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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 04 Jun 2009 08:13:36 -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/Jun/04/t1244124853yb335lor6m431ur.htm/, Retrieved Mon, 13 May 2024 22:59:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41683, Retrieved Mon, 13 May 2024 22:59:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Brutoschuld van d...] [2009-06-04 10:54:18] [ef653b42671acc8de32235b938c43afe]
- RMP   [(Partial) Autocorrelation Function] [Brutoschuld van d...] [2009-06-04 11:03:57] [ef653b42671acc8de32235b938c43afe]
- RMPD    [Bootstrap Plot - Central Tendency] [Studio 100 maximu...] [2009-06-04 11:35:38] [ef653b42671acc8de32235b938c43afe]
-   P       [Bootstrap Plot - Central Tendency] [Studio 100 maximu...] [2009-06-04 11:56:22] [ef653b42671acc8de32235b938c43afe]
- RMPD        [Blocked Bootstrap Plot - Central Tendency] [Brutoschuld van d...] [2009-06-04 12:31:11] [ef653b42671acc8de32235b938c43afe]
-   P           [Blocked Bootstrap Plot - Central Tendency] [Brutoschuld van d...] [2009-06-04 12:33:42] [ef653b42671acc8de32235b938c43afe]
- RMPD            [Classical Decomposition] [inschrijving nieu...] [2009-06-04 13:58:57] [ef653b42671acc8de32235b938c43afe]
-    D                [Classical Decomposition] [Brutoschuld van d...] [2009-06-04 14:13:36] [2eea656d1ea82c4ced0e8e79cdac0617] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
321.935
310.215
309.030
305.333
294.735
289.351
288.225
289.648
290.155
288.301
289.148
289.741
287.595
285.226
287.816
283.519
290.304
282.166
280.041
282.500
279.913
277.793
281.229
275.363
273.547
270.601
273.338
271.917
273.985
273.911
270.798
271.115
271.344
274.525
276.663
273.784
274.027
269.160
270.491
270.846
270.333
272.599
272.764
270.674
268.175
268.351
272.482
268.714
269.419
265.518
264.101
267.179
271.322
270.157
271.296
269.907
271.244
266.844
270.911
269.829
269.285
263.018
266.680
265.814
268.457
269.508
270.223
264.676
265.521
262.971
266.003
267.722
266.433

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41683&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41683&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41683&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1321.935NANA1.00141829633784NA
2310.215NANA0.98775008885803NA
3309.03NANA0.995697790077363NA
4305.333NANA0.99505059438254NA
5294.735NANA1.00748583486033NA
6289.351NANA1.00465641433361NA
7288.225296.805867731477295.7205833333331.003669965701780.97108929214553
8289.648292.205871668915293.2485416666670.9964444154033110.991246337199502
9290.155290.690987940887291.3234166666670.997829118122340.998156159072271
10288.301289.045438671142289.5305833333330.9983243750742820.997424492583018
11289.148291.211658328869288.4370416666671.009619488003930.992913544942838
12289.741288.544387459403287.9530416666671.002053618844631.00414706572924
13287.595287.720161169616287.3126666666671.001418296337840.999564989922476
14285.226283.162104348272286.6738333333330.987750088858031.00728874245542
15287.816284.719036299279285.949250.9956977900773631.01087726251456
16283.519283.673667016015285.0846666666670.995050594382540.999454771330585
17290.304286.445224174256284.3168751.007485834860331.0134712520932
18282.166284.707404502437283.3878333333331.004656414333610.991073626950874
19280.041283.239093526759282.2034166666671.003669965701780.988708855522246
20282.5280.009558098448281.0087083333330.9964444154033111.00889413175202
21279.913279.188679086585279.7960833333330.997829118122341.00259437780853
