0.452868055555598[/C][/ROW]
[ROW][C]14[/C][C]430.88[/C][C]432.698368055556[/C][C]433.3675[/C][C]-0.669131944444423[/C][C]-1.8183680555556[/C][/ROW]
[ROW][C]15[/C][C]431.64[/C][C]433.600701388889[/C][C]433.525[/C][C]0.075701388888847[/C][C]-1.96070138888888[/C][/ROW]
[ROW][C]16[/C][C]433.7[/C][C]434.058284722222[/C][C]433.678333333333[/C][C]0.37995138888886[/C][C]-0.358284722222152[/C][/ROW]
[ROW][C]17[/C][C]434.47[/C][C]434.269534722222[/C][C]433.892916666667[/C][C]0.376618055555519[/C][C]0.20046527777788[/C][/ROW]
[ROW][C]18[/C][C]434.38[/C][C]433.794451388889[/C][C]434.17625[/C][C]-0.381798611111123[/C][C]0.585548611111221[/C][/ROW]
[ROW][C]19[/C][C]434.9[/C][C]433.881451388889[/C][C]434.475[/C][C]-0.593548611111107[/C][C]1.01854861111116[/C][/ROW]
[ROW][C]20[/C][C]435.3[/C][C]434.268784722222[/C][C]434.837083333333[/C][C]-0.568298611111102[/C][C]1.0312152777779[/C][/ROW]
[ROW][C]21[/C][C]435.37[/C][C]435.347784722222[/C][C]435.303333333333[/C][C]0.0444513888889266[/C][C]0.0222152777777751[/C][/ROW]
[ROW][C]22[/C][C]436.61[/C][C]436.685284722222[/C][C]435.76625[/C][C]0.919034722222243[/C][C]-0.0752847222221931[/C][/ROW]
[ROW][C]23[/C][C]436.08[/C][C]436.727034722222[/C][C]436.110416666667[/C][C]0.616618055555596[/C][C]-0.647034722222202[/C][/ROW]
[ROW][C]24[/C][C]436.08[/C][C]436.473784722222[/C][C]436.40125[/C][C]0.072534722222206[/C][C]-0.393784722222165[/C][/ROW]
[ROW][C]25[/C][C]436.08[/C][C]436.419951388889[/C][C]436.692083333333[/C][C]-0.272131944444443[/C][C]-0.339951388888835[/C][/ROW]
[ROW][C]26[/C][C]435.99[/C][C]436.282951388889[/C][C]436.952083333333[/C][C]-0.669131944444423[/C][C]-0.29295138888881[/C][/ROW]
[ROW][C]27[/C][C]437.72[/C][C]437.332368055555[/C][C]437.256666666667[/C][C]0.075701388888847[/C][C]0.387631944444593[/C][/ROW]
[ROW][C]28[/C][C]438.73[/C][C]438.040368055555[/C][C]437.660416666667[/C][C]0.37995138888886[/C][C]0.689631944444557[/C][/ROW]
[ROW][C]29[/C][C]437.7[/C][C]438.533701388889[/C][C]438.157083333333[/C][C]0.376618055555519[/C][C]-0.833701388888812[/C][/ROW]
[ROW][C]30[/C][C]438.13[/C][C]438.305284722222[/C][C]438.687083333333[/C][C]-0.381798611111123[/C][C]-0.175284722222159[/C][/ROW]
[ROW][C]31[/C][C]438.13[/C][C]438.609368055556[/C][C]439.202916666667[/C][C]-0.593548611111107[/C][C]-0.479368055555597[/C][/ROW]
[ROW][C]32[/C][C]438.31[/C][C]439.214618055556[/C][C]439.782916666667[/C][C]-0.568298611111102[/C][C]-0.904618055555602[/C][/ROW]
[ROW][C]33[/C][C]439.67[/C][C]440.404034722222[/C][C]440.359583333333[/C][C]0.0444513888889266[/C][C]-0.734034722222248[/C][/ROW]
[ROW][C]34[/C][C]442[/C][C]441.753201388889[/C][C]440.834166666667[/C][C]0.919034722222243[/C][C]0.246798611111103[/C][/ROW]
[ROW][C]35[/C][C]442.61[/C][C]441.975368055556[/C][C]441.35875[/C][C]0.616618055555596[/C][C]0.634631944444493[/C][/ROW]
[ROW][C]36[/C][C]442.27[/C][C]442.017951388889[/C][C]441.945416666667[/C][C]0.072534722222206[/C][C]0.252048611111206[/C][/ROW]
[ROW][C]37[/C][C]442.27[/C][C]442.235784722222[/C][C]442.507916666667[/C][C]-0.272131944444443[/C][C]0.0342152777778324[/C][/ROW]
[ROW][C]38[/C][C]443.72[/C][C]442.412951388889[/C][C]443.082083333333[/C][C]-0.669131944444423[/C][C]1.30704861111116[/C][/ROW]
