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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 computationMon, 10 Dec 2012 05:55:37 -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/10/t1355137029yc93uxb1m36cb47.htm/, Retrieved Fri, 19 Apr 2024 02:02:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198087, Retrieved Fri, 19 Apr 2024 02:02:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Multiplicatief mo...] [2012-12-10 10:55:37] [a65efd8010de7ce8a50260769e922377] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8,41
8,39
8,43
8,44
8,49
8,47
8,53
8,52
8,51
8,53
8,54
8,53
8,47
8,63
8,67
8,73
8,57
8,55
8,63
8,65
8,44
8,62
8,37
8,59
8,84
8,72
8,8
8,69
8,68
8,57
8,85
8,85
8,85
8,93
8,75
8,78
8,77
9,03
9,01
9,07
8,99
9,02
8,99
8,98
8,94
8,94
8,75
8,86
8,87
8,84
8,84
9,91
10,18
10,34
10,36
10,26
10,16
10,31
10,46
10,54
10,47
10,48
10,46
11,3
11,58
11,69
11,63
11,51
11,37
11,42
11,7
11,75

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198087&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198087&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198087&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
18.41NANA0.986461986862472NA
28.39NANA0.987759749124915NA
38.43NANA0.98497466322222NA
48.44NANA1.01818617221822NA
58.49NANA1.01790806697169NA
68.47NANA1.01540507346761NA
78.538.592516969266918.4851.012671416531160.992724254198099
88.528.557353228767758.49751.007043627980910.99563495536889
98.518.47966195650328.51750.9955576115648021.00357774209071
108.538.545794725971218.539583333333331.000727364836830.998151754578984
118.548.423229490840058.5550.9845972519976671.01386291437114
128.538.464979895321418.561666666666670.9887070152215011.00768107018358
138.478.453157175755678.569166666666670.9864619868624721.00199248918412
148.638.473743947805368.578750.9877597491249151.01844002523054
158.678.452313828775688.581250.984974663222221.0257546247849
168.738.738158578824438.582083333333331.018186172218220.999066327447502
178.578.73237882953348.578751.017908066971690.981404971920799
188.558.706252334090228.574166666666661.015405073467610.982052859474519
198.638.700957200120458.592083333333331.012671416531160.991844897235045
208.658.671904441450578.611251.007043627980910.997474091002909
218.448.582121427360088.620416666666670.9955576115648020.983439825623185
228.628.6304395822478.624166666666671.000727364836830.998790376533257
238.378.494202542754888.627083333333330.9845972519976670.985377963130769
248.598.53501330889968.63250.9887070152215011.00644248451764
258.848.525497721458928.64250.9864619868624721.03688960912505
268.728.553999427421768.660.9877597491249151.01940619402499
278.88.554915356194668.685416666666670.984974663222221.02864840078492
288.698.873916735120198.715416666666671.018186172218220.979274457873567
298.688.900757788944968.744166666666671.017908066971690.975197865824508
308.578.902987067074578.767916666666671.015405073467610.962598275773528
318.858.884081947943178.772916666666671.012671416531160.99616370626218
328.858.844780264253968.782916666666671.007043627980911.00059014871937
338.858.76546995415668.804583333333330.9955576115648021.00964352696267
348.938.835588692038558.829166666666661.000727364836831.01068534437853
