Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationFri, 29 May 2009 05:31:54 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/May/29/t1243596922gvssfhkqr4nrup6.htm/, Retrieved Sun, 28 Apr 2024 17:29:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40760, Retrieved Sun, 28 Apr 2024 17:29:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Classical Decompo...] [2009-05-29 11:31:54] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message
Dataseries X:
5,11
5,11
5,11
5,1
5,1
5,1
5,1
5,1
5,12
5,25
5,26
5,26
5,26
5,26
5,26
5,26
5,29
5,3
5,33
5,33
5,35
5,38
5,38
5,38
5,38
5,38
5,39
5,39
5,4
5,4
5,4
5,4
5,4
5,41
5,41
5,41
5,41
5,41
5,42
5,42
5,42
5,42
5,43
5,43
5,45
5,51
5,51
5,51
5,51
5,51
5,51
5,53
5,53
5,53
5,53
5,52
5,53
5,54
5,54
5,57
5,56
5,57
5,58
5,61
5,66
5,68
5,69
5,7
5,72
5,71
5,69
5,7
5,7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40760&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40760&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40760&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
15.11NANA1.00069597627142NA
25.11NANA0.99921889698968NA
35.11NANA0.998475750820238NA
45.1NANA0.99865084599588NA
55.1NANA1.00057505922897NA
65.1NANA1.00033487139641NA
75.15.153935493421385.149583333333331.000845148006420.989535085666046
85.15.144625892544355.162083333333330.9966181404557630.991325726403347
95.125.159135035149015.174583333333330.9970145812350130.992414419300448
105.255.189202969520375.18751.000328283281031.01171606330235
115.265.221564654085955.202083333333331.003744907473471.00736088671888
125.265.236584656876525.218333333333331.003497538845711.00447149137420
135.265.239894305751215.236251.000695976271421.00383704194696
145.265.251311644887855.255416666666670.999218896989681.00165451142490
155.265.266543554013915.274583333333330.9984757508202380.998757523991437
165.265.282446870799045.289583333333330.998650845995880.995750667948384
175.295.303047813913555.31.000575059228970.997539563215078
185.35.311778167114915.311.000334871396410.99778263196535
195.335.324496187394145.321.000845148006421.00103367763111
205.335.311974688629225.330.9966181404557631.00339333532770
215.355.324473286537155.340416666666670.9970145812350131.00479422321967
225.385.353006725907635.351251.000328283281031.0050426378061
235.385.381327385192145.361251.003744907473470.999753334986495
245.385.388781783601455.371.003497538845710.998370358282427
255.385.380825655742775.377083333333331.000695976271420.999846555938514
265.385.378712054254035.382916666666670.999218896989681.00023945244382
275.395.379704139106875.387916666666670.9984757508202381.00191383403750
285.395.383976373475295.391250.998650845995881.00111880627010
295.45.396851725716275.393751.000575059228971.00058335385957
305.45.398057049772855.396251.000334871396411.00035993510429
315.45.403312742799645.398751.000845148006420.999386905226972
325.45.382983731136695.401250.9966181404557631.00316112210499
335.45.38761754334875.403750.9970145812350131.00229831767969
345.415.408024781488095.406251.000328283281031.00036523843579
355.415.428587041252355.408333333333331.003744907473470.99657608119551
365.415.428921685155285.411.003497538845710.996514651296772