[ROW][C]39[/C][C]443.83[/C][C]443.798201388889[/C][C]443.7225[/C][C]0.075701388888847[/C][C]0.0317986111111281[/C][/ROW]
[ROW][C]40[/C][C]444.01[/C][C]444.744118055556[/C][C]444.364166666667[/C][C]0.37995138888886[/C][C]-0.734118055555598[/C][/ROW]
[ROW][C]41[/C][C]445.01[/C][C]445.287868055556[/C][C]444.91125[/C][C]0.376618055555519[/C][C]-0.277868055555587[/C][/ROW]
[ROW][C]42[/C][C]444.9[/C][C]445.005701388889[/C][C]445.3875[/C][C]-0.381798611111123[/C][C]-0.10570138888886[/C][/ROW]
[ROW][C]43[/C][C]444.86[/C][C]445.243951388889[/C][C]445.8375[/C][C]-0.593548611111107[/C][C]-0.383951388888875[/C][/ROW]
[ROW][C]44[/C][C]445.36[/C][C]445.680451388889[/C][C]446.24875[/C][C]-0.568298611111102[/C][C]-0.320451388888841[/C][/ROW]
[ROW][C]45[/C][C]447.99[/C][C]446.761534722222[/C][C]446.717083333333[/C][C]0.0444513888889266[/C][C]1.22846527777784[/C][/ROW]
[ROW][C]46[/C][C]449.08[/C][C]448.184451388889[/C][C]447.265416666667[/C][C]0.919034722222243[/C][C]0.895548611111167[/C][/ROW]
[ROW][C]47[/C][C]448.66[/C][C]448.321201388889[/C][C]447.704583333333[/C][C]0.616618055555596[/C][C]0.338798611111145[/C][/ROW]
[ROW][C]48[/C][C]447.65[/C][C]448.110451388889[/C][C]448.037916666667[/C][C]0.072534722222206[/C][C]-0.460451388888941[/C][/ROW]
[ROW][C]49[/C][C]447.69[/C][C]448.086618055556[/C][C]448.35875[/C][C]-0.272131944444443[/C][C]-0.396618055555564[/C][/ROW]
[ROW][C]50[/C][C]448.17[/C][C]448.025451388889[/C][C]448.694583333333[/C][C]-0.669131944444423[/C][C]0.144548611111134[/C][/ROW]
[ROW][C]51[/C][C]450.62[/C][C]449.016534722222[/C][C]448.940833333333[/C][C]0.075701388888847[/C][C]1.60346527777779[/C][/ROW]
[ROW][C]52[/C][C]450.38[/C][C]449.427868055556[/C][C]449.047916666667[/C][C]0.37995138888886[/C][C]0.952131944444432[/C][/ROW]
[ROW][C]53[/C][C]449.18[/C][C]449.608701388889[/C][C]449.232083333333[/C][C]0.376618055555519[/C][C]-0.428701388888896[/C][/ROW]
[ROW][C]54[/C][C]448.73[/C][C]449.221118055556[/C][C]449.602916666667[/C][C]-0.381798611111123[/C][C]-0.491118055555546[/C][/ROW]
[ROW][C]55[/C][C]448.73[/C][C]449.447701388889[/C][C]450.04125[/C][C]-0.593548611111107[/C][C]-0.717701388888884[/C][/ROW]
[ROW][C]56[/C][C]449.55[/C][C]449.864201388889[/C][C]450.4325[/C][C]-0.568298611111102[/C][C]-0.314201388888819[/C][/ROW]
[ROW][C]57[/C][C]449.71[/C][C]450.741118055555[/C][C]450.696666666667[/C][C]0.0444513888889266[/C][C]-1.03111805555551[/C][/ROW]
[ROW][C]58[/C][C]449.93[/C][C]451.812368055556[/C][C]450.893333333333[/C][C]0.919034722222243[/C][C]-1.8823680555555[/C][/ROW]
[ROW][C]59[/C][C]452.23[/C][C]451.868701388889[/C][C]451.252083333333[/C][C]0.616618055555596[/C][C]0.361298611111181[/C][/ROW]
[ROW][C]60[/C][C]452.98[/C][C]451.778784722222[/C][C]451.70625[/C][C]0.072534722222206[/C][C]1.20121527777781[/C][/ROW]
[ROW][C]61[/C][C]452.88[/C][C]451.839951388889[/C][C]452.112083333333[/C][C]-0.272131944444443[/C][C]1.0400486111111[/C][/ROW]
[ROW][C]62[/C][C]452.37[/C][C]451.825451388889[/C][C]452.494583333333[/C][C]-0.669131944444423[/C][C]0.544548611111111[/C][/ROW]
[ROW][C]63[/C][C]452.76[/C][C]452.937368055556[/C][C]452.861666666667[/C][C]0.075701388888847[/C][C]-0.177368055555519[/C][/ROW]
