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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationMon, 03 Dec 2012 05:55:09 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/03/t1354532145hi5pl3x2jn15c44.htm/, Retrieved Sun, 05 May 2024 10:27:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195685, Retrieved Sun, 05 May 2024 10:27:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2012-12-03 10:55:09] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0,9
0,9
0,9
0,9
0,9
0,91
0,91
0,91
0,91
0,91
0,92
0,92
0,92
0,92
0,92
0,93
0,93
0,93
0,93
0,93
0,92
0,93
0,93
0,93
0,94
0,95
0,95
0,96
0,97
0,97
0,97
0,98
0,98
0,98
0,98
0,98
0,98
1
1,01
1,01
1,02
1,02
1,02
1,02
1,03
1,03
1,03
1,03
1,03
1,04
1,05
1,05
1,05
1,05
1,06
1,06
1,06
1,06
1,06
1,06
1,06
1,07
1,08
1,09
1,09
1,09
1,09
1,09
1,09
1,09
1,09
1,09




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195685&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195685&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195685&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
10.9NANA0.992567921514469NA
20.9NANA0.999481897400849NA
30.9NANA1.00224605031953NA
40.9NANA1.00534813126609NA
50.9NANA1.00649309984611NA
60.91NANA1.00367099926547NA
70.910.9105480118376850.9083333333333331.002438178169930.999398151628953
80.910.9115427939482320.911.001695377965090.998307491476566
90.910.9103268709766630.9116666666666660.998530388639850.99964093010205
100.910.9115121750537250.913750.9975509439712450.998341025940069
110.920.9130773752944440.916250.9965373809489161.0075816408257
120.920.9123087275192440.9183333333333330.9934396306924621.00843055892019
130.920.9131624877933110.920.9925679215144691.00748772786671
140.920.9211891487711150.9216666666666670.9994818974008490.998709115524535
150.920.9249895839407310.9229166666666671.002246050319530.994605794457194
160.930.9291092313117410.9241666666666671.005348131266091.00095873408448
170.930.9314254894825860.9254166666666671.006493099846110.998469561442454
180.930.9296502630696390.926251.003670999265471.00037620269068
190.930.9297614102526090.92751.002438178169931.0002566139493
200.930.9311593284333820.9295833333333331.001695377965090.998754962337828
210.920.930713533078060.9320833333333330.998530388639850.988488903731067
220.930.932294486386460.9345833333333330.9975509439712450.997538882381089
230.930.9342537946396090.93750.9965373809489160.995446853238365
240.930.9346611192098250.9408333333333330.9934396306924620.995013038293745
250.940.9371495458965780.9441666666666670.9925679215144691.00304162138893
260.950.9474255485778880.9479166666666670.9994818974008491.0027173126437
270.950.9546393629293510.95251.002246050319530.995140193135223
280.960.9622019406325820.9570833333333331.005348131266090.997711560806939
290.970.9674914922270710.961251.006493099846111.00259279569183
300.970.9689607105408690.9654166666666661.003670999265471.00107258163084
310.970.9715296676763550.9691666666666671.002438178169930.99842550595494
320.980.9745661281452030.9729166666666661.001695377965091.00557568306333
330.980.9760634548954530.97750.998530388639851.00403308318204
340.980.9796781562250940.9820833333333330.9975509439712451.00032851990509
