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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, 12 May 2011 18:10:20 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/May/12/t1305223592xjinspxjordnqbx.htm/, Retrieved Fri, 10 May 2024 15:37:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121522, Retrieved Fri, 10 May 2024 15:37:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W92
Estimated Impact154

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [opgave 9: classic...] [2011-05-12 18:10:20] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1664,81
2397,53
2840,71
3547,29
3752,96
3714,74
4349,61
3566,34
5021,82
6423,48
7600,60
19756,21
2499,81
5198,24
7225,14
4806,03
5900,88
4951,34
6179,12
4752,15
5496,43
5835,10
12600,08
28541,72
4717,02
5702,63
9957,58
5304,78
6492,43
6630,80
7349,62
8176,62
8573,17
9690,50
15151,84
34061,01
5921,10
5814,58
12421,25
6369,77
7609,12
7224,75
8121,22
7979,25
8093,06
8476,70
17914,66
30114,41
4826,64
6470,23
9638,77
8821,17
8722,37
10209,48
11276,55
12552,22
11637,39
13606,89
21822,11
45060,69
7615,03
9849,69
14558,40
11587,33
9332,56
13082,09
16732,78
19888,61
23933,38
25391,35
36024,80
80721,71
10243,24
11266,88
21826,84
17357,33
15997,79
18601,53
26155,15
28586,52
30505,41
30821,33
46634,38
104660,67

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ www.yougetit.org

\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 & 'Herman Ole Andreas Wold' @ www.yougetit.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121522&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]'Herman Ole Andreas Wold' @ www.yougetit.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121522&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121522&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ www.yougetit.org