375.415.415850014912275.412083333333331.000695976271420.998919834394203
385.415.410353985992045.414583333333330.999218896989680.999934572489535
395.425.409658411631485.417916666666670.9984757508202381.00191168971894
405.425.416848630489325.424166666666670.998650845995881.00058177175063
415.425.43562400926145.43251.000575059228970.997125627299686
425.425.442655312789285.440833333333331.000334871396410.995837452220051
435.435.453772019011635.449166666666671.000845148006420.99564117844883
445.435.439043501537335.45750.9966181404557630.998337299281616
455.455.449100109191525.465416666666670.9970145812350131.00016514484785
465.515.475546940609565.473751.000328283281031.00629216766181
475.515.503449682268085.482916666666671.003744907473471.00119022033635
485.515.511292108135535.492083333333331.003497538845710.999765552594531
495.515.504661782806355.500833333333331.000695976271421.00096976297623
505.515.50444709879195.508750.999218896989681.00100880272050
515.515.50742582889935.515833333333330.9984757508202381.00046740004871
525.535.512968774416435.520416666666670.998650845995881.00308930202228
535.535.526092670866685.522916666666671.000575059228971.00070706905693
545.535.52851738925085.526666666666671.000334871396411.00026817510823
555.535.535924724910495.531251.000845148006420.99892976779763
565.525.51711192253975.535833333333330.9966181404557631.00052347632255
575.535.524707048268525.541250.9970145812350131.00095805111208
585.545.549321151501545.54751.000328283281030.998320307791338
595.545.577057642149475.556251.003744907473470.993355341736222
605.575.5873906714985.567916666666671.003497538845710.996887514670003
615.565.584717460908075.580833333333331.000695976271420.995574089274688
625.575.590629728657265.5950.999218896989680.99630994545185
635.585.601864993664385.610416666666670.9984757508202380.996096836733997
645.615.617827113245995.625416666666670.998650845995880.998606736539197
655.665.641992615227375.638751.000575059228971.00319167109933
665.685.65230882958615.650416666666671.000334871396411.00489909013268
675.695.6664516129635.661666666666671.000845148006421.00415575542605
685.7NANA0.996618140455763NA
695.72NANA0.997014581235013NA
705.71NANA1.00032828328103NA
715.69NANA1.00374490747347NA
725.7NANA1.00349753884571NA
735.7NANANANA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 5.11 & NA & NA & 1.00069597627142 & NA \tabularnewline
2 & 5.11 & NA & NA & 0.99921889698968 & NA \tabularnewline
3 & 5.11 & NA & NA & 0.998475750820238 & NA \tabularnewline
4 & 5.1 & NA & NA & 0.99865084599588 & NA \tabularnewline
5 & 5.1 & NA & NA & 1.00057505922897 & NA \tabularnewline
6 & 5.1 & NA & NA & 1.00033487139641 & NA \tabularnewline
7 & 5.1 & 5.15393549342138 & 5.14958333333333 & 1.00084514800642 & 0.989535085666046 \tabularnewline
8 & 5.1 & 5.14462589254435 & 5.16208333333333 & 0.996618140455763 & 0.991325726403347 \tabularnewline
9 & 5.12 & 5.15913503514901 & 5.17458333333333 & 0.997014581235013 & 0.992414419300448 \tabularnewline
10 & 5.25 & 5.18920296952037 & 5.1875 & 1.00032828328103 & 1.01171606330235 \tabularnewline
11 & 5.26 & 5.22156465408595 & 5.20208333333333 & 1.00374490747347 & 1.00736088671888 \tabularnewline