22277.793278.242404221067278.7094166666670.9983243750742820.99838484639922
23281.229280.215892485018277.5460416666671.009619488003931.00361545344911
24275.363277.089996046858276.5221251.002053618844630.993767382180891
25273.547276.184197927665275.7930416666671.001418296337840.990451307687214
26270.601271.565630211303274.9335416666670.987750088858030.996447892870125
27273.338272.922880118009274.1021250.9956977900773631.00152101532056
28271.917272.25471515753273.6089166666670.995050594382540.998759561767978
29273.985275.328247665219273.28251.007485834860330.995121286404104
30273.911274.297782647371273.0264583333331.004656414333610.998589916974034
31270.798273.982496350583272.9806666666671.003669965701780.988377008046135
32271.115271.970161517939272.9406250.9964444154033110.996855678898131
33271.344272.169824341073272.7619583333330.997829118122340.996965775529774
34274.525272.141935142931272.5987083333330.9983243750742821.00875669843318
35276.663275.02228363629272.4019166666671.009619488003931.00596575790884
36273.784272.754068285884272.1950833333331.002053618844631.00377604528720
37274.027272.608425271779272.2223333333331.001418296337841.00520370831095
38269.16268.950397226036272.2858750.987750088858031.00077933617546
39270.491270.964674464190272.1354583333330.9956977900773630.998251895878579
40270.846270.401184662844271.7461666666670.995050594382541.00164501992738
41270.333273.345725435096271.3147083333331.007485834860330.988978333462869
42272.599272.190808843094270.929251.004656414333611.00149965077308
43272.764271.51882114144270.5261.003669965701781.00458597622561
44270.674269.221594153601270.182250.9964444154033111.00539483413641
45268.175269.178623678435269.764250.997829118122340.996271532766162
46268.351268.893886788627269.3452083333330.9983243750742820.997981037073357
47272.482271.823514625943269.2336251.009619488003931.00242247391644
48268.714269.725862249735269.1730833333331.002053618844630.99624855310019
49269.419269.391702800892269.0101666666671.001418296337841.00010132902693
50265.518265.622831801688268.9170416666670.987750088858030.99960533587803
51264.101267.855608114674269.0129583333330.9956977900773630.98598271605698
52267.179267.746265295707269.0780416666670.995050594382540.997881332555357
53271.322270.963105392804268.9497916666671.007485834860331.00132451466658
54270.157270.183044859732268.9307916666671.004656414333610.99990360290837
55271.296269.958783458084268.9716666666671.003669965701781.00495341001610
56269.907267.905955377130268.8619166666670.9964444154033111.00746920545328
57271.244268.281533725029268.8652083333330.997829118122341.01104237863053
58266.844268.465189663231268.9157916666670.9983243750742820.99396126676511
59270.911271.324678463912268.7395416666671.009619488003930.998475337863648
60269.829269.144712903039268.5931251.002053618844631.00254245045195
61269.285268.902217882795268.5213751.001418296337841.00142349929361
62263.018264.97256299319268.2587083333330.987750088858030.992623526862137
63266.68266.650149990153267.8022916666670.9956977900773631.00011194447049
64265.814266.078975103936267.4024583333330.995050594382540.999004148659877
65268.457269.035575097834267.0365833333331.007485834860330.997849447614415
66269.508267.986363609792266.7442916666671.004656414333611.00567803663482
67270.223267.515850761566266.5376666666671.003669965701781.01011958443108
68264.676NANA0.996444415403311NA
69265.521NANA0.99782911812234NA
70262.971NANA0.998324375074282NA
71266.003NANA1.00961948800393NA
72267.722NANA1.00205361884463NA
