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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 27 May 2012 09:42:02 -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/2012/May/27/t1338126343r1g0j8d6lsgmcwd.htm/, Retrieved Thu, 09 May 2024 01:18:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167712, Retrieved Thu, 09 May 2024 01:18:42 +0000

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Estimated Impact

126

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

-       [Classical Decomposition] [Kleding en kledin...] [2012-05-27 13:42:02] [675223405f94cd8491f4a89fc80aa26c] [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	2 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167712&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167712&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167712&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	219.2	NA	NA	1.01280126475593	NA
2	232.5	NA	NA	1.11502904126225	NA
3	235.6	NA	NA	1.09052652392481	NA
4	171	NA	NA	0.855521070004111	NA
5	165.9	NA	NA	0.748053590035559	NA
6	187.6	NA	NA	0.850619371588104	NA
7	218.2	229.912335180738	212.4375	1.08225871223648	0.949057386714243
8	249.8	243.442006385613	213.745833333333	1.13893217280156	1.02611707695309
9	256.5	251.348500692639	216.05	1.16338116497403	1.02049544474371
10	224.9	239.644493968738	218.5875	1.09633210484926	0.938473470745955
11	200	197.318440804845	220.45	0.895071176252415	1.01359000803076
12	182.5	211.088428627137	221.854166666667	0.951473807315484	0.864566576135562
13	230.3	227.010963484502	224.141666666667	1.01280126475593	1.01448844789262
14	252.8	253.329952220446	227.195833333333	1.11502904126225	0.997908055420211
15	270.6	249.821451189109	229.083333333333	1.09052652392481	1.08317359743124
16	196.9	198.512970281079	232.0375	0.855521070004111	0.991874736049765
17	184.7	176.381685860509	235.7875	0.748053590035559	1.04716087216713
18	202.5	202.716773238972	238.316666666667	0.850619371588104	0.998930659582293
19	258.2	259.62484624293	239.891666666667	1.08225871223648	0.994511903373082
20	283.1	274.084027384695	240.65	1.13893217280156	1.03289492168272
21	268.5	279.23571670137	240.020833333333	1.16338116497403	0.961553210928057
22	283.8	262.055349412032	239.029166666667	1.09633210484926	1.08297732000799
23	231.1	213.343944322997	238.354166666667	0.895071176252415	1.08322737133856
24	212.1	225.368464685264	236.8625	0.951473807315484	0.941125460015918
25	238.5	238.983118434971	235.9625	1.01280126475593	0.997978441162981
26	262.8	261.246658413408	234.295833333333	1.11502904126225	1.00594588116849
27	245.5	253.656469464911	232.6	1.09052652392481	0.967844425643401
28	198.2	197.375840192198	230.708333333333	0.855521070004111	1.00417558606463
29	167.2	169.907905416743	227.133333333333	0.748053590035559	0.984062510746034
30	184.2	193.140216813842	227.058333333333	0.850619371588104	0.953711262411706
31	254.9	247.278078100832	228.483333333333	1.08225871223648	1.03082328186027
32	246.4	259.391802355555	227.75	1.13893217280156	0.949914368004016
33	264.5	263.665798776801	226.6375	1.16338116497403	1.00316385828981