350.980.9828349919608690.986250.9965373809489160.997115495496134
360.980.9839191675649930.9904166666666670.9934396306924620.996016778924338
370.980.9871915119395990.9945833333333330.9925679215144690.992715180537291
3810.9978160942385140.9983333333333330.9994818974008491.00218868564468
391.011.004334062924361.002083333333331.002246050319531.00564148651808
401.011.01163155708651.006251.005348131266090.998387202262455
411.021.01697740296951.010416666666671.006493099846111.00297213784856
421.021.018307868004751.014583333333331.003670999265471.00166170963459
431.021.021233894010611.018751.002438178169930.998791761595604
441.021.024233523969311.02251.001695377965090.995866641864154
451.031.024325757013051.025833333333330.998530388639851.00553949068263
461.031.026646179837071.029166666666670.9975509439712451.00326677313839
471.031.028509621921031.032083333333330.9965373809489161.00144906576196
481.031.027796084587241.034583333333330.9934396306924621.00214431193678
491.031.029789218571261.03750.9925679215144691.00020468405081
501.041.040294074878051.040833333333330.9994818974008490.999717315627233
511.051.046094315021011.043751.002246050319531.00373358780648
521.051.051845482337141.046251.005348131266090.998245481519737
531.051.055559638463611.048751.006493099846110.994732994459983
541.051.055109137977821.051251.003670999265470.995157716113033
551.061.056319230246561.053751.002438178169931.00348452404164
561.061.058040742975631.056251.001695377965091.00185177842855
571.061.057194048972441.058750.998530388639851.00265414947264
581.061.059066585516141.061666666666670.9975509439712451.00088135580579
591.061.06131231071061.0650.9965373809489160.998763501848276
601.061.061324672123111.068333333333330.9934396306924620.998751869095379
611.061.063288385922381.071250.9925679215144690.996907343326691
621.071.073193687334161.073750.9994818974008490.997024127730294
631.081.078667311656391.076251.002246050319531.00123549525345
641.091.084519296603291.078751.005348131266091.00505357849683
651.091.08827066420861.081251.006493099846111.00158906772761
661.091.087728445453951.083751.003670999265471.00208834710129
671.09NANA1.00243817816993NA
681.09NANA1.00169537796509NA
691.09NANA0.99853038863985NA
701.09NANA0.997550943971245NA
711.09NANA0.996537380948916NA
721.09NANA0.993439630692462NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 0.9 & NA & NA & 0.992567921514469 & NA \tabularnewline
2 & 0.9 & NA & NA & 0.999481897400849 & NA \tabularnewline
3 & 0.9 & NA & NA & 1.00224605031953 & NA \tabularnewline
4 & 0.9 & NA & NA & 1.00534813126609 & NA \tabularnewline
5 & 0.9 & NA & NA & 1.00649309984611 & NA \tabularnewline
6 & 0.91 & NA & NA & 1.00367099926547 & NA \tabularnewline
7 & 0.91 & 0.910548011837685 & 0.908333333333333 & 1.00243817816993 & 0.999398151628953 \tabularnewline
8 & 0.91 & 0.911542793948232 & 0.91 & 1.00169537796509 & 0.998307491476566 \tabularnewline
9 & 0.91 & 0.910326870976663 & 0.911666666666666 & 0.99853038863985 & 0.99964093010205 \tabularnewline
10 & 0.91 & 0.911512175053725 & 0.91375 & 0.997550943971245 & 0.998341025940069 \tabularnewline
11 & 0.92 & 0.913077375294444 & 0.91625 & 0.996537380948916 & 1.0075816408257 \tabularnewline