73266.433NANANANA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 321.935 & NA & NA & 1.00141829633784 & NA \tabularnewline
2 & 310.215 & NA & NA & 0.98775008885803 & NA \tabularnewline
3 & 309.03 & NA & NA & 0.995697790077363 & NA \tabularnewline
4 & 305.333 & NA & NA & 0.99505059438254 & NA \tabularnewline
5 & 294.735 & NA & NA & 1.00748583486033 & NA \tabularnewline
6 & 289.351 & NA & NA & 1.00465641433361 & NA \tabularnewline
7 & 288.225 & 296.805867731477 & 295.720583333333 & 1.00366996570178 & 0.97108929214553 \tabularnewline
8 & 289.648 & 292.205871668915 & 293.248541666667 & 0.996444415403311 & 0.991246337199502 \tabularnewline
9 & 290.155 & 290.690987940887 & 291.323416666667 & 0.99782911812234 & 0.998156159072271 \tabularnewline
10 & 288.301 & 289.045438671142 & 289.530583333333 & 0.998324375074282 & 0.997424492583018 \tabularnewline
11 & 289.148 & 291.211658328869 & 288.437041666667 & 1.00961948800393 & 0.992913544942838 \tabularnewline
12 & 289.741 & 288.544387459403 & 287.953041666667 & 1.00205361884463 & 1.00414706572924 \tabularnewline
13 & 287.595 & 287.720161169616 & 287.312666666667 & 1.00141829633784 & 0.999564989922476 \tabularnewline
14 & 285.226 & 283.162104348272 & 286.673833333333 & 0.98775008885803 & 1.00728874245542 \tabularnewline
15 & 287.816 & 284.719036299279 & 285.94925 & 0.995697790077363 & 1.01087726251456 \tabularnewline
16 & 283.519 & 283.673667016015 & 285.084666666667 & 0.99505059438254 & 0.999454771330585 \tabularnewline
17 & 290.304 & 286.445224174256 & 284.316875 & 1.00748583486033 & 1.0134712520932 \tabularnewline
18 & 282.166 & 284.707404502437 & 283.387833333333 & 1.00465641433361 & 0.991073626950874 \tabularnewline
19 & 280.041 & 283.239093526759 & 282.203416666667 & 1.00366996570178 & 0.988708855522246 \tabularnewline
20 & 282.5 & 280.009558098448 & 281.008708333333 & 0.996444415403311 & 1.00889413175202 \tabularnewline
21 & 279.913 & 279.188679086585 & 279.796083333333 & 0.99782911812234 & 1.00259437780853 \tabularnewline
22 & 277.793 & 278.242404221067 & 278.709416666667 & 0.998324375074282 & 0.99838484639922 \tabularnewline
23 & 281.229 & 280.215892485018 & 277.546041666667 & 1.00961948800393 & 1.00361545344911 \tabularnewline
24 & 275.363 & 277.089996046858 & 276.522125 & 1.00205361884463 & 0.993767382180891 \tabularnewline
25 & 273.547 & 276.184197927665 & 275.793041666667 & 1.00141829633784 & 0.990451307687214 \tabularnewline
26 & 270.601 & 271.565630211303 & 274.933541666667 & 0.98775008885803 & 0.996447892870125 \tabularnewline
27 & 273.338 & 272.922880118009 & 274.102125 & 0.995697790077363 & 1.00152101532056 \tabularnewline
28 & 271.917 & 272.25471515753 & 273.608916666667 & 0.99505059438254 & 0.998759561767978 \tabularnewline
29 & 273.985 & 275.328247665219 & 273.2825 & 1.00748583486033 & 0.995121286404104 \tabularnewline
30 & 273.911 & 274.297782647371 & 273.026458333333 & 1.00465641433361 & 0.998589916974034 \tabularnewline
31 & 270.798 & 273.982496350583 & 272.980666666667 & 1.00366996570178 & 0.988377008046135 \tabularnewline
32 & 271.115 & 271.970161517939 & 272.940625 & 0.996444415403311 & 0.996855678898131 \tabularnewline
33 & 271.344 & 272.169824341073 & 272.761958333333 & 0.99782911812234 & 0.996965775529774 \tabularnewline
34 & 274.525 & 272.141935142931 & 272.598708333333 & 0.998324375074282 & 1.00875669843318 \tabularnewline
35 & 276.663 & 275.02228363629 & 272.401916666667 & 1.00961948800393 & 1.00596575790884 \tabularnewline
36 & 273.784 & 272.754068285884 & 272.195083333333 & 1.00205361884463 & 1.00377604528720 \tabularnewline