34	242.4	247.012759323413	225.308333333333	1.09633210484926	0.981325825693995
35	186.7	200.488484554072	223.991666666667	0.895071176252415	0.931225553503781
36	254.7	212.214339299127	223.0375	0.951473807315484	1.20020164914958
37	230.1	224.533820391119	221.695833333333	1.01280126475593	1.02478993854549
38	253.6	245.143780675845	219.854166666667	1.11502904126225	1.03449493721946
39	228	237.689343610445	217.958333333333	1.09052652392481	0.959235262871837
40	183.8	184.614317564637	215.791666666667	0.855521070004111	0.995589087697101
41	150	160.258014105285	214.233333333333	0.748053590035559	0.93599063258986
42	178.5	179.43815643651	210.95	0.850619371588104	0.994771700427928
43	228.4	223.74346052099	206.7375	1.08225871223648	1.02081195789217
44	228.7	231.881844831678	203.595833333333	1.13893217280156	0.986278163199938
45	236.7	234.358288262497	201.445833333333	1.16338116497403	1.00999201587818
46	218.2	219.864835577083	200.545833333333	1.09633210484926	0.99242791339182
47	173.5	179.390911037156	200.420833333333	0.895071176252415	0.967161596966662
48	189.1	191.143158941286	200.891666666667	0.951473807315484	0.989310844538705
49	194.6	203.14261367842	200.575	1.01280126475593	0.957947702238668
50	213.7	223.335671010491	200.295833333333	1.11502904126225	0.956855656031595
51	216.3	219.604778755359	201.375	1.09052652392481	0.984951243893283
52	173.9	173.282228058208	202.545833333333	0.855521070004111	1.00356512002826
53	156.9	152.627867486922	204.033333333333	0.748053590035559	1.02799051433674
54	182.9	174.557727792024	205.2125	0.850619371588104	1.04779090741784
55	216.4	NA	NA	1.08225871223648	NA
56	234	NA	NA	1.13893217280156	NA
57	257.3	NA	NA	1.16338116497403	NA
58	225.7	NA	NA	1.09633210484926	NA
59	201.7	NA	NA	0.895071176252415	NA
60	189.2	NA	NA	0.951473807315484	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 219.2 & NA & NA & 1.01280126475593 & NA \tabularnewline
2 & 232.5 & NA & NA & 1.11502904126225 & NA \tabularnewline
3 & 235.6 & NA & NA & 1.09052652392481 & NA \tabularnewline
4 & 171 & NA & NA & 0.855521070004111 & NA \tabularnewline
5 & 165.9 & NA & NA & 0.748053590035559 & NA \tabularnewline
6 & 187.6 & NA & NA & 0.850619371588104 & NA \tabularnewline
7 & 218.2 & 229.912335180738 & 212.4375 & 1.08225871223648 & 0.949057386714243 \tabularnewline
8 & 249.8 & 243.442006385613 & 213.745833333333 & 1.13893217280156 & 1.02611707695309 \tabularnewline
9 & 256.5 & 251.348500692639 & 216.05 & 1.16338116497403 & 1.02049544474371 \tabularnewline
10 & 224.9 & 239.644493968738 & 218.5875 & 1.09633210484926 & 0.938473470745955 \tabularnewline
11 & 200 & 197.318440804845 & 220.45 & 0.895071176252415 & 1.01359000803076 \tabularnewline
12 & 182.5 & 211.088428627137 & 221.854166666667 & 0.951473807315484 & 0.864566576135562 \tabularnewline
13 & 230.3 & 227.010963484502 & 224.141666666667 & 1.01280126475593 & 1.01448844789262 \tabularnewline
14 & 252.8 & 253.329952220446 & 227.195833333333 & 1.11502904126225 & 0.997908055420211 \tabularnewline
15 & 270.6 & 249.821451189109 & 229.083333333333 & 1.09052652392481 & 1.08317359743124 \tabularnewline