12 & 0.92 & 0.912308727519244 & 0.918333333333333 & 0.993439630692462 & 1.00843055892019 \tabularnewline
13 & 0.92 & 0.913162487793311 & 0.92 & 0.992567921514469 & 1.00748772786671 \tabularnewline
14 & 0.92 & 0.921189148771115 & 0.921666666666667 & 0.999481897400849 & 0.998709115524535 \tabularnewline
15 & 0.92 & 0.924989583940731 & 0.922916666666667 & 1.00224605031953 & 0.994605794457194 \tabularnewline
16 & 0.93 & 0.929109231311741 & 0.924166666666667 & 1.00534813126609 & 1.00095873408448 \tabularnewline
17 & 0.93 & 0.931425489482586 & 0.925416666666667 & 1.00649309984611 & 0.998469561442454 \tabularnewline
18 & 0.93 & 0.929650263069639 & 0.92625 & 1.00367099926547 & 1.00037620269068 \tabularnewline
19 & 0.93 & 0.929761410252609 & 0.9275 & 1.00243817816993 & 1.0002566139493 \tabularnewline
20 & 0.93 & 0.931159328433382 & 0.929583333333333 & 1.00169537796509 & 0.998754962337828 \tabularnewline
21 & 0.92 & 0.93071353307806 & 0.932083333333333 & 0.99853038863985 & 0.988488903731067 \tabularnewline
22 & 0.93 & 0.93229448638646 & 0.934583333333333 & 0.997550943971245 & 0.997538882381089 \tabularnewline
23 & 0.93 & 0.934253794639609 & 0.9375 & 0.996537380948916 & 0.995446853238365 \tabularnewline
24 & 0.93 & 0.934661119209825 & 0.940833333333333 & 0.993439630692462 & 0.995013038293745 \tabularnewline
25 & 0.94 & 0.937149545896578 & 0.944166666666667 & 0.992567921514469 & 1.00304162138893 \tabularnewline
26 & 0.95 & 0.947425548577888 & 0.947916666666667 & 0.999481897400849 & 1.0027173126437 \tabularnewline
27 & 0.95 & 0.954639362929351 & 0.9525 & 1.00224605031953 & 0.995140193135223 \tabularnewline
28 & 0.96 & 0.962201940632582 & 0.957083333333333 & 1.00534813126609 & 0.997711560806939 \tabularnewline
29 & 0.97 & 0.967491492227071 & 0.96125 & 1.00649309984611 & 1.00259279569183 \tabularnewline
30 & 0.97 & 0.968960710540869 & 0.965416666666666 & 1.00367099926547 & 1.00107258163084 \tabularnewline
31 & 0.97 & 0.971529667676355 & 0.969166666666667 & 1.00243817816993 & 0.99842550595494 \tabularnewline
32 & 0.98 & 0.974566128145203 & 0.972916666666666 & 1.00169537796509 & 1.00557568306333 \tabularnewline
33 & 0.98 & 0.976063454895453 & 0.9775 & 0.99853038863985 & 1.00403308318204 \tabularnewline
34 & 0.98 & 0.979678156225094 & 0.982083333333333 & 0.997550943971245 & 1.00032851990509 \tabularnewline
35 & 0.98 & 0.982834991960869 & 0.98625 & 0.996537380948916 & 0.997115495496134 \tabularnewline
36 & 0.98 & 0.983919167564993 & 0.990416666666667 & 0.993439630692462 & 0.996016778924338 \tabularnewline
37 & 0.98 & 0.987191511939599 & 0.994583333333333 & 0.992567921514469 & 0.992715180537291 \tabularnewline
38 & 1 & 0.997816094238514 & 0.998333333333333 & 0.999481897400849 & 1.00218868564468 \tabularnewline
39 & 1.01 & 1.00433406292436 & 1.00208333333333 & 1.00224605031953 & 1.00564148651808 \tabularnewline
40 & 1.01 & 1.0116315570865 & 1.00625 & 1.00534813126609 & 0.998387202262455 \tabularnewline
41 & 1.02 & 1.0169774029695 & 1.01041666666667 & 1.00649309984611 & 1.00297213784856 \tabularnewline
42 & 1.02 & 1.01830786800475 & 1.01458333333333 & 1.00367099926547 & 1.00166170963459 \tabularnewline