12 & 5.26 & 5.23658465687652 & 5.21833333333333 & 1.00349753884571 & 1.00447149137420 \tabularnewline
13 & 5.26 & 5.23989430575121 & 5.23625 & 1.00069597627142 & 1.00383704194696 \tabularnewline
14 & 5.26 & 5.25131164488785 & 5.25541666666667 & 0.99921889698968 & 1.00165451142490 \tabularnewline
15 & 5.26 & 5.26654355401391 & 5.27458333333333 & 0.998475750820238 & 0.998757523991437 \tabularnewline
16 & 5.26 & 5.28244687079904 & 5.28958333333333 & 0.99865084599588 & 0.995750667948384 \tabularnewline
17 & 5.29 & 5.30304781391355 & 5.3 & 1.00057505922897 & 0.997539563215078 \tabularnewline
18 & 5.3 & 5.31177816711491 & 5.31 & 1.00033487139641 & 0.99778263196535 \tabularnewline
19 & 5.33 & 5.32449618739414 & 5.32 & 1.00084514800642 & 1.00103367763111 \tabularnewline
20 & 5.33 & 5.31197468862922 & 5.33 & 0.996618140455763 & 1.00339333532770 \tabularnewline
21 & 5.35 & 5.32447328653715 & 5.34041666666667 & 0.997014581235013 & 1.00479422321967 \tabularnewline
22 & 5.38 & 5.35300672590763 & 5.35125 & 1.00032828328103 & 1.0050426378061 \tabularnewline
23 & 5.38 & 5.38132738519214 & 5.36125 & 1.00374490747347 & 0.999753334986495 \tabularnewline
24 & 5.38 & 5.38878178360145 & 5.37 & 1.00349753884571 & 0.998370358282427 \tabularnewline
25 & 5.38 & 5.38082565574277 & 5.37708333333333 & 1.00069597627142 & 0.999846555938514 \tabularnewline
26 & 5.38 & 5.37871205425403 & 5.38291666666667 & 0.99921889698968 & 1.00023945244382 \tabularnewline
27 & 5.39 & 5.37970413910687 & 5.38791666666667 & 0.998475750820238 & 1.00191383403750 \tabularnewline
28 & 5.39 & 5.38397637347529 & 5.39125 & 0.99865084599588 & 1.00111880627010 \tabularnewline
29 & 5.4 & 5.39685172571627 & 5.39375 & 1.00057505922897 & 1.00058335385957 \tabularnewline
30 & 5.4 & 5.39805704977285 & 5.39625 & 1.00033487139641 & 1.00035993510429 \tabularnewline
31 & 5.4 & 5.40331274279964 & 5.39875 & 1.00084514800642 & 0.999386905226972 \tabularnewline
32 & 5.4 & 5.38298373113669 & 5.40125 & 0.996618140455763 & 1.00316112210499 \tabularnewline
33 & 5.4 & 5.3876175433487 & 5.40375 & 0.997014581235013 & 1.00229831767969 \tabularnewline
34 & 5.41 & 5.40802478148809 & 5.40625 & 1.00032828328103 & 1.00036523843579 \tabularnewline
35 & 5.41 & 5.42858704125235 & 5.40833333333333 & 1.00374490747347 & 0.99657608119551 \tabularnewline
36 & 5.41 & 5.42892168515528 & 5.41 & 1.00349753884571 & 0.996514651296772 \tabularnewline
37 & 5.41 & 5.41585001491227 & 5.41208333333333 & 1.00069597627142 & 0.998919834394203 \tabularnewline
38 & 5.41 & 5.41035398599204 & 5.41458333333333 & 0.99921889698968 & 0.999934572489535 \tabularnewline
39 & 5.42 & 5.40965841163148 & 5.41791666666667 & 0.998475750820238 & 1.00191168971894 \tabularnewline
40 & 5.42 & 5.41684863048932 & 5.42416666666667 & 0.99865084599588 & 1.00058177175063 \tabularnewline
41 & 5.42 & 5.4356240092614 & 5.4325 & 1.00057505922897 & 0.997125627299686 \tabularnewline
42 & 5.42 & 5.44265531278928 & 5.44083333333333 & 1.00033487139641 & 0.995837452220051 \tabularnewline
43 & 5.43 & 5.45377201901163 & 5.44916666666667 & 1.00084514800642 & 0.99564117844883 \tabularnewline