16 & 196.9 & 198.512970281079 & 232.0375 & 0.855521070004111 & 0.991874736049765 \tabularnewline
17 & 184.7 & 176.381685860509 & 235.7875 & 0.748053590035559 & 1.04716087216713 \tabularnewline
18 & 202.5 & 202.716773238972 & 238.316666666667 & 0.850619371588104 & 0.998930659582293 \tabularnewline
19 & 258.2 & 259.62484624293 & 239.891666666667 & 1.08225871223648 & 0.994511903373082 \tabularnewline
20 & 283.1 & 274.084027384695 & 240.65 & 1.13893217280156 & 1.03289492168272 \tabularnewline
21 & 268.5 & 279.23571670137 & 240.020833333333 & 1.16338116497403 & 0.961553210928057 \tabularnewline
22 & 283.8 & 262.055349412032 & 239.029166666667 & 1.09633210484926 & 1.08297732000799 \tabularnewline
23 & 231.1 & 213.343944322997 & 238.354166666667 & 0.895071176252415 & 1.08322737133856 \tabularnewline
24 & 212.1 & 225.368464685264 & 236.8625 & 0.951473807315484 & 0.941125460015918 \tabularnewline
25 & 238.5 & 238.983118434971 & 235.9625 & 1.01280126475593 & 0.997978441162981 \tabularnewline
26 & 262.8 & 261.246658413408 & 234.295833333333 & 1.11502904126225 & 1.00594588116849 \tabularnewline
27 & 245.5 & 253.656469464911 & 232.6 & 1.09052652392481 & 0.967844425643401 \tabularnewline
28 & 198.2 & 197.375840192198 & 230.708333333333 & 0.855521070004111 & 1.00417558606463 \tabularnewline
29 & 167.2 & 169.907905416743 & 227.133333333333 & 0.748053590035559 & 0.984062510746034 \tabularnewline
30 & 184.2 & 193.140216813842 & 227.058333333333 & 0.850619371588104 & 0.953711262411706 \tabularnewline
31 & 254.9 & 247.278078100832 & 228.483333333333 & 1.08225871223648 & 1.03082328186027 \tabularnewline
32 & 246.4 & 259.391802355555 & 227.75 & 1.13893217280156 & 0.949914368004016 \tabularnewline
33 & 264.5 & 263.665798776801 & 226.6375 & 1.16338116497403 & 1.00316385828981 \tabularnewline
34 & 242.4 & 247.012759323413 & 225.308333333333 & 1.09633210484926 & 0.981325825693995 \tabularnewline
35 & 186.7 & 200.488484554072 & 223.991666666667 & 0.895071176252415 & 0.931225553503781 \tabularnewline
36 & 254.7 & 212.214339299127 & 223.0375 & 0.951473807315484 & 1.20020164914958 \tabularnewline
37 & 230.1 & 224.533820391119 & 221.695833333333 & 1.01280126475593 & 1.02478993854549 \tabularnewline
38 & 253.6 & 245.143780675845 & 219.854166666667 & 1.11502904126225 & 1.03449493721946 \tabularnewline
39 & 228 & 237.689343610445 & 217.958333333333 & 1.09052652392481 & 0.959235262871837 \tabularnewline
40 & 183.8 & 184.614317564637 & 215.791666666667 & 0.855521070004111 & 0.995589087697101 \tabularnewline
41 & 150 & 160.258014105285 & 214.233333333333 & 0.748053590035559 & 0.93599063258986 \tabularnewline
42 & 178.5 & 179.43815643651 & 210.95 & 0.850619371588104 & 0.994771700427928 \tabularnewline
43 & 228.4 & 223.74346052099 & 206.7375 & 1.08225871223648 & 1.02081195789217 \tabularnewline
44 & 228.7 & 231.881844831678 & 203.595833333333 & 1.13893217280156 & 0.986278163199938 \tabularnewline
45 & 236.7 & 234.358288262497 & 201.445833333333 & 1.16338116497403 & 1.00999201587818 \tabularnewline
46 & 218.2 & 219.864835577083 & 200.545833333333 & 1.09633210484926 & 0.99242791339182 \tabularnewline