43 & 1.02 & 1.02123389401061 & 1.01875 & 1.00243817816993 & 0.998791761595604 \tabularnewline
44 & 1.02 & 1.02423352396931 & 1.0225 & 1.00169537796509 & 0.995866641864154 \tabularnewline
45 & 1.03 & 1.02432575701305 & 1.02583333333333 & 0.99853038863985 & 1.00553949068263 \tabularnewline
46 & 1.03 & 1.02664617983707 & 1.02916666666667 & 0.997550943971245 & 1.00326677313839 \tabularnewline
47 & 1.03 & 1.02850962192103 & 1.03208333333333 & 0.996537380948916 & 1.00144906576196 \tabularnewline
48 & 1.03 & 1.02779608458724 & 1.03458333333333 & 0.993439630692462 & 1.00214431193678 \tabularnewline
49 & 1.03 & 1.02978921857126 & 1.0375 & 0.992567921514469 & 1.00020468405081 \tabularnewline
50 & 1.04 & 1.04029407487805 & 1.04083333333333 & 0.999481897400849 & 0.999717315627233 \tabularnewline
51 & 1.05 & 1.04609431502101 & 1.04375 & 1.00224605031953 & 1.00373358780648 \tabularnewline
52 & 1.05 & 1.05184548233714 & 1.04625 & 1.00534813126609 & 0.998245481519737 \tabularnewline
53 & 1.05 & 1.05555963846361 & 1.04875 & 1.00649309984611 & 0.994732994459983 \tabularnewline
54 & 1.05 & 1.05510913797782 & 1.05125 & 1.00367099926547 & 0.995157716113033 \tabularnewline
55 & 1.06 & 1.05631923024656 & 1.05375 & 1.00243817816993 & 1.00348452404164 \tabularnewline
56 & 1.06 & 1.05804074297563 & 1.05625 & 1.00169537796509 & 1.00185177842855 \tabularnewline
57 & 1.06 & 1.05719404897244 & 1.05875 & 0.99853038863985 & 1.00265414947264 \tabularnewline
58 & 1.06 & 1.05906658551614 & 1.06166666666667 & 0.997550943971245 & 1.00088135580579 \tabularnewline
59 & 1.06 & 1.0613123107106 & 1.065 & 0.996537380948916 & 0.998763501848276 \tabularnewline
60 & 1.06 & 1.06132467212311 & 1.06833333333333 & 0.993439630692462 & 0.998751869095379 \tabularnewline
61 & 1.06 & 1.06328838592238 & 1.07125 & 0.992567921514469 & 0.996907343326691 \tabularnewline
62 & 1.07 & 1.07319368733416 & 1.07375 & 0.999481897400849 & 0.997024127730294 \tabularnewline
63 & 1.08 & 1.07866731165639 & 1.07625 & 1.00224605031953 & 1.00123549525345 \tabularnewline
64 & 1.09 & 1.08451929660329 & 1.07875 & 1.00534813126609 & 1.00505357849683 \tabularnewline
65 & 1.09 & 1.0882706642086 & 1.08125 & 1.00649309984611 & 1.00158906772761 \tabularnewline
66 & 1.09 & 1.08772844545395 & 1.08375 & 1.00367099926547 & 1.00208834710129 \tabularnewline
67 & 1.09 & NA & NA & 1.00243817816993 & NA \tabularnewline
68 & 1.09 & NA & NA & 1.00169537796509 & NA \tabularnewline
69 & 1.09 & NA & NA & 0.99853038863985 & NA \tabularnewline
70 & 1.09 & NA & NA & 0.997550943971245 & NA \tabularnewline
71 & 1.09 & NA & NA & 0.996537380948916 & NA \tabularnewline
72 & 1.09 & NA & NA & 0.993439630692462 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195685&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]0.9[/C][C]NA[/C][C]NA[/C][C]0.992567921514469[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]0.9[/C][C]NA[/C][C]NA[/C][C]0.999481897400849[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]0.9[/C][C]NA[/C][C]NA[/C][C]1.00224605031953[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]0.9[/C][C]NA[/C][C]NA[/C][C]1.00534813126609[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]0.9[/C][C]NA[/C][C]NA[/C][C]1.00649309984611[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]0.91[/C][C]NA[/C][C]NA[/C][C]1.00367099926547[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]0.91[/C][C]0.910548011837685[/C][C]0.908333333333333[/C][C]1.00243817816993[/C][C]0.999398151628953[/C][/ROW]