358.758.721480408424348.857916666666670.9845972519976671.0032700402042
368.788.78919340406288.889583333333330.9887070152215010.998954010494461
378.778.793486561223228.914166666666670.9864619868624720.997329095682389
389.038.8161673275028.925416666666670.9877597491249151.02425460685517
399.018.800338209780868.934583333333330.984974663222221.02382428779682
409.079.101311646915598.938751.018186172218220.996559655560614
418.999.099249862004458.939166666666671.017908066971690.987993530932628
429.029.080259869484128.94251.015405073467610.993363640429869
438.999.06340917795398.951.012671416531160.99190048948331
448.989.009264056824188.946251.007043627980910.996751781650577
458.948.891573918288148.931250.9955576115648021.00544628905488
468.948.965683249467348.959166666666671.000727364836830.997135382909176
478.758.90445139775399.043750.9845972519976670.982654585795946
488.869.045021344251369.148333333333330.9887070152215010.979544399376243
498.879.135049024174359.260416666666670.9864619868624720.970985484207808
508.849.256131982424729.370833333333330.9877597491249150.955042561707757
518.849.332634934030549.4750.984974663222220.947213735722782
529.919.757193239519499.582916666666671.018186172218221.01566093411593
5310.189.885159715378849.711251.017908066971691.02982655749734
5410.3410.00427848633969.85251.015405073467611.03355779370984
5510.3610.11574355829929.989166666666671.012671416531161.02414616783167
5610.2610.195477530283410.12416666666671.007043627980911.00632853826856
5710.1610.214421094654910.260.9955576115648020.99467213127885
5810.3110.392970653565910.38541666666671.000727364836830.99201665661036
5910.4610.339912141395510.50166666666670.9845972519976671.01161401150825
6010.5410.496360850345310.616250.9887070152215011.00415755043838
6110.4710.580215834927910.72541666666670.9864619868624720.989582836810944
6210.4810.69784964958510.83041666666670.9877597491249150.979636127191841
6310.4610.768645911786610.93291666666670.984974663222220.971338465920885
6411.311.230169235328511.02958333333331.018186172218221.00621814001269
6511.5811.326772015227511.12751.017908066971691.02235658883502
6611.6911.40257588959411.22958333333331.015405073467611.02520694562255
6711.63NANA1.01267141653116NA
6811.51NANA1.00704362798091NA
6911.37NANA0.995557611564802NA
7011.42NANA1.00072736483683NA
7111.7NANA0.984597251997667NA
7211.75NANA0.988707015221501NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 8.41 & NA & NA & 0.986461986862472 & NA \tabularnewline
2 & 8.39 & NA & NA & 0.987759749124915 & NA \tabularnewline
3 & 8.43 & NA & NA & 0.98497466322222 & NA \tabularnewline
4 & 8.44 & NA & NA & 1.01818617221822 & NA \tabularnewline
5 & 8.49 & NA & NA & 1.01790806697169 & NA \tabularnewline
6 & 8.47 & NA & NA & 1.01540507346761 & NA \tabularnewline
7 & 8.53 & 8.59251696926691 & 8.485 & 1.01267141653116 & 0.992724254198099 \tabularnewline
8 & 8.52 & 8.55735322876775 & 8.4975 & 1.00704362798091 & 0.99563495536889 \tabularnewline
9 & 8.51 & 8.4796619565032 & 8.5175 & 0.995557611564802 & 1.00357774209071 \tabularnewline
10 & 8.53 & 8.54579472597121 & 8.53958333333333 & 1.00072736483683 & 0.998151754578984 \tabularnewline