37 & 274.027 & 272.608425271779 & 272.222333333333 & 1.00141829633784 & 1.00520370831095 \tabularnewline
38 & 269.16 & 268.950397226036 & 272.285875 & 0.98775008885803 & 1.00077933617546 \tabularnewline
39 & 270.491 & 270.964674464190 & 272.135458333333 & 0.995697790077363 & 0.998251895878579 \tabularnewline
40 & 270.846 & 270.401184662844 & 271.746166666667 & 0.99505059438254 & 1.00164501992738 \tabularnewline
41 & 270.333 & 273.345725435096 & 271.314708333333 & 1.00748583486033 & 0.988978333462869 \tabularnewline
42 & 272.599 & 272.190808843094 & 270.92925 & 1.00465641433361 & 1.00149965077308 \tabularnewline
43 & 272.764 & 271.51882114144 & 270.526 & 1.00366996570178 & 1.00458597622561 \tabularnewline
44 & 270.674 & 269.221594153601 & 270.18225 & 0.996444415403311 & 1.00539483413641 \tabularnewline
45 & 268.175 & 269.178623678435 & 269.76425 & 0.99782911812234 & 0.996271532766162 \tabularnewline
46 & 268.351 & 268.893886788627 & 269.345208333333 & 0.998324375074282 & 0.997981037073357 \tabularnewline
47 & 272.482 & 271.823514625943 & 269.233625 & 1.00961948800393 & 1.00242247391644 \tabularnewline
48 & 268.714 & 269.725862249735 & 269.173083333333 & 1.00205361884463 & 0.99624855310019 \tabularnewline
49 & 269.419 & 269.391702800892 & 269.010166666667 & 1.00141829633784 & 1.00010132902693 \tabularnewline
50 & 265.518 & 265.622831801688 & 268.917041666667 & 0.98775008885803 & 0.99960533587803 \tabularnewline
51 & 264.101 & 267.855608114674 & 269.012958333333 & 0.995697790077363 & 0.98598271605698 \tabularnewline
52 & 267.179 & 267.746265295707 & 269.078041666667 & 0.99505059438254 & 0.997881332555357 \tabularnewline
53 & 271.322 & 270.963105392804 & 268.949791666667 & 1.00748583486033 & 1.00132451466658 \tabularnewline
54 & 270.157 & 270.183044859732 & 268.930791666667 & 1.00465641433361 & 0.99990360290837 \tabularnewline
55 & 271.296 & 269.958783458084 & 268.971666666667 & 1.00366996570178 & 1.00495341001610 \tabularnewline
56 & 269.907 & 267.905955377130 & 268.861916666667 & 0.996444415403311 & 1.00746920545328 \tabularnewline
57 & 271.244 & 268.281533725029 & 268.865208333333 & 0.99782911812234 & 1.01104237863053 \tabularnewline
58 & 266.844 & 268.465189663231 & 268.915791666667 & 0.998324375074282 & 0.99396126676511 \tabularnewline
59 & 270.911 & 271.324678463912 & 268.739541666667 & 1.00961948800393 & 0.998475337863648 \tabularnewline
60 & 269.829 & 269.144712903039 & 268.593125 & 1.00205361884463 & 1.00254245045195 \tabularnewline
61 & 269.285 & 268.902217882795 & 268.521375 & 1.00141829633784 & 1.00142349929361 \tabularnewline
62 & 263.018 & 264.97256299319 & 268.258708333333 & 0.98775008885803 & 0.992623526862137 \tabularnewline
63 & 266.68 & 266.650149990153 & 267.802291666667 & 0.995697790077363 & 1.00011194447049 \tabularnewline
64 & 265.814 & 266.078975103936 & 267.402458333333 & 0.99505059438254 & 0.999004148659877 \tabularnewline
65 & 268.457 & 269.035575097834 & 267.036583333333 & 1.00748583486033 & 0.997849447614415 \tabularnewline
66 & 269.508 & 267.986363609792 & 266.744291666667 & 1.00465641433361 & 1.00567803663482 \tabularnewline
67 & 270.223 & 267.515850761566 & 266.537666666667 & 1.00366996570178 & 1.01011958443108 \tabularnewline
68 & 264.676 & NA & NA & 0.996444415403311 & NA \tabularnewline
69 & 265.521 & NA & NA & 0.99782911812234 & NA \tabularnewline
70 & 262.971 & NA & NA & 0.998324375074282 & NA \tabularnewline
71 & 266.003 & NA & NA & 1.00961948800393 & NA \tabularnewline