[ROW][C]64[/C][C]452.96[/C][C]453.624534722222[/C][C]453.244583333333[/C][C]0.37995138888886[/C][C]-0.664534722222186[/C][/ROW]
[ROW][C]65[/C][C]455.21[/C][C]453.985368055556[/C][C]453.60875[/C][C]0.376618055555519[/C][C]1.22463194444441[/C][/ROW]
[ROW][C]66[/C][C]453.6[/C][C]453.528618055556[/C][C]453.910416666667[/C][C]-0.381798611111123[/C][C]0.0713819444445107[/C][/ROW]
[ROW][C]67[/C][C]453.6[/C][C]NA[/C][C]NA[/C][C]-0.593548611111107[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]453.86[/C][C]NA[/C][C]NA[/C][C]-0.568298611111102[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]454.21[/C][C]NA[/C][C]NA[/C][C]0.0444513888889266[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]454.62[/C][C]NA[/C][C]NA[/C][C]0.919034722222243[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]456.28[/C][C]NA[/C][C]NA[/C][C]0.616618055555596[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]456.17[/C][C]NA[/C][C]NA[/C][C]0.072534722222206[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205592&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205592&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	434.49	NA	NA	-0.272131944444443	NA
2	434.43	NA	NA	-0.669131944444423	NA
3	434.07	NA	NA	0.075701388888847	NA
4	434.52	NA	NA	0.37995138888886	NA
5	433.52	NA	NA	0.376618055555519	NA
6	433.52	NA	NA	-0.381798611111123	NA
7	433.52	433.072701388889	433.66625	-0.593548611111107	0.447298611111137
8	433.26	432.867118055556	433.435416666667	-0.568298611111102	0.392881944444468
9	433.63	433.230701388889	433.18625	0.0444513888889266	0.399298611111078
10	434.67	433.969868055556	433.050833333333	0.919034722222243	0.700131944444422
11	432.87	433.672868055556	433.05625	0.616618055555596	-0.802868055555564
12	432.49	433.204201388889	433.131666666667	0.072534722222206	-0.714201388888853
13	432.5	432.952868055556	433.225	-0.272131944444443	-0.452868055555598
14	430.88	432.698368055556	433.3675	-0.669131944444423	-1.8183680555556
15	431.64	433.600701388889	433.525	0.075701388888847	-1.96070138888888
16	433.7	434.058284722222	433.678333333333	0.37995138888886	-0.358284722222152
17	434.47	434.269534722222	433.892916666667	0.376618055555519	0.20046527777788
18	434.38	433.794451388889	434.17625	-0.381798611111123	0.585548611111221
19	434.9	433.881451388889	434.475	-0.593548611111107	1.01854861111116
20	435.3	434.268784722222	434.837083333333	-0.568298611111102	1.0312152777779
21	435.37	435.347784722222	435.303333333333	0.0444513888889266	0.0222152777777751
22	436.61	436.685284722222	435.76625	0.919034722222243	-0.0752847222221931
23	436.08	436.727034722222	436.110416666667	0.616618055555596	-0.647034722222202
24	436.08	436.473784722222	436.40125	0.072534722222206	-0.393784722222165
25	436.08	436.419951388889	436.692083333333	-0.272131944444443	-0.339951388888835
26	435.99	436.282951388889	436.952083333333	-0.669131944444423	-0.29295138888881
27	437.72	437.332368055555	437.256666666667	0.075701388888847	0.387631944444593
28	438.73	438.040368055555	437.660416666667	0.37995138888886	0.689631944444557
29	437.7	438.533701388889	438.157083333333	0.376618055555519	-0.833701388888812