11 & 8.54 & 8.42322949084005 & 8.555 & 0.984597251997667 & 1.01386291437114 \tabularnewline
12 & 8.53 & 8.46497989532141 & 8.56166666666667 & 0.988707015221501 & 1.00768107018358 \tabularnewline
13 & 8.47 & 8.45315717575567 & 8.56916666666667 & 0.986461986862472 & 1.00199248918412 \tabularnewline
14 & 8.63 & 8.47374394780536 & 8.57875 & 0.987759749124915 & 1.01844002523054 \tabularnewline
15 & 8.67 & 8.45231382877568 & 8.58125 & 0.98497466322222 & 1.0257546247849 \tabularnewline
16 & 8.73 & 8.73815857882443 & 8.58208333333333 & 1.01818617221822 & 0.999066327447502 \tabularnewline
17 & 8.57 & 8.7323788295334 & 8.57875 & 1.01790806697169 & 0.981404971920799 \tabularnewline
18 & 8.55 & 8.70625233409022 & 8.57416666666666 & 1.01540507346761 & 0.982052859474519 \tabularnewline
19 & 8.63 & 8.70095720012045 & 8.59208333333333 & 1.01267141653116 & 0.991844897235045 \tabularnewline
20 & 8.65 & 8.67190444145057 & 8.61125 & 1.00704362798091 & 0.997474091002909 \tabularnewline
21 & 8.44 & 8.58212142736008 & 8.62041666666667 & 0.995557611564802 & 0.983439825623185 \tabularnewline
22 & 8.62 & 8.630439582247 & 8.62416666666667 & 1.00072736483683 & 0.998790376533257 \tabularnewline
23 & 8.37 & 8.49420254275488 & 8.62708333333333 & 0.984597251997667 & 0.985377963130769 \tabularnewline
24 & 8.59 & 8.5350133088996 & 8.6325 & 0.988707015221501 & 1.00644248451764 \tabularnewline
25 & 8.84 & 8.52549772145892 & 8.6425 & 0.986461986862472 & 1.03688960912505 \tabularnewline
26 & 8.72 & 8.55399942742176 & 8.66 & 0.987759749124915 & 1.01940619402499 \tabularnewline
27 & 8.8 & 8.55491535619466 & 8.68541666666667 & 0.98497466322222 & 1.02864840078492 \tabularnewline
28 & 8.69 & 8.87391673512019 & 8.71541666666667 & 1.01818617221822 & 0.979274457873567 \tabularnewline
29 & 8.68 & 8.90075778894496 & 8.74416666666667 & 1.01790806697169 & 0.975197865824508 \tabularnewline
30 & 8.57 & 8.90298706707457 & 8.76791666666667 & 1.01540507346761 & 0.962598275773528 \tabularnewline
31 & 8.85 & 8.88408194794317 & 8.77291666666667 & 1.01267141653116 & 0.99616370626218 \tabularnewline
32 & 8.85 & 8.84478026425396 & 8.78291666666667 & 1.00704362798091 & 1.00059014871937 \tabularnewline
33 & 8.85 & 8.7654699541566 & 8.80458333333333 & 0.995557611564802 & 1.00964352696267 \tabularnewline
34 & 8.93 & 8.83558869203855 & 8.82916666666666 & 1.00072736483683 & 1.01068534437853 \tabularnewline
35 & 8.75 & 8.72148040842434 & 8.85791666666667 & 0.984597251997667 & 1.0032700402042 \tabularnewline
36 & 8.78 & 8.7891934040628 & 8.88958333333333 & 0.988707015221501 & 0.998954010494461 \tabularnewline
37 & 8.77 & 8.79348656122322 & 8.91416666666667 & 0.986461986862472 & 0.997329095682389 \tabularnewline
38 & 9.03 & 8.816167327502 & 8.92541666666667 & 0.987759749124915 & 1.02425460685517 \tabularnewline
39 & 9.01 & 8.80033820978086 & 8.93458333333333 & 0.98497466322222 & 1.02382428779682 \tabularnewline
40 & 9.07 & 9.10131164691559 & 8.93875 & 1.01818617221822 & 0.996559655560614 \tabularnewline
41 & 8.99 & 9.09924986200445 & 8.93916666666667 & 1.01790806697169 & 0.987993530932628 \tabularnewline
42 & 9.02 & 9.08025986948412 & 8.9425 & 1.01540507346761 & 0.993363640429869 \tabularnewline