72 & 267.722 & NA & NA & 1.00205361884463 & NA \tabularnewline
73 & 266.433 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41683&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]321.935[/C][C]NA[/C][C]NA[/C][C]1.00141829633784[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]310.215[/C][C]NA[/C][C]NA[/C][C]0.98775008885803[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]309.03[/C][C]NA[/C][C]NA[/C][C]0.995697790077363[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]305.333[/C][C]NA[/C][C]NA[/C][C]0.99505059438254[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]294.735[/C][C]NA[/C][C]NA[/C][C]1.00748583486033[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]289.351[/C][C]NA[/C][C]NA[/C][C]1.00465641433361[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]288.225[/C][C]296.805867731477[/C][C]295.720583333333[/C][C]1.00366996570178[/C][C]0.97108929214553[/C][/ROW]
[ROW][C]8[/C][C]289.648[/C][C]292.205871668915[/C][C]293.248541666667[/C][C]0.996444415403311[/C][C]0.991246337199502[/C][/ROW]
[ROW][C]9[/C][C]290.155[/C][C]290.690987940887[/C][C]291.323416666667[/C][C]0.99782911812234[/C][C]0.998156159072271[/C][/ROW]
[ROW][C]10[/C][C]288.301[/C][C]289.045438671142[/C][C]289.530583333333[/C][C]0.998324375074282[/C][C]0.997424492583018[/C][/ROW]
[ROW][C]11[/C][C]289.148[/C][C]291.211658328869[/C][C]288.437041666667[/C][C]1.00961948800393[/C][C]0.992913544942838[/C][/ROW]
[ROW][C]12[/C][C]289.741[/C][C]288.544387459403[/C][C]287.953041666667[/C][C]1.00205361884463[/C][C]1.00414706572924[/C][/ROW]
[ROW][C]13[/C][C]287.595[/C][C]287.720161169616[/C][C]287.312666666667[/C][C]1.00141829633784[/C][C]0.999564989922476[/C][/ROW]
[ROW][C]14[/C][C]285.226[/C][C]283.162104348272[/C][C]286.673833333333[/C][C]0.98775008885803[/C][C]1.00728874245542[/C][/ROW]
[ROW][C]15[/C][C]287.816[/C][C]284.719036299279[/C][C]285.94925[/C][C]0.995697790077363[/C][C]1.01087726251456[/C][/ROW]
[ROW][C]16[/C][C]283.519[/C][C]283.673667016015[/C][C]285.084666666667[/C][C]0.99505059438254[/C][C]0.999454771330585[/C][/ROW]
[ROW][C]17[/C][C]290.304[/C][C]286.445224174256[/C][C]284.316875[/C][C]1.00748583486033[/C][C]1.0134712520932[/C][/ROW]
[ROW][C]18[/C][C]282.166[/C][C]284.707404502437[/C][C]283.387833333333[/C][C]1.00465641433361[/C][C]0.991073626950874[/C][/ROW]
[ROW][C]19[/C][C]280.041[/C][C]283.239093526759[/C][C]282.203416666667[/C][C]1.00366996570178[/C][C]0.988708855522246[/C][/ROW]
[ROW][C]20[/C][C]282.5[/C][C]280.009558098448[/C][C]281.008708333333[/C][C]0.996444415403311[/C][C]1.00889413175202[/C][/ROW]
[ROW][C]21[/C][C]279.913[/C][C]279.188679086585[/C][C]279.796083333333[/C][C]0.99782911812234[/C][C]1.00259437780853[/C][/ROW]
[ROW][C]22[/C][C]277.793[/C][C]278.242404221067[/C][C]278.709416666667[/C][C]0.998324375074282[/C][C]0.99838484639922[/C][/ROW]
[ROW][C]23[/C][C]281.229[/C][C]280.215892485018[/C][C]277.546041666667[/C][C]1.00961948800393[/C][C]1.00361545344911[/C][/ROW]
[ROW][C]24[/C][C]275.363[/C][C]277.089996046858[/C][C]276.522125[/C][C]1.00205361884463[/C][C]0.993767382180891[/C][/ROW]
[ROW][C]25[/C][C]273.547[/C][C]276.184197927665[/C][C]275.793041666667[/C][C]1.00141829633784[/C][C]0.990451307687214[/C][/ROW]
[ROW][C]26[/C][C]270.601[/C][C]271.565630211303[/C][C]274.933541666667[/C][C]0.98775008885803[/C][C]0.996447892870125[/C][/ROW]
[ROW][C]27[/C][C]273.338[/C][C]272.922880118009[/C][C]274.102125[/C][C]0.995697790077363[/C][C]1.00152101532056[/C][/ROW]
[ROW][C]28[/C][C]271.917[/C][C]272.25471515753[/C][C]273.608916666667[/C][C]0.99505059438254[/C][C]0.998759561767978[/C][/ROW]