[ROW][C]8[/C][C]0.91[/C][C]0.911542793948232[/C][C]0.91[/C][C]1.00169537796509[/C][C]0.998307491476566[/C][/ROW]
[ROW][C]9[/C][C]0.91[/C][C]0.910326870976663[/C][C]0.911666666666666[/C][C]0.99853038863985[/C][C]0.99964093010205[/C][/ROW]
[ROW][C]10[/C][C]0.91[/C][C]0.911512175053725[/C][C]0.91375[/C][C]0.997550943971245[/C][C]0.998341025940069[/C][/ROW]
[ROW][C]11[/C][C]0.92[/C][C]0.913077375294444[/C][C]0.91625[/C][C]0.996537380948916[/C][C]1.0075816408257[/C][/ROW]
[ROW][C]12[/C][C]0.92[/C][C]0.912308727519244[/C][C]0.918333333333333[/C][C]0.993439630692462[/C][C]1.00843055892019[/C][/ROW]
[ROW][C]13[/C][C]0.92[/C][C]0.913162487793311[/C][C]0.92[/C][C]0.992567921514469[/C][C]1.00748772786671[/C][/ROW]
[ROW][C]14[/C][C]0.92[/C][C]0.921189148771115[/C][C]0.921666666666667[/C][C]0.999481897400849[/C][C]0.998709115524535[/C][/ROW]
[ROW][C]15[/C][C]0.92[/C][C]0.924989583940731[/C][C]0.922916666666667[/C][C]1.00224605031953[/C][C]0.994605794457194[/C][/ROW]
[ROW][C]16[/C][C]0.93[/C][C]0.929109231311741[/C][C]0.924166666666667[/C][C]1.00534813126609[/C][C]1.00095873408448[/C][/ROW]
[ROW][C]17[/C][C]0.93[/C][C]0.931425489482586[/C][C]0.925416666666667[/C][C]1.00649309984611[/C][C]0.998469561442454[/C][/ROW]
[ROW][C]18[/C][C]0.93[/C][C]0.929650263069639[/C][C]0.92625[/C][C]1.00367099926547[/C][C]1.00037620269068[/C][/ROW]
[ROW][C]19[/C][C]0.93[/C][C]0.929761410252609[/C][C]0.9275[/C][C]1.00243817816993[/C][C]1.0002566139493[/C][/ROW]
[ROW][C]20[/C][C]0.93[/C][C]0.931159328433382[/C][C]0.929583333333333[/C][C]1.00169537796509[/C][C]0.998754962337828[/C][/ROW]
[ROW][C]21[/C][C]0.92[/C][C]0.93071353307806[/C][C]0.932083333333333[/C][C]0.99853038863985[/C][C]0.988488903731067[/C][/ROW]
[ROW][C]22[/C][C]0.93[/C][C]0.93229448638646[/C][C]0.934583333333333[/C][C]0.997550943971245[/C][C]0.997538882381089[/C][/ROW]
[ROW][C]23[/C][C]0.93[/C][C]0.934253794639609[/C][C]0.9375[/C][C]0.996537380948916[/C][C]0.995446853238365[/C][/ROW]
[ROW][C]24[/C][C]0.93[/C][C]0.934661119209825[/C][C]0.940833333333333[/C][C]0.993439630692462[/C][C]0.995013038293745[/C][/ROW]
[ROW][C]25[/C][C]0.94[/C][C]0.937149545896578[/C][C]0.944166666666667[/C][C]0.992567921514469[/C][C]1.00304162138893[/C][/ROW]
[ROW][C]26[/C][C]0.95[/C][C]0.947425548577888[/C][C]0.947916666666667[/C][C]0.999481897400849[/C][C]1.0027173126437[/C][/ROW]
[ROW][C]27[/C][C]0.95[/C][C]0.954639362929351[/C][C]0.9525[/C][C]1.00224605031953[/C][C]0.995140193135223[/C][/ROW]
[ROW][C]28[/C][C]0.96[/C][C]0.962201940632582[/C][C]0.957083333333333[/C][C]1.00534813126609[/C][C]0.997711560806939[/C][/ROW]
[ROW][C]29[/C][C]0.97[/C][C]0.967491492227071[/C][C]0.96125[/C][C]1.00649309984611[/C][C]1.00259279569183[/C][/ROW]
[ROW][C]30[/C][C]0.97[/C][C]0.968960710540869[/C][C]0.965416666666666[/C][C]1.00367099926547[/C][C]1.00107258163084[/C][/ROW]