43 & 8.99 & 9.0634091779539 & 8.95 & 1.01267141653116 & 0.99190048948331 \tabularnewline
44 & 8.98 & 9.00926405682418 & 8.94625 & 1.00704362798091 & 0.996751781650577 \tabularnewline
45 & 8.94 & 8.89157391828814 & 8.93125 & 0.995557611564802 & 1.00544628905488 \tabularnewline
46 & 8.94 & 8.96568324946734 & 8.95916666666667 & 1.00072736483683 & 0.997135382909176 \tabularnewline
47 & 8.75 & 8.9044513977539 & 9.04375 & 0.984597251997667 & 0.982654585795946 \tabularnewline
48 & 8.86 & 9.04502134425136 & 9.14833333333333 & 0.988707015221501 & 0.979544399376243 \tabularnewline
49 & 8.87 & 9.13504902417435 & 9.26041666666667 & 0.986461986862472 & 0.970985484207808 \tabularnewline
50 & 8.84 & 9.25613198242472 & 9.37083333333333 & 0.987759749124915 & 0.955042561707757 \tabularnewline
51 & 8.84 & 9.33263493403054 & 9.475 & 0.98497466322222 & 0.947213735722782 \tabularnewline
52 & 9.91 & 9.75719323951949 & 9.58291666666667 & 1.01818617221822 & 1.01566093411593 \tabularnewline
53 & 10.18 & 9.88515971537884 & 9.71125 & 1.01790806697169 & 1.02982655749734 \tabularnewline
54 & 10.34 & 10.0042784863396 & 9.8525 & 1.01540507346761 & 1.03355779370984 \tabularnewline
55 & 10.36 & 10.1157435582992 & 9.98916666666667 & 1.01267141653116 & 1.02414616783167 \tabularnewline
56 & 10.26 & 10.1954775302834 & 10.1241666666667 & 1.00704362798091 & 1.00632853826856 \tabularnewline
57 & 10.16 & 10.2144210946549 & 10.26 & 0.995557611564802 & 0.99467213127885 \tabularnewline
58 & 10.31 & 10.3929706535659 & 10.3854166666667 & 1.00072736483683 & 0.99201665661036 \tabularnewline
59 & 10.46 & 10.3399121413955 & 10.5016666666667 & 0.984597251997667 & 1.01161401150825 \tabularnewline
60 & 10.54 & 10.4963608503453 & 10.61625 & 0.988707015221501 & 1.00415755043838 \tabularnewline
61 & 10.47 & 10.5802158349279 & 10.7254166666667 & 0.986461986862472 & 0.989582836810944 \tabularnewline
62 & 10.48 & 10.697849649585 & 10.8304166666667 & 0.987759749124915 & 0.979636127191841 \tabularnewline
63 & 10.46 & 10.7686459117866 & 10.9329166666667 & 0.98497466322222 & 0.971338465920885 \tabularnewline
64 & 11.3 & 11.2301692353285 & 11.0295833333333 & 1.01818617221822 & 1.00621814001269 \tabularnewline
65 & 11.58 & 11.3267720152275 & 11.1275 & 1.01790806697169 & 1.02235658883502 \tabularnewline
66 & 11.69 & 11.402575889594 & 11.2295833333333 & 1.01540507346761 & 1.02520694562255 \tabularnewline
67 & 11.63 & NA & NA & 1.01267141653116 & NA \tabularnewline
68 & 11.51 & NA & NA & 1.00704362798091 & NA \tabularnewline
69 & 11.37 & NA & NA & 0.995557611564802 & NA \tabularnewline
70 & 11.42 & NA & NA & 1.00072736483683 & NA \tabularnewline
71 & 11.7 & NA & NA & 0.984597251997667 & NA \tabularnewline
72 & 11.75 & NA & NA & 0.988707015221501 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198087&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]8.41[/C][C]NA[/C][C]NA[/C][C]0.986461986862472[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]8.39[/C][C]NA[/C][C]NA[/C][C]0.987759749124915[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]8.43[/C][C]NA[/C][C]NA[/C][C]0.98497466322222[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]8.44[/C][C]NA[/C][C]NA[/C][C]1.01818617221822[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]8.49[/C][C]NA[/C][C]NA[/C][C]1.01790806697169[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]8.47[/C][C]NA[/C][C]NA[/C][C]1.01540507346761[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]8.53[/C][C]8.59251696926691[/C][C]8.485[/C][C]1.01267141653116[/C][C]0.992724254198099[/C][/ROW]