[ROW][C]29[/C][C]273.985[/C][C]275.328247665219[/C][C]273.2825[/C][C]1.00748583486033[/C][C]0.995121286404104[/C][/ROW]
[ROW][C]30[/C][C]273.911[/C][C]274.297782647371[/C][C]273.026458333333[/C][C]1.00465641433361[/C][C]0.998589916974034[/C][/ROW]
[ROW][C]31[/C][C]270.798[/C][C]273.982496350583[/C][C]272.980666666667[/C][C]1.00366996570178[/C][C]0.988377008046135[/C][/ROW]
[ROW][C]32[/C][C]271.115[/C][C]271.970161517939[/C][C]272.940625[/C][C]0.996444415403311[/C][C]0.996855678898131[/C][/ROW]
[ROW][C]33[/C][C]271.344[/C][C]272.169824341073[/C][C]272.761958333333[/C][C]0.99782911812234[/C][C]0.996965775529774[/C][/ROW]
[ROW][C]34[/C][C]274.525[/C][C]272.141935142931[/C][C]272.598708333333[/C][C]0.998324375074282[/C][C]1.00875669843318[/C][/ROW]
[ROW][C]35[/C][C]276.663[/C][C]275.02228363629[/C][C]272.401916666667[/C][C]1.00961948800393[/C][C]1.00596575790884[/C][/ROW]
[ROW][C]36[/C][C]273.784[/C][C]272.754068285884[/C][C]272.195083333333[/C][C]1.00205361884463[/C][C]1.00377604528720[/C][/ROW]
[ROW][C]37[/C][C]274.027[/C][C]272.608425271779[/C][C]272.222333333333[/C][C]1.00141829633784[/C][C]1.00520370831095[/C][/ROW]
[ROW][C]38[/C][C]269.16[/C][C]268.950397226036[/C][C]272.285875[/C][C]0.98775008885803[/C][C]1.00077933617546[/C][/ROW]
[ROW][C]39[/C][C]270.491[/C][C]270.964674464190[/C][C]272.135458333333[/C][C]0.995697790077363[/C][C]0.998251895878579[/C][/ROW]
[ROW][C]40[/C][C]270.846[/C][C]270.401184662844[/C][C]271.746166666667[/C][C]0.99505059438254[/C][C]1.00164501992738[/C][/ROW]
[ROW][C]41[/C][C]270.333[/C][C]273.345725435096[/C][C]271.314708333333[/C][C]1.00748583486033[/C][C]0.988978333462869[/C][/ROW]
[ROW][C]42[/C][C]272.599[/C][C]272.190808843094[/C][C]270.92925[/C][C]1.00465641433361[/C][C]1.00149965077308[/C][/ROW]
[ROW][C]43[/C][C]272.764[/C][C]271.51882114144[/C][C]270.526[/C][C]1.00366996570178[/C][C]1.00458597622561[/C][/ROW]
[ROW][C]44[/C][C]270.674[/C][C]269.221594153601[/C][C]270.18225[/C][C]0.996444415403311[/C][C]1.00539483413641[/C][/ROW]
[ROW][C]45[/C][C]268.175[/C][C]269.178623678435[/C][C]269.76425[/C][C]0.99782911812234[/C][C]0.996271532766162[/C][/ROW]
[ROW][C]46[/C][C]268.351[/C][C]268.893886788627[/C][C]269.345208333333[/C][C]0.998324375074282[/C][C]0.997981037073357[/C][/ROW]
[ROW][C]47[/C][C]272.482[/C][C]271.823514625943[/C][C]269.233625[/C][C]1.00961948800393[/C][C]1.00242247391644[/C][/ROW]
[ROW][C]48[/C][C]268.714[/C][C]269.725862249735[/C][C]269.173083333333[/C][C]1.00205361884463[/C][C]0.99624855310019[/C][/ROW]
[ROW][C]49[/C][C]269.419[/C][C]269.391702800892[/C][C]269.010166666667[/C][C]1.00141829633784[/C][C]1.00010132902693[/C][/ROW]
[ROW][C]50[/C][C]265.518[/C][C]265.622831801688[/C][C]268.917041666667[/C][C]0.98775008885803[/C][C]0.99960533587803[/C][/ROW]
[ROW][C]51[/C][C]264.101[/C][C]267.855608114674[/C][C]269.012958333333[/C][C]0.995697790077363[/C][C]0.98598271605698[/C][/ROW]
[ROW][C]52[/C][C]267.179[/C][C]267.746265295707[/C][C]269.078041666667[/C][C]0.99505059438254[/C][C]0.997881332555357[/C][/ROW]
[ROW][C]53[/C][C]271.322[/C][C]270.963105392804[/C][C]268.949791666667[/C][C]1.00748583486033[/C][C]1.00132451466658[/C][/ROW]
[ROW][C]54[/C][C]270.157[/C][C]270.183044859732[/C][C]268.930791666667[/C][C]1.00465641433361[/C][C]0.99990360290837[/C][/ROW]
[ROW][C]55[/C][C]271.296[/C][C]269.958783458084[/C][C]268.971666666667[/C][C]1.00366996570178[/C][C]1.00495341001610[/C][/ROW]
[ROW][C]56[/C][C]269.907[/C][C]267.905955377130[/C][C]268.861916666667[/C][C]0.996444415403311[/C][C]1.00746920545328[/C][/ROW]