[ROW][C]31[/C][C]0.97[/C][C]0.971529667676355[/C][C]0.969166666666667[/C][C]1.00243817816993[/C][C]0.99842550595494[/C][/ROW]
[ROW][C]32[/C][C]0.98[/C][C]0.974566128145203[/C][C]0.972916666666666[/C][C]1.00169537796509[/C][C]1.00557568306333[/C][/ROW]
[ROW][C]33[/C][C]0.98[/C][C]0.976063454895453[/C][C]0.9775[/C][C]0.99853038863985[/C][C]1.00403308318204[/C][/ROW]
[ROW][C]34[/C][C]0.98[/C][C]0.979678156225094[/C][C]0.982083333333333[/C][C]0.997550943971245[/C][C]1.00032851990509[/C][/ROW]
[ROW][C]35[/C][C]0.98[/C][C]0.982834991960869[/C][C]0.98625[/C][C]0.996537380948916[/C][C]0.997115495496134[/C][/ROW]
[ROW][C]36[/C][C]0.98[/C][C]0.983919167564993[/C][C]0.990416666666667[/C][C]0.993439630692462[/C][C]0.996016778924338[/C][/ROW]
[ROW][C]37[/C][C]0.98[/C][C]0.987191511939599[/C][C]0.994583333333333[/C][C]0.992567921514469[/C][C]0.992715180537291[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.997816094238514[/C][C]0.998333333333333[/C][C]0.999481897400849[/C][C]1.00218868564468[/C][/ROW]
[ROW][C]39[/C][C]1.01[/C][C]1.00433406292436[/C][C]1.00208333333333[/C][C]1.00224605031953[/C][C]1.00564148651808[/C][/ROW]
[ROW][C]40[/C][C]1.01[/C][C]1.0116315570865[/C][C]1.00625[/C][C]1.00534813126609[/C][C]0.998387202262455[/C][/ROW]
[ROW][C]41[/C][C]1.02[/C][C]1.0169774029695[/C][C]1.01041666666667[/C][C]1.00649309984611[/C][C]1.00297213784856[/C][/ROW]
[ROW][C]42[/C][C]1.02[/C][C]1.01830786800475[/C][C]1.01458333333333[/C][C]1.00367099926547[/C][C]1.00166170963459[/C][/ROW]
[ROW][C]43[/C][C]1.02[/C][C]1.02123389401061[/C][C]1.01875[/C][C]1.00243817816993[/C][C]0.998791761595604[/C][/ROW]
[ROW][C]44[/C][C]1.02[/C][C]1.02423352396931[/C][C]1.0225[/C][C]1.00169537796509[/C][C]0.995866641864154[/C][/ROW]
[ROW][C]45[/C][C]1.03[/C][C]1.02432575701305[/C][C]1.02583333333333[/C][C]0.99853038863985[/C][C]1.00553949068263[/C][/ROW]
[ROW][C]46[/C][C]1.03[/C][C]1.02664617983707[/C][C]1.02916666666667[/C][C]0.997550943971245[/C][C]1.00326677313839[/C][/ROW]
[ROW][C]47[/C][C]1.03[/C][C]1.02850962192103[/C][C]1.03208333333333[/C][C]0.996537380948916[/C][C]1.00144906576196[/C][/ROW]
[ROW][C]48[/C][C]1.03[/C][C]1.02779608458724[/C][C]1.03458333333333[/C][C]0.993439630692462[/C][C]1.00214431193678[/C][/ROW]
[ROW][C]49[/C][C]1.03[/C][C]1.02978921857126[/C][C]1.0375[/C][C]0.992567921514469[/C][C]1.00020468405081[/C][/ROW]
[ROW][C]50[/C][C]1.04[/C][C]1.04029407487805[/C][C]1.04083333333333[/C][C]0.999481897400849[/C][C]0.999717315627233[/C][/ROW]
[ROW][C]51[/C][C]1.05[/C][C]1.04609431502101[/C][C]1.04375[/C][C]1.00224605031953[/C][C]1.00373358780648[/C][/ROW]
[ROW][C]52[/C][C]1.05[/C][C]1.05184548233714[/C][C]1.04625[/C][C]1.00534813126609[/C][C]0.998245481519737[/C][/ROW]
[ROW][C]53[/C][C]1.05[/C][C]1.05555963846361[/C][C]1.04875[/C][C]1.00649309984611[/C][C]0.994732994459983[/C][/ROW]
[ROW][C]54[/C][C]1.05[/C][C]1.05510913797782[/C][C]1.05125[/C][C]1.00367099926547[/C][C]0.995157716113033[/C][/ROW]
[ROW][C]55[/C][C]1.06[/C][C]1.05631923024656[/C][C]1.05375[/C][C]1.00243817816993[/C][C]1.00348452404164[/C][/ROW]
[ROW][C]56[/C][C]1.06[/C][C]1.05804074297563[/C][C]1.05625[/C][C]1.00169537796509[/C][C]1.00185177842855[/C][/ROW]
[ROW][C]57[/C][C]1.06[/C][C]1.05719404897244[/C][C]1.05875[/C][C]0.99853038863985[/C][C]1.00265414947264[/C][/ROW]