[ROW][C]8[/C][C]8.52[/C][C]8.55735322876775[/C][C]8.4975[/C][C]1.00704362798091[/C][C]0.99563495536889[/C][/ROW]
[ROW][C]9[/C][C]8.51[/C][C]8.4796619565032[/C][C]8.5175[/C][C]0.995557611564802[/C][C]1.00357774209071[/C][/ROW]
[ROW][C]10[/C][C]8.53[/C][C]8.54579472597121[/C][C]8.53958333333333[/C][C]1.00072736483683[/C][C]0.998151754578984[/C][/ROW]
[ROW][C]11[/C][C]8.54[/C][C]8.42322949084005[/C][C]8.555[/C][C]0.984597251997667[/C][C]1.01386291437114[/C][/ROW]
[ROW][C]12[/C][C]8.53[/C][C]8.46497989532141[/C][C]8.56166666666667[/C][C]0.988707015221501[/C][C]1.00768107018358[/C][/ROW]
[ROW][C]13[/C][C]8.47[/C][C]8.45315717575567[/C][C]8.56916666666667[/C][C]0.986461986862472[/C][C]1.00199248918412[/C][/ROW]
[ROW][C]14[/C][C]8.63[/C][C]8.47374394780536[/C][C]8.57875[/C][C]0.987759749124915[/C][C]1.01844002523054[/C][/ROW]
[ROW][C]15[/C][C]8.67[/C][C]8.45231382877568[/C][C]8.58125[/C][C]0.98497466322222[/C][C]1.0257546247849[/C][/ROW]
[ROW][C]16[/C][C]8.73[/C][C]8.73815857882443[/C][C]8.58208333333333[/C][C]1.01818617221822[/C][C]0.999066327447502[/C][/ROW]
[ROW][C]17[/C][C]8.57[/C][C]8.7323788295334[/C][C]8.57875[/C][C]1.01790806697169[/C][C]0.981404971920799[/C][/ROW]
[ROW][C]18[/C][C]8.55[/C][C]8.70625233409022[/C][C]8.57416666666666[/C][C]1.01540507346761[/C][C]0.982052859474519[/C][/ROW]
[ROW][C]19[/C][C]8.63[/C][C]8.70095720012045[/C][C]8.59208333333333[/C][C]1.01267141653116[/C][C]0.991844897235045[/C][/ROW]
[ROW][C]20[/C][C]8.65[/C][C]8.67190444145057[/C][C]8.61125[/C][C]1.00704362798091[/C][C]0.997474091002909[/C][/ROW]
[ROW][C]21[/C][C]8.44[/C][C]8.58212142736008[/C][C]8.62041666666667[/C][C]0.995557611564802[/C][C]0.983439825623185[/C][/ROW]
[ROW][C]22[/C][C]8.62[/C][C]8.630439582247[/C][C]8.62416666666667[/C][C]1.00072736483683[/C][C]0.998790376533257[/C][/ROW]
[ROW][C]23[/C][C]8.37[/C][C]8.49420254275488[/C][C]8.62708333333333[/C][C]0.984597251997667[/C][C]0.985377963130769[/C][/ROW]
[ROW][C]24[/C][C]8.59[/C][C]8.5350133088996[/C][C]8.6325[/C][C]0.988707015221501[/C][C]1.00644248451764[/C][/ROW]
[ROW][C]25[/C][C]8.84[/C][C]8.52549772145892[/C][C]8.6425[/C][C]0.986461986862472[/C][C]1.03688960912505[/C][/ROW]
[ROW][C]26[/C][C]8.72[/C][C]8.55399942742176[/C][C]8.66[/C][C]0.987759749124915[/C][C]1.01940619402499[/C][/ROW]
[ROW][C]27[/C][C]8.8[/C][C]8.55491535619466[/C][C]8.68541666666667[/C][C]0.98497466322222[/C][C]1.02864840078492[/C][/ROW]
[ROW][C]28[/C][C]8.69[/C][C]8.87391673512019[/C][C]8.71541666666667[/C][C]1.01818617221822[/C][C]0.979274457873567[/C][/ROW]
[ROW][C]29[/C][C]8.68[/C][C]8.90075778894496[/C][C]8.74416666666667[/C][C]1.01790806697169[/C][C]0.975197865824508[/C][/ROW]
[ROW][C]30[/C][C]8.57[/C][C]8.90298706707457[/C][C]8.76791666666667[/C][C]1.01540507346761[/C][C]0.962598275773528[/C][/ROW]
[ROW][C]31[/C][C]8.85[/C][C]8.88408194794317[/C][C]8.77291666666667[/C][C]1.01267141653116[/C][C]0.99616370626218[/C][/ROW]