44 & 5.43 & 5.43904350153733 & 5.4575 & 0.996618140455763 & 0.998337299281616 \tabularnewline
45 & 5.45 & 5.44910010919152 & 5.46541666666667 & 0.997014581235013 & 1.00016514484785 \tabularnewline
46 & 5.51 & 5.47554694060956 & 5.47375 & 1.00032828328103 & 1.00629216766181 \tabularnewline
47 & 5.51 & 5.50344968226808 & 5.48291666666667 & 1.00374490747347 & 1.00119022033635 \tabularnewline
48 & 5.51 & 5.51129210813553 & 5.49208333333333 & 1.00349753884571 & 0.999765552594531 \tabularnewline
49 & 5.51 & 5.50466178280635 & 5.50083333333333 & 1.00069597627142 & 1.00096976297623 \tabularnewline
50 & 5.51 & 5.5044470987919 & 5.50875 & 0.99921889698968 & 1.00100880272050 \tabularnewline
51 & 5.51 & 5.5074258288993 & 5.51583333333333 & 0.998475750820238 & 1.00046740004871 \tabularnewline
52 & 5.53 & 5.51296877441643 & 5.52041666666667 & 0.99865084599588 & 1.00308930202228 \tabularnewline
53 & 5.53 & 5.52609267086668 & 5.52291666666667 & 1.00057505922897 & 1.00070706905693 \tabularnewline
54 & 5.53 & 5.5285173892508 & 5.52666666666667 & 1.00033487139641 & 1.00026817510823 \tabularnewline
55 & 5.53 & 5.53592472491049 & 5.53125 & 1.00084514800642 & 0.99892976779763 \tabularnewline
56 & 5.52 & 5.5171119225397 & 5.53583333333333 & 0.996618140455763 & 1.00052347632255 \tabularnewline
57 & 5.53 & 5.52470704826852 & 5.54125 & 0.997014581235013 & 1.00095805111208 \tabularnewline
58 & 5.54 & 5.54932115150154 & 5.5475 & 1.00032828328103 & 0.998320307791338 \tabularnewline
59 & 5.54 & 5.57705764214947 & 5.55625 & 1.00374490747347 & 0.993355341736222 \tabularnewline
60 & 5.57 & 5.587390671498 & 5.56791666666667 & 1.00349753884571 & 0.996887514670003 \tabularnewline
61 & 5.56 & 5.58471746090807 & 5.58083333333333 & 1.00069597627142 & 0.995574089274688 \tabularnewline
62 & 5.57 & 5.59062972865726 & 5.595 & 0.99921889698968 & 0.99630994545185 \tabularnewline
63 & 5.58 & 5.60186499366438 & 5.61041666666667 & 0.998475750820238 & 0.996096836733997 \tabularnewline
64 & 5.61 & 5.61782711324599 & 5.62541666666667 & 0.99865084599588 & 0.998606736539197 \tabularnewline
65 & 5.66 & 5.64199261522737 & 5.63875 & 1.00057505922897 & 1.00319167109933 \tabularnewline
66 & 5.68 & 5.6523088295861 & 5.65041666666667 & 1.00033487139641 & 1.00489909013268 \tabularnewline
67 & 5.69 & 5.666451612963 & 5.66166666666667 & 1.00084514800642 & 1.00415575542605 \tabularnewline
68 & 5.7 & NA & NA & 0.996618140455763 & NA \tabularnewline
69 & 5.72 & NA & NA & 0.997014581235013 & NA \tabularnewline
70 & 5.71 & NA & NA & 1.00032828328103 & NA \tabularnewline
71 & 5.69 & NA & NA & 1.00374490747347 & NA \tabularnewline
72 & 5.7 & NA & NA & 1.00349753884571 & NA \tabularnewline
73 & 5.7 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40760&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]5.11[/C][C]NA[/C][C]NA[/C][C]1.00069597627142[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]5.11[/C][C]NA[/C][C]NA[/C][C]0.99921889698968[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]5.11[/C][C]NA[/C][C]NA[/C][C]0.998475750820238[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.1[/C][C]NA[/C][C]NA[/C][C]0.99865084599588[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]5.1[/C][C]NA[/C][C]NA[/C][C]1.00057505922897[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5.1[/C][C]NA[/C][C]NA[/C][C]1.00033487139641[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.1[/C][C]5.15393549342138[/C][C]5.14958333333333[/C][C]1.00084514800642[/C][C]0.989535085666046[/C][/ROW]