30	438.13	438.305284722222	438.687083333333	-0.381798611111123	-0.175284722222159
31	438.13	438.609368055556	439.202916666667	-0.593548611111107	-0.479368055555597
32	438.31	439.214618055556	439.782916666667	-0.568298611111102	-0.904618055555602
33	439.67	440.404034722222	440.359583333333	0.0444513888889266	-0.734034722222248
34	442	441.753201388889	440.834166666667	0.919034722222243	0.246798611111103
35	442.61	441.975368055556	441.35875	0.616618055555596	0.634631944444493
36	442.27	442.017951388889	441.945416666667	0.072534722222206	0.252048611111206
37	442.27	442.235784722222	442.507916666667	-0.272131944444443	0.0342152777778324
38	443.72	442.412951388889	443.082083333333	-0.669131944444423	1.30704861111116
39	443.83	443.798201388889	443.7225	0.075701388888847	0.0317986111111281
40	444.01	444.744118055556	444.364166666667	0.37995138888886	-0.734118055555598
41	445.01	445.287868055556	444.91125	0.376618055555519	-0.277868055555587
42	444.9	445.005701388889	445.3875	-0.381798611111123	-0.10570138888886
43	444.86	445.243951388889	445.8375	-0.593548611111107	-0.383951388888875
44	445.36	445.680451388889	446.24875	-0.568298611111102	-0.320451388888841
45	447.99	446.761534722222	446.717083333333	0.0444513888889266	1.22846527777784
46	449.08	448.184451388889	447.265416666667	0.919034722222243	0.895548611111167
47	448.66	448.321201388889	447.704583333333	0.616618055555596	0.338798611111145
48	447.65	448.110451388889	448.037916666667	0.072534722222206	-0.460451388888941
49	447.69	448.086618055556	448.35875	-0.272131944444443	-0.396618055555564
50	448.17	448.025451388889	448.694583333333	-0.669131944444423	0.144548611111134
51	450.62	449.016534722222	448.940833333333	0.075701388888847	1.60346527777779
52	450.38	449.427868055556	449.047916666667	0.37995138888886	0.952131944444432
53	449.18	449.608701388889	449.232083333333	0.376618055555519	-0.428701388888896
54	448.73	449.221118055556	449.602916666667	-0.381798611111123	-0.491118055555546
55	448.73	449.447701388889	450.04125	-0.593548611111107	-0.717701388888884
56	449.55	449.864201388889	450.4325	-0.568298611111102	-0.314201388888819
57	449.71	450.741118055555	450.696666666667	0.0444513888889266	-1.03111805555551
58	449.93	451.812368055556	450.893333333333	0.919034722222243	-1.8823680555555
59	452.23	451.868701388889	451.252083333333	0.616618055555596	0.361298611111181
60	452.98	451.778784722222	451.70625	0.072534722222206	1.20121527777781
61	452.88	451.839951388889	452.112083333333	-0.272131944444443	1.0400486111111
62	452.37	451.825451388889	452.494583333333	-0.669131944444423	0.544548611111111
63	452.76	452.937368055556	452.861666666667	0.075701388888847	-0.177368055555519
64	452.96	453.624534722222	453.244583333333	0.37995138888886	-0.664534722222186
65	455.21	453.985368055556	453.60875	0.376618055555519	1.22463194444441
66	453.6	453.528618055556	453.910416666667	-0.381798611111123	0.0713819444445107
67	453.6	NA	NA	-0.593548611111107	NA
68	453.86	NA	NA	-0.568298611111102	NA
69	454.21	NA	NA	0.0444513888889266	NA
70	454.62	NA	NA	0.919034722222243	NA
71	456.28	NA	NA	0.616618055555596	NA
72	456.17	NA	NA	0.072534722222206	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