[ROW][C]32[/C][C]8.85[/C][C]8.84478026425396[/C][C]8.78291666666667[/C][C]1.00704362798091[/C][C]1.00059014871937[/C][/ROW]
[ROW][C]33[/C][C]8.85[/C][C]8.7654699541566[/C][C]8.80458333333333[/C][C]0.995557611564802[/C][C]1.00964352696267[/C][/ROW]
[ROW][C]34[/C][C]8.93[/C][C]8.83558869203855[/C][C]8.82916666666666[/C][C]1.00072736483683[/C][C]1.01068534437853[/C][/ROW]
[ROW][C]35[/C][C]8.75[/C][C]8.72148040842434[/C][C]8.85791666666667[/C][C]0.984597251997667[/C][C]1.0032700402042[/C][/ROW]
[ROW][C]36[/C][C]8.78[/C][C]8.7891934040628[/C][C]8.88958333333333[/C][C]0.988707015221501[/C][C]0.998954010494461[/C][/ROW]
[ROW][C]37[/C][C]8.77[/C][C]8.79348656122322[/C][C]8.91416666666667[/C][C]0.986461986862472[/C][C]0.997329095682389[/C][/ROW]
[ROW][C]38[/C][C]9.03[/C][C]8.816167327502[/C][C]8.92541666666667[/C][C]0.987759749124915[/C][C]1.02425460685517[/C][/ROW]
[ROW][C]39[/C][C]9.01[/C][C]8.80033820978086[/C][C]8.93458333333333[/C][C]0.98497466322222[/C][C]1.02382428779682[/C][/ROW]
[ROW][C]40[/C][C]9.07[/C][C]9.10131164691559[/C][C]8.93875[/C][C]1.01818617221822[/C][C]0.996559655560614[/C][/ROW]
[ROW][C]41[/C][C]8.99[/C][C]9.09924986200445[/C][C]8.93916666666667[/C][C]1.01790806697169[/C][C]0.987993530932628[/C][/ROW]
[ROW][C]42[/C][C]9.02[/C][C]9.08025986948412[/C][C]8.9425[/C][C]1.01540507346761[/C][C]0.993363640429869[/C][/ROW]
[ROW][C]43[/C][C]8.99[/C][C]9.0634091779539[/C][C]8.95[/C][C]1.01267141653116[/C][C]0.99190048948331[/C][/ROW]
[ROW][C]44[/C][C]8.98[/C][C]9.00926405682418[/C][C]8.94625[/C][C]1.00704362798091[/C][C]0.996751781650577[/C][/ROW]
[ROW][C]45[/C][C]8.94[/C][C]8.89157391828814[/C][C]8.93125[/C][C]0.995557611564802[/C][C]1.00544628905488[/C][/ROW]
[ROW][C]46[/C][C]8.94[/C][C]8.96568324946734[/C][C]8.95916666666667[/C][C]1.00072736483683[/C][C]0.997135382909176[/C][/ROW]
[ROW][C]47[/C][C]8.75[/C][C]8.9044513977539[/C][C]9.04375[/C][C]0.984597251997667[/C][C]0.982654585795946[/C][/ROW]
[ROW][C]48[/C][C]8.86[/C][C]9.04502134425136[/C][C]9.14833333333333[/C][C]0.988707015221501[/C][C]0.979544399376243[/C][/ROW]
[ROW][C]49[/C][C]8.87[/C][C]9.13504902417435[/C][C]9.26041666666667[/C][C]0.986461986862472[/C][C]0.970985484207808[/C][/ROW]
[ROW][C]50[/C][C]8.84[/C][C]9.25613198242472[/C][C]9.37083333333333[/C][C]0.987759749124915[/C][C]0.955042561707757[/C][/ROW]
[ROW][C]51[/C][C]8.84[/C][C]9.33263493403054[/C][C]9.475[/C][C]0.98497466322222[/C][C]0.947213735722782[/C][/ROW]
[ROW][C]52[/C][C]9.91[/C][C]9.75719323951949[/C][C]9.58291666666667[/C][C]1.01818617221822[/C][C]1.01566093411593[/C][/ROW]
[ROW][C]53[/C][C]10.18[/C][C]9.88515971537884[/C][C]9.71125[/C][C]1.01790806697169[/C][C]1.02982655749734[/C][/ROW]
[ROW][C]54[/C][C]10.34[/C][C]10.0042784863396[/C][C]9.8525[/C][C]1.01540507346761[/C][C]1.03355779370984[/C][/ROW]
[ROW][C]55[/C][C]10.36[/C][C]10.1157435582992[/C][C]9.98916666666667[/C][C]1.01267141653116[/C][C]1.02414616783167[/C][/ROW]
[ROW][C]56[/C][C]10.26[/C][C]10.1954775302834[/C][C]10.1241666666667[/C][C]1.00704362798091[/C][C]1.00632853826856[/C][/ROW]
[ROW][C]57[/C][C]10.16[/C][C]10.2144210946549[/C][C]10.26[/C][C]0.995557611564802[/C][C]0.99467213127885[/C][/ROW]