[ROW][C]8[/C][C]5.1[/C][C]5.14462589254435[/C][C]5.16208333333333[/C][C]0.996618140455763[/C][C]0.991325726403347[/C][/ROW]
[ROW][C]9[/C][C]5.12[/C][C]5.15913503514901[/C][C]5.17458333333333[/C][C]0.997014581235013[/C][C]0.992414419300448[/C][/ROW]
[ROW][C]10[/C][C]5.25[/C][C]5.18920296952037[/C][C]5.1875[/C][C]1.00032828328103[/C][C]1.01171606330235[/C][/ROW]
[ROW][C]11[/C][C]5.26[/C][C]5.22156465408595[/C][C]5.20208333333333[/C][C]1.00374490747347[/C][C]1.00736088671888[/C][/ROW]
[ROW][C]12[/C][C]5.26[/C][C]5.23658465687652[/C][C]5.21833333333333[/C][C]1.00349753884571[/C][C]1.00447149137420[/C][/ROW]
[ROW][C]13[/C][C]5.26[/C][C]5.23989430575121[/C][C]5.23625[/C][C]1.00069597627142[/C][C]1.00383704194696[/C][/ROW]
[ROW][C]14[/C][C]5.26[/C][C]5.25131164488785[/C][C]5.25541666666667[/C][C]0.99921889698968[/C][C]1.00165451142490[/C][/ROW]
[ROW][C]15[/C][C]5.26[/C][C]5.26654355401391[/C][C]5.27458333333333[/C][C]0.998475750820238[/C][C]0.998757523991437[/C][/ROW]
[ROW][C]16[/C][C]5.26[/C][C]5.28244687079904[/C][C]5.28958333333333[/C][C]0.99865084599588[/C][C]0.995750667948384[/C][/ROW]
[ROW][C]17[/C][C]5.29[/C][C]5.30304781391355[/C][C]5.3[/C][C]1.00057505922897[/C][C]0.997539563215078[/C][/ROW]
[ROW][C]18[/C][C]5.3[/C][C]5.31177816711491[/C][C]5.31[/C][C]1.00033487139641[/C][C]0.99778263196535[/C][/ROW]
[ROW][C]19[/C][C]5.33[/C][C]5.32449618739414[/C][C]5.32[/C][C]1.00084514800642[/C][C]1.00103367763111[/C][/ROW]
[ROW][C]20[/C][C]5.33[/C][C]5.31197468862922[/C][C]5.33[/C][C]0.996618140455763[/C][C]1.00339333532770[/C][/ROW]
[ROW][C]21[/C][C]5.35[/C][C]5.32447328653715[/C][C]5.34041666666667[/C][C]0.997014581235013[/C][C]1.00479422321967[/C][/ROW]
[ROW][C]22[/C][C]5.38[/C][C]5.35300672590763[/C][C]5.35125[/C][C]1.00032828328103[/C][C]1.0050426378061[/C][/ROW]
[ROW][C]23[/C][C]5.38[/C][C]5.38132738519214[/C][C]5.36125[/C][C]1.00374490747347[/C][C]0.999753334986495[/C][/ROW]
[ROW][C]24[/C][C]5.38[/C][C]5.38878178360145[/C][C]5.37[/C][C]1.00349753884571[/C][C]0.998370358282427[/C][/ROW]
[ROW][C]25[/C][C]5.38[/C][C]5.38082565574277[/C][C]5.37708333333333[/C][C]1.00069597627142[/C][C]0.999846555938514[/C][/ROW]
[ROW][C]26[/C][C]5.38[/C][C]5.37871205425403[/C][C]5.38291666666667[/C][C]0.99921889698968[/C][C]1.00023945244382[/C][/ROW]
[ROW][C]27[/C][C]5.39[/C][C]5.37970413910687[/C][C]5.38791666666667[/C][C]0.998475750820238[/C][C]1.00191383403750[/C][/ROW]
[ROW][C]28[/C][C]5.39[/C][C]5.38397637347529[/C][C]5.39125[/C][C]0.99865084599588[/C][C]1.00111880627010[/C][/ROW]
[ROW][C]29[/C][C]5.4[/C][C]5.39685172571627[/C][C]5.39375[/C][C]1.00057505922897[/C][C]1.00058335385957[/C][/ROW]
[ROW][C]30[/C][C]5.4[/C][C]5.39805704977285[/C][C]5.39625[/C][C]1.00033487139641[/C][C]1.00035993510429[/C][/ROW]
[ROW][C]31[/C][C]5.4[/C][C]5.40331274279964[/C][C]5.39875[/C][C]1.00084514800642[/C][C]0.999386905226972[/C][/ROW]