[ROW][C]58[/C][C]1.06[/C][C]1.05906658551614[/C][C]1.06166666666667[/C][C]0.997550943971245[/C][C]1.00088135580579[/C][/ROW]
[ROW][C]59[/C][C]1.06[/C][C]1.0613123107106[/C][C]1.065[/C][C]0.996537380948916[/C][C]0.998763501848276[/C][/ROW]
[ROW][C]60[/C][C]1.06[/C][C]1.06132467212311[/C][C]1.06833333333333[/C][C]0.993439630692462[/C][C]0.998751869095379[/C][/ROW]
[ROW][C]61[/C][C]1.06[/C][C]1.06328838592238[/C][C]1.07125[/C][C]0.992567921514469[/C][C]0.996907343326691[/C][/ROW]
[ROW][C]62[/C][C]1.07[/C][C]1.07319368733416[/C][C]1.07375[/C][C]0.999481897400849[/C][C]0.997024127730294[/C][/ROW]
[ROW][C]63[/C][C]1.08[/C][C]1.07866731165639[/C][C]1.07625[/C][C]1.00224605031953[/C][C]1.00123549525345[/C][/ROW]
[ROW][C]64[/C][C]1.09[/C][C]1.08451929660329[/C][C]1.07875[/C][C]1.00534813126609[/C][C]1.00505357849683[/C][/ROW]
[ROW][C]65[/C][C]1.09[/C][C]1.0882706642086[/C][C]1.08125[/C][C]1.00649309984611[/C][C]1.00158906772761[/C][/ROW]
[ROW][C]66[/C][C]1.09[/C][C]1.08772844545395[/C][C]1.08375[/C][C]1.00367099926547[/C][C]1.00208834710129[/C][/ROW]
[ROW][C]67[/C][C]1.09[/C][C]NA[/C][C]NA[/C][C]1.00243817816993[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.09[/C][C]NA[/C][C]NA[/C][C]1.00169537796509[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.09[/C][C]NA[/C][C]NA[/C][C]0.99853038863985[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.09[/C][C]NA[/C][C]NA[/C][C]0.997550943971245[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.09[/C][C]NA[/C][C]NA[/C][C]0.996537380948916[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.09[/C][C]NA[/C][C]NA[/C][C]0.993439630692462[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195685&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195685&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
tObservationsFitTrendSeasonalRandom
10.9NANA0.992567921514469NA
20.9NANA0.999481897400849NA
30.9NANA1.00224605031953NA
40.9NANA1.00534813126609NA
50.9NANA1.00649309984611NA
60.91NANA1.00367099926547NA
70.910.9105480118376850.9083333333333331.002438178169930.999398151628953
80.910.9115427939482320.911.001695377965090.998307491476566
90.910.9103268709766630.9116666666666660.998530388639850.99964093010205
100.910.9115121750537250.913750.9975509439712450.998341025940069
110.920.9130773752944440.916250.9965373809489161.0075816408257
120.920.9123087275192440.9183333333333330.9934396306924621.00843055892019
130.920.9131624877933110.920.9925679215144691.00748772786671
140.920.9211891487711150.9216666666666670.9994818974008490.998709115524535
150.920.9249895839407310.9229166666666671.002246050319530.994605794457194
160.930.9291092313117410.9241666666666671.005348131266091.00095873408448
170.930.9314254894825860.9254166666666671.006493099846110.998469561442454
180.930.9296502630696390.926251.003670999265471.00037620269068
190.930.9297614102526090.92751.002438178169931.0002566139493
200.930.9311593284333820.9295833333333331.001695377965090.998754962337828
210.920.930713533078060.9320833333333330.998530388639850.988488903731067
220.930.932294486386460.9345833333333330.9975509439712450.997538882381089