[ROW][C]58[/C][C]10.31[/C][C]10.3929706535659[/C][C]10.3854166666667[/C][C]1.00072736483683[/C][C]0.99201665661036[/C][/ROW]
[ROW][C]59[/C][C]10.46[/C][C]10.3399121413955[/C][C]10.5016666666667[/C][C]0.984597251997667[/C][C]1.01161401150825[/C][/ROW]
[ROW][C]60[/C][C]10.54[/C][C]10.4963608503453[/C][C]10.61625[/C][C]0.988707015221501[/C][C]1.00415755043838[/C][/ROW]
[ROW][C]61[/C][C]10.47[/C][C]10.5802158349279[/C][C]10.7254166666667[/C][C]0.986461986862472[/C][C]0.989582836810944[/C][/ROW]
[ROW][C]62[/C][C]10.48[/C][C]10.697849649585[/C][C]10.8304166666667[/C][C]0.987759749124915[/C][C]0.979636127191841[/C][/ROW]
[ROW][C]63[/C][C]10.46[/C][C]10.7686459117866[/C][C]10.9329166666667[/C][C]0.98497466322222[/C][C]0.971338465920885[/C][/ROW]
[ROW][C]64[/C][C]11.3[/C][C]11.2301692353285[/C][C]11.0295833333333[/C][C]1.01818617221822[/C][C]1.00621814001269[/C][/ROW]
[ROW][C]65[/C][C]11.58[/C][C]11.3267720152275[/C][C]11.1275[/C][C]1.01790806697169[/C][C]1.02235658883502[/C][/ROW]
[ROW][C]66[/C][C]11.69[/C][C]11.402575889594[/C][C]11.2295833333333[/C][C]1.01540507346761[/C][C]1.02520694562255[/C][/ROW]
[ROW][C]67[/C][C]11.63[/C][C]NA[/C][C]NA[/C][C]1.01267141653116[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]11.51[/C][C]NA[/C][C]NA[/C][C]1.00704362798091[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]11.37[/C][C]NA[/C][C]NA[/C][C]0.995557611564802[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]11.42[/C][C]NA[/C][C]NA[/C][C]1.00072736483683[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]11.7[/C][C]NA[/C][C]NA[/C][C]0.984597251997667[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]11.75[/C][C]NA[/C][C]NA[/C][C]0.988707015221501[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198087&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198087&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
18.41NANA0.986461986862472NA
28.39NANA0.987759749124915NA
38.43NANA0.98497466322222NA
48.44NANA1.01818617221822NA
58.49NANA1.01790806697169NA
68.47NANA1.01540507346761NA
78.538.592516969266918.4851.012671416531160.992724254198099
88.528.557353228767758.49751.007043627980910.99563495536889
98.518.47966195650328.51750.9955576115648021.00357774209071
108.538.545794725971218.539583333333331.000727364836830.998151754578984
118.548.423229490840058.5550.9845972519976671.01386291437114
128.538.464979895321418.561666666666670.9887070152215011.00768107018358
138.478.453157175755678.569166666666670.9864619868624721.00199248918412
148.638.473743947805368.578750.9877597491249151.01844002523054
158.678.452313828775688.581250.984974663222221.0257546247849
168.738.738158578824438.582083333333331.018186172218220.999066327447502
178.578.73237882953348.578751.017908066971690.981404971920799
188.558.706252334090228.574166666666661.015405073467610.982052859474519
198.638.700957200120458.592083333333331.012671416531160.991844897235045
208.658.671904441450578.611251.007043627980910.997474091002909
218.448.582121427360088.620416666666670.9955576115648020.983439825623185
228.628.6304395822478.624166666666671.000727364836830.998790376533257
238.378.494202542754888.627083333333330.9845972519976670.985377963130769
248.598.53501330889968.63250.9887070152215011.00644248451764