47 & 173.5 & 179.390911037156 & 200.420833333333 & 0.895071176252415 & 0.967161596966662 \tabularnewline
48 & 189.1 & 191.143158941286 & 200.891666666667 & 0.951473807315484 & 0.989310844538705 \tabularnewline
49 & 194.6 & 203.14261367842 & 200.575 & 1.01280126475593 & 0.957947702238668 \tabularnewline
50 & 213.7 & 223.335671010491 & 200.295833333333 & 1.11502904126225 & 0.956855656031595 \tabularnewline
51 & 216.3 & 219.604778755359 & 201.375 & 1.09052652392481 & 0.984951243893283 \tabularnewline
52 & 173.9 & 173.282228058208 & 202.545833333333 & 0.855521070004111 & 1.00356512002826 \tabularnewline
53 & 156.9 & 152.627867486922 & 204.033333333333 & 0.748053590035559 & 1.02799051433674 \tabularnewline
54 & 182.9 & 174.557727792024 & 205.2125 & 0.850619371588104 & 1.04779090741784 \tabularnewline
55 & 216.4 & NA & NA & 1.08225871223648 & NA \tabularnewline
56 & 234 & NA & NA & 1.13893217280156 & NA \tabularnewline
57 & 257.3 & NA & NA & 1.16338116497403 & NA \tabularnewline
58 & 225.7 & NA & NA & 1.09633210484926 & NA \tabularnewline
59 & 201.7 & NA & NA & 0.895071176252415 & NA \tabularnewline
60 & 189.2 & NA & NA & 0.951473807315484 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167712&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]219.2[/C][C]NA[/C][C]NA[/C][C]1.01280126475593[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]232.5[/C][C]NA[/C][C]NA[/C][C]1.11502904126225[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]235.6[/C][C]NA[/C][C]NA[/C][C]1.09052652392481[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]171[/C][C]NA[/C][C]NA[/C][C]0.855521070004111[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]165.9[/C][C]NA[/C][C]NA[/C][C]0.748053590035559[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]187.6[/C][C]NA[/C][C]NA[/C][C]0.850619371588104[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]218.2[/C][C]229.912335180738[/C][C]212.4375[/C][C]1.08225871223648[/C][C]0.949057386714243[/C][/ROW]
[ROW][C]8[/C][C]249.8[/C][C]243.442006385613[/C][C]213.745833333333[/C][C]1.13893217280156[/C][C]1.02611707695309[/C][/ROW]
[ROW][C]9[/C][C]256.5[/C][C]251.348500692639[/C][C]216.05[/C][C]1.16338116497403[/C][C]1.02049544474371[/C][/ROW]
[ROW][C]10[/C][C]224.9[/C][C]239.644493968738[/C][C]218.5875[/C][C]1.09633210484926[/C][C]0.938473470745955[/C][/ROW]
[ROW][C]11[/C][C]200[/C][C]197.318440804845[/C][C]220.45[/C][C]0.895071176252415[/C][C]1.01359000803076[/C][/ROW]
[ROW][C]12[/C][C]182.5[/C][C]211.088428627137[/C][C]221.854166666667[/C][C]0.951473807315484[/C][C]0.864566576135562[/C][/ROW]
[ROW][C]13[/C][C]230.3[/C][C]227.010963484502[/C][C]224.141666666667[/C][C]1.01280126475593[/C][C]1.01448844789262[/C][/ROW]
[ROW][C]14[/C][C]252.8[/C][C]253.329952220446[/C][C]227.195833333333[/C][C]1.11502904126225[/C][C]0.997908055420211[/C][/ROW]
[ROW][C]15[/C][C]270.6[/C][C]249.821451189109[/C][C]229.083333333333[/C][C]1.09052652392481[/C][C]1.08317359743124[/C][/ROW]
[ROW][C]16[/C][C]196.9[/C][C]198.512970281079[/C][C]232.0375[/C][C]0.855521070004111[/C][C]0.991874736049765[/C][/ROW]
[ROW][C]17[/C][C]184.7[/C][C]176.381685860509[/C][C]235.7875[/C][C]0.748053590035559[/C][C]1.04716087216713[/C][/ROW]