230.930.9342537946396090.93750.9965373809489160.995446853238365
240.930.9346611192098250.9408333333333330.9934396306924620.995013038293745
250.940.9371495458965780.9441666666666670.9925679215144691.00304162138893
260.950.9474255485778880.9479166666666670.9994818974008491.0027173126437
270.950.9546393629293510.95251.002246050319530.995140193135223
280.960.9622019406325820.9570833333333331.005348131266090.997711560806939
290.970.9674914922270710.961251.006493099846111.00259279569183
300.970.9689607105408690.9654166666666661.003670999265471.00107258163084
310.970.9715296676763550.9691666666666671.002438178169930.99842550595494
320.980.9745661281452030.9729166666666661.001695377965091.00557568306333
330.980.9760634548954530.97750.998530388639851.00403308318204
340.980.9796781562250940.9820833333333330.9975509439712451.00032851990509
350.980.9828349919608690.986250.9965373809489160.997115495496134
360.980.9839191675649930.9904166666666670.9934396306924620.996016778924338
370.980.9871915119395990.9945833333333330.9925679215144690.992715180537291
3810.9978160942385140.9983333333333330.9994818974008491.00218868564468
391.011.004334062924361.002083333333331.002246050319531.00564148651808
401.011.01163155708651.006251.005348131266090.998387202262455
411.021.01697740296951.010416666666671.006493099846111.00297213784856
421.021.018307868004751.014583333333331.003670999265471.00166170963459
431.021.021233894010611.018751.002438178169930.998791761595604
441.021.024233523969311.02251.001695377965090.995866641864154
451.031.024325757013051.025833333333330.998530388639851.00553949068263
461.031.026646179837071.029166666666670.9975509439712451.00326677313839
471.031.028509621921031.032083333333330.9965373809489161.00144906576196
481.031.027796084587241.034583333333330.9934396306924621.00214431193678
491.031.029789218571261.03750.9925679215144691.00020468405081
501.041.040294074878051.040833333333330.9994818974008490.999717315627233
511.051.046094315021011.043751.002246050319531.00373358780648
521.051.051845482337141.046251.005348131266090.998245481519737
531.051.055559638463611.048751.006493099846110.994732994459983
541.051.055109137977821.051251.003670999265470.995157716113033
551.061.056319230246561.053751.002438178169931.00348452404164
561.061.058040742975631.056251.001695377965091.00185177842855
571.061.057194048972441.058750.998530388639851.00265414947264
581.061.059066585516141.061666666666670.9975509439712451.00088135580579
591.061.06131231071061.0650.9965373809489160.998763501848276
601.061.061324672123111.068333333333330.9934396306924620.998751869095379
611.061.063288385922381.071250.9925679215144690.996907343326691
621.071.073193687334161.073750.9994818974008490.997024127730294
631.081.078667311656391.076251.002246050319531.00123549525345
641.091.084519296603291.078751.005348131266091.00505357849683
651.091.08827066420861.081251.006493099846111.00158906772761
661.091.087728445453951.083751.003670999265471.00208834710129
671.09NANA1.00243817816993NA
681.09NANA1.00169537796509NA
691.09NANA0.99853038863985NA
701.09NANA0.997550943971245NA
711.09NANA0.996537380948916NA
721.09NANA0.993439630692462NA



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')