[ROW][C]57[/C][C]271.244[/C][C]268.281533725029[/C][C]268.865208333333[/C][C]0.99782911812234[/C][C]1.01104237863053[/C][/ROW]
[ROW][C]58[/C][C]266.844[/C][C]268.465189663231[/C][C]268.915791666667[/C][C]0.998324375074282[/C][C]0.99396126676511[/C][/ROW]
[ROW][C]59[/C][C]270.911[/C][C]271.324678463912[/C][C]268.739541666667[/C][C]1.00961948800393[/C][C]0.998475337863648[/C][/ROW]
[ROW][C]60[/C][C]269.829[/C][C]269.144712903039[/C][C]268.593125[/C][C]1.00205361884463[/C][C]1.00254245045195[/C][/ROW]
[ROW][C]61[/C][C]269.285[/C][C]268.902217882795[/C][C]268.521375[/C][C]1.00141829633784[/C][C]1.00142349929361[/C][/ROW]
[ROW][C]62[/C][C]263.018[/C][C]264.97256299319[/C][C]268.258708333333[/C][C]0.98775008885803[/C][C]0.992623526862137[/C][/ROW]
[ROW][C]63[/C][C]266.68[/C][C]266.650149990153[/C][C]267.802291666667[/C][C]0.995697790077363[/C][C]1.00011194447049[/C][/ROW]
[ROW][C]64[/C][C]265.814[/C][C]266.078975103936[/C][C]267.402458333333[/C][C]0.99505059438254[/C][C]0.999004148659877[/C][/ROW]
[ROW][C]65[/C][C]268.457[/C][C]269.035575097834[/C][C]267.036583333333[/C][C]1.00748583486033[/C][C]0.997849447614415[/C][/ROW]
[ROW][C]66[/C][C]269.508[/C][C]267.986363609792[/C][C]266.744291666667[/C][C]1.00465641433361[/C][C]1.00567803663482[/C][/ROW]
[ROW][C]67[/C][C]270.223[/C][C]267.515850761566[/C][C]266.537666666667[/C][C]1.00366996570178[/C][C]1.01011958443108[/C][/ROW]
[ROW][C]68[/C][C]264.676[/C][C]NA[/C][C]NA[/C][C]0.996444415403311[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]265.521[/C][C]NA[/C][C]NA[/C][C]0.99782911812234[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]262.971[/C][C]NA[/C][C]NA[/C][C]0.998324375074282[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]266.003[/C][C]NA[/C][C]NA[/C][C]1.00961948800393[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]267.722[/C][C]NA[/C][C]NA[/C][C]1.00205361884463[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]266.433[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41683&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41683&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1321.935NANA1.00141829633784NA
2310.215NANA0.98775008885803NA
3309.03NANA0.995697790077363NA
4305.333NANA0.99505059438254NA
5294.735NANA1.00748583486033NA
6289.351NANA1.00465641433361NA
7288.225296.805867731477295.7205833333331.003669965701780.97108929214553
8289.648292.205871668915293.2485416666670.9964444154033110.991246337199502
9290.155290.690987940887291.3234166666670.997829118122340.998156159072271
10288.301289.045438671142289.5305833333330.9983243750742820.997424492583018
11289.148291.211658328869288.4370416666671.009619488003930.992913544942838
12289.741288.544387459403287.9530416666671.002053618844631.00414706572924
13287.595287.720161169616287.3126666666671.001418296337840.999564989922476
14285.226283.162104348272286.6738333333330.987750088858031.00728874245542
15287.816284.719036299279285.949250.9956977900773631.01087726251456
16283.519283.673667016015285.0846666666670.995050594382540.999454771330585
17290.304286.445224174256284.3168751.007485834860331.0134712520932
18282.166284.707404502437283.3878333333331.004656414333610.991073626950874
19280.041283.239093526759282.2034166666671.003669965701780.988708855522246
20282.5280.009558098448281.0087083333330.9964444154033111.00889413175202
21279.913279.188679086585279.7960833333330.997829118122341.00259437780853
22277.793278.242404221067278.7094166666670.9983243750742820.99838484639922