[ROW][C]18[/C][C]202.5[/C][C]202.716773238972[/C][C]238.316666666667[/C][C]0.850619371588104[/C][C]0.998930659582293[/C][/ROW]
[ROW][C]19[/C][C]258.2[/C][C]259.62484624293[/C][C]239.891666666667[/C][C]1.08225871223648[/C][C]0.994511903373082[/C][/ROW]
[ROW][C]20[/C][C]283.1[/C][C]274.084027384695[/C][C]240.65[/C][C]1.13893217280156[/C][C]1.03289492168272[/C][/ROW]
[ROW][C]21[/C][C]268.5[/C][C]279.23571670137[/C][C]240.020833333333[/C][C]1.16338116497403[/C][C]0.961553210928057[/C][/ROW]
[ROW][C]22[/C][C]283.8[/C][C]262.055349412032[/C][C]239.029166666667[/C][C]1.09633210484926[/C][C]1.08297732000799[/C][/ROW]
[ROW][C]23[/C][C]231.1[/C][C]213.343944322997[/C][C]238.354166666667[/C][C]0.895071176252415[/C][C]1.08322737133856[/C][/ROW]
[ROW][C]24[/C][C]212.1[/C][C]225.368464685264[/C][C]236.8625[/C][C]0.951473807315484[/C][C]0.941125460015918[/C][/ROW]
[ROW][C]25[/C][C]238.5[/C][C]238.983118434971[/C][C]235.9625[/C][C]1.01280126475593[/C][C]0.997978441162981[/C][/ROW]
[ROW][C]26[/C][C]262.8[/C][C]261.246658413408[/C][C]234.295833333333[/C][C]1.11502904126225[/C][C]1.00594588116849[/C][/ROW]
[ROW][C]27[/C][C]245.5[/C][C]253.656469464911[/C][C]232.6[/C][C]1.09052652392481[/C][C]0.967844425643401[/C][/ROW]
[ROW][C]28[/C][C]198.2[/C][C]197.375840192198[/C][C]230.708333333333[/C][C]0.855521070004111[/C][C]1.00417558606463[/C][/ROW]
[ROW][C]29[/C][C]167.2[/C][C]169.907905416743[/C][C]227.133333333333[/C][C]0.748053590035559[/C][C]0.984062510746034[/C][/ROW]
[ROW][C]30[/C][C]184.2[/C][C]193.140216813842[/C][C]227.058333333333[/C][C]0.850619371588104[/C][C]0.953711262411706[/C][/ROW]
[ROW][C]31[/C][C]254.9[/C][C]247.278078100832[/C][C]228.483333333333[/C][C]1.08225871223648[/C][C]1.03082328186027[/C][/ROW]
[ROW][C]32[/C][C]246.4[/C][C]259.391802355555[/C][C]227.75[/C][C]1.13893217280156[/C][C]0.949914368004016[/C][/ROW]
[ROW][C]33[/C][C]264.5[/C][C]263.665798776801[/C][C]226.6375[/C][C]1.16338116497403[/C][C]1.00316385828981[/C][/ROW]
[ROW][C]34[/C][C]242.4[/C][C]247.012759323413[/C][C]225.308333333333[/C][C]1.09633210484926[/C][C]0.981325825693995[/C][/ROW]
[ROW][C]35[/C][C]186.7[/C][C]200.488484554072[/C][C]223.991666666667[/C][C]0.895071176252415[/C][C]0.931225553503781[/C][/ROW]
[ROW][C]36[/C][C]254.7[/C][C]212.214339299127[/C][C]223.0375[/C][C]0.951473807315484[/C][C]1.20020164914958[/C][/ROW]
[ROW][C]37[/C][C]230.1[/C][C]224.533820391119[/C][C]221.695833333333[/C][C]1.01280126475593[/C][C]1.02478993854549[/C][/ROW]
[ROW][C]38[/C][C]253.6[/C][C]245.143780675845[/C][C]219.854166666667[/C][C]1.11502904126225[/C][C]1.03449493721946[/C][/ROW]
[ROW][C]39[/C][C]228[/C][C]237.689343610445[/C][C]217.958333333333[/C][C]1.09052652392481[/C][C]0.959235262871837[/C][/ROW]
[ROW][C]40[/C][C]183.8[/C][C]184.614317564637[/C][C]215.791666666667[/C][C]0.855521070004111[/C][C]0.995589087697101[/C][/ROW]
[ROW][C]41[/C][C]150[/C][C]160.258014105285[/C][C]214.233333333333[/C][C]0.748053590035559[/C][C]0.93599063258986[/C][/ROW]
[ROW][C]42[/C][C]178.5[/C][C]179.43815643651[/C][C]210.95[/C][C]0.850619371588104[/C][C]0.994771700427928[/C][/ROW]