[ROW][C]32[/C][C]5.4[/C][C]5.38298373113669[/C][C]5.40125[/C][C]0.996618140455763[/C][C]1.00316112210499[/C][/ROW]
[ROW][C]33[/C][C]5.4[/C][C]5.3876175433487[/C][C]5.40375[/C][C]0.997014581235013[/C][C]1.00229831767969[/C][/ROW]
[ROW][C]34[/C][C]5.41[/C][C]5.40802478148809[/C][C]5.40625[/C][C]1.00032828328103[/C][C]1.00036523843579[/C][/ROW]
[ROW][C]35[/C][C]5.41[/C][C]5.42858704125235[/C][C]5.40833333333333[/C][C]1.00374490747347[/C][C]0.99657608119551[/C][/ROW]
[ROW][C]36[/C][C]5.41[/C][C]5.42892168515528[/C][C]5.41[/C][C]1.00349753884571[/C][C]0.996514651296772[/C][/ROW]
[ROW][C]37[/C][C]5.41[/C][C]5.41585001491227[/C][C]5.41208333333333[/C][C]1.00069597627142[/C][C]0.998919834394203[/C][/ROW]
[ROW][C]38[/C][C]5.41[/C][C]5.41035398599204[/C][C]5.41458333333333[/C][C]0.99921889698968[/C][C]0.999934572489535[/C][/ROW]
[ROW][C]39[/C][C]5.42[/C][C]5.40965841163148[/C][C]5.41791666666667[/C][C]0.998475750820238[/C][C]1.00191168971894[/C][/ROW]
[ROW][C]40[/C][C]5.42[/C][C]5.41684863048932[/C][C]5.42416666666667[/C][C]0.99865084599588[/C][C]1.00058177175063[/C][/ROW]
[ROW][C]41[/C][C]5.42[/C][C]5.4356240092614[/C][C]5.4325[/C][C]1.00057505922897[/C][C]0.997125627299686[/C][/ROW]
[ROW][C]42[/C][C]5.42[/C][C]5.44265531278928[/C][C]5.44083333333333[/C][C]1.00033487139641[/C][C]0.995837452220051[/C][/ROW]
[ROW][C]43[/C][C]5.43[/C][C]5.45377201901163[/C][C]5.44916666666667[/C][C]1.00084514800642[/C][C]0.99564117844883[/C][/ROW]
[ROW][C]44[/C][C]5.43[/C][C]5.43904350153733[/C][C]5.4575[/C][C]0.996618140455763[/C][C]0.998337299281616[/C][/ROW]
[ROW][C]45[/C][C]5.45[/C][C]5.44910010919152[/C][C]5.46541666666667[/C][C]0.997014581235013[/C][C]1.00016514484785[/C][/ROW]
[ROW][C]46[/C][C]5.51[/C][C]5.47554694060956[/C][C]5.47375[/C][C]1.00032828328103[/C][C]1.00629216766181[/C][/ROW]
[ROW][C]47[/C][C]5.51[/C][C]5.50344968226808[/C][C]5.48291666666667[/C][C]1.00374490747347[/C][C]1.00119022033635[/C][/ROW]
[ROW][C]48[/C][C]5.51[/C][C]5.51129210813553[/C][C]5.49208333333333[/C][C]1.00349753884571[/C][C]0.999765552594531[/C][/ROW]
[ROW][C]49[/C][C]5.51[/C][C]5.50466178280635[/C][C]5.50083333333333[/C][C]1.00069597627142[/C][C]1.00096976297623[/C][/ROW]
[ROW][C]50[/C][C]5.51[/C][C]5.5044470987919[/C][C]5.50875[/C][C]0.99921889698968[/C][C]1.00100880272050[/C][/ROW]
[ROW][C]51[/C][C]5.51[/C][C]5.5074258288993[/C][C]5.51583333333333[/C][C]0.998475750820238[/C][C]1.00046740004871[/C][/ROW]
[ROW][C]52[/C][C]5.53[/C][C]5.51296877441643[/C][C]5.52041666666667[/C][C]0.99865084599588[/C][C]1.00308930202228[/C][/ROW]
[ROW][C]53[/C][C]5.53[/C][C]5.52609267086668[/C][C]5.52291666666667[/C][C]1.00057505922897[/C][C]1.00070706905693[/C][/ROW]
[ROW][C]54[/C][C]5.53[/C][C]5.5285173892508[/C][C]5.52666666666667[/C][C]1.00033487139641[/C][C]1.00026817510823[/C][/ROW]
[ROW][C]55[/C][C]5.53[/C][C]5.53592472491049[/C][C]5.53125[/C][C]1.00084514800642[/C][C]0.99892976779763[/C][/ROW]
[ROW][C]56[/C][C]5.52[/C][C]5.5171119225397[/C][C]5.53583333333333[/C][C]0.996618140455763[/C][C]1.00052347632255[/C][/ROW]
[ROW][C]57[/C][C]5.53[/C][C]5.52470704826852[/C][C]5.54125[/C][C]0.997014581235013[/C][C]1.00095805111208[/C][/ROW]