23281.229280.215892485018277.5460416666671.009619488003931.00361545344911
24275.363277.089996046858276.5221251.002053618844630.993767382180891
25273.547276.184197927665275.7930416666671.001418296337840.990451307687214
26270.601271.565630211303274.9335416666670.987750088858030.996447892870125
27273.338272.922880118009274.1021250.9956977900773631.00152101532056
28271.917272.25471515753273.6089166666670.995050594382540.998759561767978
29273.985275.328247665219273.28251.007485834860330.995121286404104
30273.911274.297782647371273.0264583333331.004656414333610.998589916974034
31270.798273.982496350583272.9806666666671.003669965701780.988377008046135
32271.115271.970161517939272.9406250.9964444154033110.996855678898131
33271.344272.169824341073272.7619583333330.997829118122340.996965775529774
34274.525272.141935142931272.5987083333330.9983243750742821.00875669843318
35276.663275.02228363629272.4019166666671.009619488003931.00596575790884
36273.784272.754068285884272.1950833333331.002053618844631.00377604528720
37274.027272.608425271779272.2223333333331.001418296337841.00520370831095
38269.16268.950397226036272.2858750.987750088858031.00077933617546
39270.491270.964674464190272.1354583333330.9956977900773630.998251895878579
40270.846270.401184662844271.7461666666670.995050594382541.00164501992738
41270.333273.345725435096271.3147083333331.007485834860330.988978333462869
42272.599272.190808843094270.929251.004656414333611.00149965077308
43272.764271.51882114144270.5261.003669965701781.00458597622561
44270.674269.221594153601270.182250.9964444154033111.00539483413641
45268.175269.178623678435269.764250.997829118122340.996271532766162
46268.351268.893886788627269.3452083333330.9983243750742820.997981037073357
47272.482271.823514625943269.2336251.009619488003931.00242247391644
48268.714269.725862249735269.1730833333331.002053618844630.99624855310019
49269.419269.391702800892269.0101666666671.001418296337841.00010132902693
50265.518265.622831801688268.9170416666670.987750088858030.99960533587803
51264.101267.855608114674269.0129583333330.9956977900773630.98598271605698
52267.179267.746265295707269.0780416666670.995050594382540.997881332555357
53271.322270.963105392804268.9497916666671.007485834860331.00132451466658
54270.157270.183044859732268.9307916666671.004656414333610.99990360290837
55271.296269.958783458084268.9716666666671.003669965701781.00495341001610
56269.907267.905955377130268.8619166666670.9964444154033111.00746920545328
57271.244268.281533725029268.8652083333330.997829118122341.01104237863053
58266.844268.465189663231268.9157916666670.9983243750742820.99396126676511
59270.911271.324678463912268.7395416666671.009619488003930.998475337863648
60269.829269.144712903039268.5931251.002053618844631.00254245045195
61269.285268.902217882795268.5213751.001418296337841.00142349929361
62263.018264.97256299319268.2587083333330.987750088858030.992623526862137
63266.68266.650149990153267.8022916666670.9956977900773631.00011194447049
64265.814266.078975103936267.4024583333330.995050594382540.999004148659877
65268.457269.035575097834267.0365833333331.007485834860330.997849447614415
66269.508267.986363609792266.7442916666671.004656414333611.00567803663482
67270.223267.515850761566266.5376666666671.003669965701781.01011958443108
68264.676NANA0.996444415403311NA
69265.521NANA0.99782911812234NA
70262.971NANA0.998324375074282NA
71266.003NANA1.00961948800393NA
72267.722NANA1.00205361884463NA
73266.433NANANANA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
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')