[ROW][C]43[/C][C]228.4[/C][C]223.74346052099[/C][C]206.7375[/C][C]1.08225871223648[/C][C]1.02081195789217[/C][/ROW]
[ROW][C]44[/C][C]228.7[/C][C]231.881844831678[/C][C]203.595833333333[/C][C]1.13893217280156[/C][C]0.986278163199938[/C][/ROW]
[ROW][C]45[/C][C]236.7[/C][C]234.358288262497[/C][C]201.445833333333[/C][C]1.16338116497403[/C][C]1.00999201587818[/C][/ROW]
[ROW][C]46[/C][C]218.2[/C][C]219.864835577083[/C][C]200.545833333333[/C][C]1.09633210484926[/C][C]0.99242791339182[/C][/ROW]
[ROW][C]47[/C][C]173.5[/C][C]179.390911037156[/C][C]200.420833333333[/C][C]0.895071176252415[/C][C]0.967161596966662[/C][/ROW]
[ROW][C]48[/C][C]189.1[/C][C]191.143158941286[/C][C]200.891666666667[/C][C]0.951473807315484[/C][C]0.989310844538705[/C][/ROW]
[ROW][C]49[/C][C]194.6[/C][C]203.14261367842[/C][C]200.575[/C][C]1.01280126475593[/C][C]0.957947702238668[/C][/ROW]
[ROW][C]50[/C][C]213.7[/C][C]223.335671010491[/C][C]200.295833333333[/C][C]1.11502904126225[/C][C]0.956855656031595[/C][/ROW]
[ROW][C]51[/C][C]216.3[/C][C]219.604778755359[/C][C]201.375[/C][C]1.09052652392481[/C][C]0.984951243893283[/C][/ROW]
[ROW][C]52[/C][C]173.9[/C][C]173.282228058208[/C][C]202.545833333333[/C][C]0.855521070004111[/C][C]1.00356512002826[/C][/ROW]
[ROW][C]53[/C][C]156.9[/C][C]152.627867486922[/C][C]204.033333333333[/C][C]0.748053590035559[/C][C]1.02799051433674[/C][/ROW]
[ROW][C]54[/C][C]182.9[/C][C]174.557727792024[/C][C]205.2125[/C][C]0.850619371588104[/C][C]1.04779090741784[/C][/ROW]
[ROW][C]55[/C][C]216.4[/C][C]NA[/C][C]NA[/C][C]1.08225871223648[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]234[/C][C]NA[/C][C]NA[/C][C]1.13893217280156[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]257.3[/C][C]NA[/C][C]NA[/C][C]1.16338116497403[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]225.7[/C][C]NA[/C][C]NA[/C][C]1.09633210484926[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]201.7[/C][C]NA[/C][C]NA[/C][C]0.895071176252415[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]189.2[/C][C]NA[/C][C]NA[/C][C]0.951473807315484[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167712&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167712&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	219.2	NA	NA	1.01280126475593	NA
2	232.5	NA	NA	1.11502904126225	NA
3	235.6	NA	NA	1.09052652392481	NA
4	171	NA	NA	0.855521070004111	NA
5	165.9	NA	NA	0.748053590035559	NA
6	187.6	NA	NA	0.850619371588104	NA
7	218.2	229.912335180738	212.4375	1.08225871223648	0.949057386714243
8	249.8	243.442006385613	213.745833333333	1.13893217280156	1.02611707695309
9	256.5	251.348500692639	216.05	1.16338116497403	1.02049544474371
10	224.9	239.644493968738	218.5875	1.09633210484926	0.938473470745955
11	200	197.318440804845	220.45	0.895071176252415	1.01359000803076
12	182.5	211.088428627137	221.854166666667	0.951473807315484	0.864566576135562
13	230.3	227.010963484502	224.141666666667	1.01280126475593	1.01448844789262
14	252.8	253.329952220446	227.195833333333	1.11502904126225	0.997908055420211
15	270.6	249.821451189109	229.083333333333	1.09052652392481	1.08317359743124
16	196.9	198.512970281079	232.0375	0.855521070004111	0.991874736049765