[ROW][C]58[/C][C]5.54[/C][C]5.54932115150154[/C][C]5.5475[/C][C]1.00032828328103[/C][C]0.998320307791338[/C][/ROW]
[ROW][C]59[/C][C]5.54[/C][C]5.57705764214947[/C][C]5.55625[/C][C]1.00374490747347[/C][C]0.993355341736222[/C][/ROW]
[ROW][C]60[/C][C]5.57[/C][C]5.587390671498[/C][C]5.56791666666667[/C][C]1.00349753884571[/C][C]0.996887514670003[/C][/ROW]
[ROW][C]61[/C][C]5.56[/C][C]5.58471746090807[/C][C]5.58083333333333[/C][C]1.00069597627142[/C][C]0.995574089274688[/C][/ROW]
[ROW][C]62[/C][C]5.57[/C][C]5.59062972865726[/C][C]5.595[/C][C]0.99921889698968[/C][C]0.99630994545185[/C][/ROW]
[ROW][C]63[/C][C]5.58[/C][C]5.60186499366438[/C][C]5.61041666666667[/C][C]0.998475750820238[/C][C]0.996096836733997[/C][/ROW]
[ROW][C]64[/C][C]5.61[/C][C]5.61782711324599[/C][C]5.62541666666667[/C][C]0.99865084599588[/C][C]0.998606736539197[/C][/ROW]
[ROW][C]65[/C][C]5.66[/C][C]5.64199261522737[/C][C]5.63875[/C][C]1.00057505922897[/C][C]1.00319167109933[/C][/ROW]
[ROW][C]66[/C][C]5.68[/C][C]5.6523088295861[/C][C]5.65041666666667[/C][C]1.00033487139641[/C][C]1.00489909013268[/C][/ROW]
[ROW][C]67[/C][C]5.69[/C][C]5.666451612963[/C][C]5.66166666666667[/C][C]1.00084514800642[/C][C]1.00415575542605[/C][/ROW]
[ROW][C]68[/C][C]5.7[/C][C]NA[/C][C]NA[/C][C]0.996618140455763[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]5.72[/C][C]NA[/C][C]NA[/C][C]0.997014581235013[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]5.71[/C][C]NA[/C][C]NA[/C][C]1.00032828328103[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]5.69[/C][C]NA[/C][C]NA[/C][C]1.00374490747347[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]5.7[/C][C]NA[/C][C]NA[/C][C]1.00349753884571[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]5.7[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40760&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40760&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
15.11NANA1.00069597627142NA
25.11NANA0.99921889698968NA
35.11NANA0.998475750820238NA
45.1NANA0.99865084599588NA
55.1NANA1.00057505922897NA
65.1NANA1.00033487139641NA
75.15.153935493421385.149583333333331.000845148006420.989535085666046
85.15.144625892544355.162083333333330.9966181404557630.991325726403347
95.125.159135035149015.174583333333330.9970145812350130.992414419300448
105.255.189202969520375.18751.000328283281031.01171606330235
115.265.221564654085955.202083333333331.003744907473471.00736088671888
125.265.236584656876525.218333333333331.003497538845711.00447149137420
135.265.239894305751215.236251.000695976271421.00383704194696
145.265.251311644887855.255416666666670.999218896989681.00165451142490
155.265.266543554013915.274583333333330.9984757508202380.998757523991437
165.265.282446870799045.289583333333330.998650845995880.995750667948384
175.295.303047813913555.31.000575059228970.997539563215078
185.35.311778167114915.311.000334871396410.99778263196535
195.335.324496187394145.321.000845148006421.00103367763111
205.335.311974688629225.330.9966181404557631.00339333532770
215.355.324473286537155.340416666666670.9970145812350131.00479422321967
225.385.353006725907635.351251.000328283281031.0050426378061
235.385.381327385192145.361251.003744907473470.999753334986495