258.848.525497721458928.64250.9864619868624721.03688960912505
268.728.553999427421768.660.9877597491249151.01940619402499
278.88.554915356194668.685416666666670.984974663222221.02864840078492
288.698.873916735120198.715416666666671.018186172218220.979274457873567
298.688.900757788944968.744166666666671.017908066971690.975197865824508
308.578.902987067074578.767916666666671.015405073467610.962598275773528
318.858.884081947943178.772916666666671.012671416531160.99616370626218
328.858.844780264253968.782916666666671.007043627980911.00059014871937
338.858.76546995415668.804583333333330.9955576115648021.00964352696267
348.938.835588692038558.829166666666661.000727364836831.01068534437853
358.758.721480408424348.857916666666670.9845972519976671.0032700402042
368.788.78919340406288.889583333333330.9887070152215010.998954010494461
378.778.793486561223228.914166666666670.9864619868624720.997329095682389
389.038.8161673275028.925416666666670.9877597491249151.02425460685517
399.018.800338209780868.934583333333330.984974663222221.02382428779682
409.079.101311646915598.938751.018186172218220.996559655560614
418.999.099249862004458.939166666666671.017908066971690.987993530932628
429.029.080259869484128.94251.015405073467610.993363640429869
438.999.06340917795398.951.012671416531160.99190048948331
448.989.009264056824188.946251.007043627980910.996751781650577
458.948.891573918288148.931250.9955576115648021.00544628905488
468.948.965683249467348.959166666666671.000727364836830.997135382909176
478.758.90445139775399.043750.9845972519976670.982654585795946
488.869.045021344251369.148333333333330.9887070152215010.979544399376243
498.879.135049024174359.260416666666670.9864619868624720.970985484207808
508.849.256131982424729.370833333333330.9877597491249150.955042561707757
518.849.332634934030549.4750.984974663222220.947213735722782
529.919.757193239519499.582916666666671.018186172218221.01566093411593
5310.189.885159715378849.711251.017908066971691.02982655749734
5410.3410.00427848633969.85251.015405073467611.03355779370984
5510.3610.11574355829929.989166666666671.012671416531161.02414616783167
5610.2610.195477530283410.12416666666671.007043627980911.00632853826856
5710.1610.214421094654910.260.9955576115648020.99467213127885
5810.3110.392970653565910.38541666666671.000727364836830.99201665661036
5910.4610.339912141395510.50166666666670.9845972519976671.01161401150825
6010.5410.496360850345310.616250.9887070152215011.00415755043838
6110.4710.580215834927910.72541666666670.9864619868624720.989582836810944
6210.4810.69784964958510.83041666666670.9877597491249150.979636127191841
6310.4610.768645911786610.93291666666670.984974663222220.971338465920885
6411.311.230169235328511.02958333333331.018186172218221.00621814001269
6511.5811.326772015227511.12751.017908066971691.02235658883502
6611.6911.40257588959411.22958333333331.015405073467611.02520694562255
6711.63NANA1.01267141653116NA
6811.51NANA1.00704362798091NA
6911.37NANA0.995557611564802NA
7011.42NANA1.00072736483683NA
7111.7NANA0.984597251997667NA
7211.75NANA0.988707015221501NA


Figures (Output of Computation)

Input Parameters & R Code

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')