17	184.7	176.381685860509	235.7875	0.748053590035559	1.04716087216713
18	202.5	202.716773238972	238.316666666667	0.850619371588104	0.998930659582293
19	258.2	259.62484624293	239.891666666667	1.08225871223648	0.994511903373082
20	283.1	274.084027384695	240.65	1.13893217280156	1.03289492168272
21	268.5	279.23571670137	240.020833333333	1.16338116497403	0.961553210928057
22	283.8	262.055349412032	239.029166666667	1.09633210484926	1.08297732000799
23	231.1	213.343944322997	238.354166666667	0.895071176252415	1.08322737133856
24	212.1	225.368464685264	236.8625	0.951473807315484	0.941125460015918
25	238.5	238.983118434971	235.9625	1.01280126475593	0.997978441162981
26	262.8	261.246658413408	234.295833333333	1.11502904126225	1.00594588116849
27	245.5	253.656469464911	232.6	1.09052652392481	0.967844425643401
28	198.2	197.375840192198	230.708333333333	0.855521070004111	1.00417558606463
29	167.2	169.907905416743	227.133333333333	0.748053590035559	0.984062510746034
30	184.2	193.140216813842	227.058333333333	0.850619371588104	0.953711262411706
31	254.9	247.278078100832	228.483333333333	1.08225871223648	1.03082328186027
32	246.4	259.391802355555	227.75	1.13893217280156	0.949914368004016
33	264.5	263.665798776801	226.6375	1.16338116497403	1.00316385828981
34	242.4	247.012759323413	225.308333333333	1.09633210484926	0.981325825693995
35	186.7	200.488484554072	223.991666666667	0.895071176252415	0.931225553503781
36	254.7	212.214339299127	223.0375	0.951473807315484	1.20020164914958
37	230.1	224.533820391119	221.695833333333	1.01280126475593	1.02478993854549
38	253.6	245.143780675845	219.854166666667	1.11502904126225	1.03449493721946
39	228	237.689343610445	217.958333333333	1.09052652392481	0.959235262871837
40	183.8	184.614317564637	215.791666666667	0.855521070004111	0.995589087697101
41	150	160.258014105285	214.233333333333	0.748053590035559	0.93599063258986
42	178.5	179.43815643651	210.95	0.850619371588104	0.994771700427928
43	228.4	223.74346052099	206.7375	1.08225871223648	1.02081195789217
44	228.7	231.881844831678	203.595833333333	1.13893217280156	0.986278163199938
45	236.7	234.358288262497	201.445833333333	1.16338116497403	1.00999201587818
46	218.2	219.864835577083	200.545833333333	1.09633210484926	0.99242791339182
47	173.5	179.390911037156	200.420833333333	0.895071176252415	0.967161596966662
48	189.1	191.143158941286	200.891666666667	0.951473807315484	0.989310844538705
49	194.6	203.14261367842	200.575	1.01280126475593	0.957947702238668
50	213.7	223.335671010491	200.295833333333	1.11502904126225	0.956855656031595
51	216.3	219.604778755359	201.375	1.09052652392481	0.984951243893283
52	173.9	173.282228058208	202.545833333333	0.855521070004111	1.00356512002826
53	156.9	152.627867486922	204.033333333333	0.748053590035559	1.02799051433674
54	182.9	174.557727792024	205.2125	0.850619371588104	1.04779090741784
55	216.4	NA	NA	1.08225871223648	NA
56	234	NA	NA	1.13893217280156	NA
57	257.3	NA	NA	1.16338116497403	NA
58	225.7	NA	NA	1.09633210484926	NA
59	201.7	NA	NA	0.895071176252415	NA
60	189.2	NA	NA	0.951473807315484	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