245.385.388781783601455.371.003497538845710.998370358282427
255.385.380825655742775.377083333333331.000695976271420.999846555938514
265.385.378712054254035.382916666666670.999218896989681.00023945244382
275.395.379704139106875.387916666666670.9984757508202381.00191383403750
285.395.383976373475295.391250.998650845995881.00111880627010
295.45.396851725716275.393751.000575059228971.00058335385957
305.45.398057049772855.396251.000334871396411.00035993510429
315.45.403312742799645.398751.000845148006420.999386905226972
325.45.382983731136695.401250.9966181404557631.00316112210499
335.45.38761754334875.403750.9970145812350131.00229831767969
345.415.408024781488095.406251.000328283281031.00036523843579
355.415.428587041252355.408333333333331.003744907473470.99657608119551
365.415.428921685155285.411.003497538845710.996514651296772
375.415.415850014912275.412083333333331.000695976271420.998919834394203
385.415.410353985992045.414583333333330.999218896989680.999934572489535
395.425.409658411631485.417916666666670.9984757508202381.00191168971894
405.425.416848630489325.424166666666670.998650845995881.00058177175063
415.425.43562400926145.43251.000575059228970.997125627299686
425.425.442655312789285.440833333333331.000334871396410.995837452220051
435.435.453772019011635.449166666666671.000845148006420.99564117844883
445.435.439043501537335.45750.9966181404557630.998337299281616
455.455.449100109191525.465416666666670.9970145812350131.00016514484785
465.515.475546940609565.473751.000328283281031.00629216766181
475.515.503449682268085.482916666666671.003744907473471.00119022033635
485.515.511292108135535.492083333333331.003497538845710.999765552594531
495.515.504661782806355.500833333333331.000695976271421.00096976297623
505.515.50444709879195.508750.999218896989681.00100880272050
515.515.50742582889935.515833333333330.9984757508202381.00046740004871
525.535.512968774416435.520416666666670.998650845995881.00308930202228
535.535.526092670866685.522916666666671.000575059228971.00070706905693
545.535.52851738925085.526666666666671.000334871396411.00026817510823
555.535.535924724910495.531251.000845148006420.99892976779763
565.525.51711192253975.535833333333330.9966181404557631.00052347632255
575.535.524707048268525.541250.9970145812350131.00095805111208
585.545.549321151501545.54751.000328283281030.998320307791338
595.545.577057642149475.556251.003744907473470.993355341736222
605.575.5873906714985.567916666666671.003497538845710.996887514670003
615.565.584717460908075.580833333333331.000695976271420.995574089274688
625.575.590629728657265.5950.999218896989680.99630994545185
635.585.601864993664385.610416666666670.9984757508202380.996096836733997
645.615.617827113245995.625416666666670.998650845995880.998606736539197
655.665.641992615227375.638751.000575059228971.00319167109933
665.685.65230882958615.650416666666671.000334871396411.00489909013268
675.695.6664516129635.661666666666671.000845148006421.00415575542605
685.7NANA0.996618140455763NA
695.72NANA0.997014581235013NA
705.71NANA1.00032828328103NA
715.69NANA1.00374490747347NA
725.7NANA1.00349753884571NA
735.7NANANANA



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')