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
11664.81NANA0.474541560006453NA
22397.53NANA0.604244670194867NA
32840.71NANA0.982889337904476NA
43547.29NANA0.656813757195405NA
53752.96NANA0.674859893085904NA
63714.74NANA0.679399190357424NA
74349.614217.04196136625421.133333333330.777889364099671.03143626263345
83566.344262.886120944925572.621250.7649696488784190.836602221785245
95021.824906.79244877415872.002083333330.8356251205532071.02344251411217
106423.485628.976484892686107.134166666670.9217050635003551.14114528942156
117600.69247.099284210176249.078333333331.479754099878220.821944240717558
1219756.2120111.61473169786390.13.14730829434560.982328384048764
132499.813092.992881870216517.854583333330.4745415600064530.808217184932047
145198.244014.295186373186643.492916666670.6042446701948671.29493217580157
157225.146597.818734004056712.677083333330.9828893379044761.09508010014929
164806.034405.865085062166707.936666666670.6568137571954051.09082550355311
175900.884650.953858126656891.73250.6748598930859041.26874619271686
184951.345072.46710753857466.107083333330.6793991903574240.976120671663206
196179.126164.426077361167924.553750.777889364099671.00238366434351
204752.156148.790657838478037.953750.7649696488784190.772859292898834
215496.436829.41509046828172.821666666660.8356251205532070.804817092999862
225835.17657.022954257568307.454583333330.9217050635003550.762058574834948
2312600.0812360.21397486878352.883751.479754099878221.01940630037789
2428541.7226586.91566681058447.509166666673.14730829434561.07352505110737
254717.024065.045197466988566.25750.4745415600064531.16038562201948
265702.635291.802360067038757.714583333330.6042446701948671.07763472858192
279957.588874.113038055459028.598333333330.9828893379044761.12209298634108
285304.786119.821131808369317.43750.6568137571954050.866819452030696
296492.436468.128846442279584.40250.6748598930859041.00375706083392
306630.86740.113000031949920.696250.6793991903574240.983781725910023
317349.627935.1223479179410200.83666666670.777889364099670.926213822264307
328176.627845.27723512510255.671250.7649696488784191.04223467889592
338573.178659.5737235102810362.988750.8356251205532070.990022173577009
349690.59687.13519509610510.016250.9217050635003551.00034734777994
3515151.8415686.754215916810600.91958333331.479754099878220.96590026154843
3634061.0133588.69177650910672.196253.14730829434561.01406182255128
375921.15091.4010833061310729.09416666670.4745415600064531.16296082416573
385814.586497.4552752674210753.02041666670.6042446701948670.894901119540324
3912421.2510541.283789950710724.79208333330.9828893379044761.1783431930598
406369.776997.8333420832510654.21250.6568137571954050.910248885421973
417609.127233.65785331410718.7550.6748598930859041.05190488053205
427224.757248.8026697412110669.43083333330.6793991903574240.996681842390108
438121.228136.245643005910459.38666666670.777889364099670.998153246145066
447979.257987.1268320659410441.10291666670.7649696488784190.99901380906657
458093.068650.7965261502710352.4850.8356251205532070.935527725745912
468476.79529.2229229604810338.690.9217050635003550.889547874840408
4717914.6615518.502475375410487.21708333331.479754099878221.15440649176212
4830114.4133543.905579480410657.966253.14730829434560.897760993532657
494826.645179.0526662266810913.80208333330.4745415600064530.93195422233784
506470.236789.1810772769211235.81458333330.6042446701948670.953020684873992
519638.7711375.996007570511574.03541666670.9828893379044760.847290205937628
528821.177839.3833576446311935.473750.6568137571954051.12523773842466
538722.378308.9034040274912312.04208333330.6748598930859041.04976187300145
5410209.488898.5084604472613097.61416666670.6793991903574241.14732486296775
5511276.5510763.311887365213836.558750.777889364099671.04768403238758
5612552.2210781.139907374614093.55250.7649696488784191.16427577304826
5711637.3912065.881843574314439.34791666670.8356251205532070.964487316457315
5813606.8913603.988070101614759.58916666670.9217050635003551.00021331464593
5921822.1122048.736238356714900.27041666671.479754099878220.989721576969004
6045060.6947352.471559015115045.38708333333.14730829434560.95160164858219
617615.037304.3439877027715392.42208333330.4745415600064531.04253441689223
629849.699622.8670241117815925.44791666670.6042446701948671.0235712470431
6314558.416456.971999465116743.463750.9828893379044760.884634184251708
6411587.3311656.352785746617746.81583333330.6568137571954050.994078526361095
659332.5612707.351122173918829.613750.6748598930859040.734422139616101
6613082.0914204.381178252120907.26833333330.6793991903574240.92098978729391
6716732.7817504.574367901422502.65291666670.777889364099670.955908989748606
6819888.6117342.78850956122671.211250.7649696488784191.14679424182769
6923933.3819247.047409528123033.11250.8356251205532071.24348319463026
7025391.3521730.46959309623576.38083333330.9217050635003551.16846761599975
7136024.835653.957972391524094.51541666671.479754099878221.01040114614752
7280721.7177430.739592232224602.213.14730829434561.04250211770027
7310243.2411970.20902245325224.78541666670.4745415600064530.855727747175202
7411266.8815698.153920348325979.79708333330.6042446701948670.717720061681623
7521826.8426160.626438148526616.04458333330.9828893379044760.834339347783018
7617357.3317810.246131209427116.12833333330.6568137571954050.97456991173099
7715997.7918750.606457384727784.44333333330.6748598930859040.853187870822144
7818601.5319854.738726199729223.96583333330.6793991903574240.936881127297535
7926155.15NANA0.77788936409967NA
8028586.52NANA0.764969648878419NA
8130505.41NANA0.835625120553207NA
8230821.33NANA0.921705063500355NA
8346634.38NANA1.47975409987822NA
84104660.67NANA3.1473082943456NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1664.81 & NA & NA & 0.474541560006453 & NA \tabularnewline
2 & 2397.53 & NA & NA & 0.604244670194867 & NA \tabularnewline
3 & 2840.71 & NA & NA & 0.982889337904476 & NA \tabularnewline
4 & 3547.29 & NA & NA & 0.656813757195405 & NA \tabularnewline
5 & 3752.96 & NA & NA & 0.674859893085904 & NA \tabularnewline
6 & 3714.74 & NA & NA & 0.679399190357424 & NA \tabularnewline
7 & 4349.61 & 4217.0419613662 & 5421.13333333333 & 0.77788936409967 & 1.03143626263345 \tabularnewline
8 & 3566.34 & 4262.88612094492 & 5572.62125 & 0.764969648878419 & 0.836602221785245 \tabularnewline
9 & 5021.82 & 4906.7924487741 & 5872.00208333333 & 0.835625120553207 & 1.02344251411217 \tabularnewline
10 & 6423.48 & 5628.97648489268 & 6107.13416666667 & 0.921705063500355 & 1.14114528942156 \tabularnewline
11 & 7600.6 & 9247.09928421017 & 6249.07833333333 & 1.47975409987822 & 0.821944240717558 \tabularnewline
12 & 19756.21 & 20111.6147316978 & 6390.1 & 3.1473082943456 & 0.982328384048764 \tabularnewline
13 & 2499.81 & 3092.99288187021 & 6517.85458333333 & 0.474541560006453 & 0.808217184932047 \tabularnewline
14 & 5198.24 & 4014.29518637318 & 6643.49291666667 & 0.604244670194867 & 1.29493217580157 \tabularnewline
15 & 7225.14 & 6597.81873400405 & 6712.67708333333 & 0.982889337904476 & 1.09508010014929 \tabularnewline
16 & 4806.03 & 4405.86508506216 & 6707.93666666667 & 0.656813757195405 & 1.09082550355311 \tabularnewline
17 & 5900.88 & 4650.95385812665 & 6891.7325 & 0.674859893085904 & 1.26874619271686 \tabularnewline
18 & 4951.34 & 5072.4671075385 & 7466.10708333333 & 0.679399190357424 & 0.976120671663206 \tabularnewline
19 & 6179.12 & 6164.42607736116 & 7924.55375 & 0.77788936409967 & 1.00238366434351 \tabularnewline
20 & 4752.15 & 6148.79065783847 & 8037.95375 & 0.764969648878419 & 0.772859292898834 \tabularnewline
21 & 5496.43 & 6829.4150904682 & 8172.82166666666 & 0.835625120553207 & 0.804817092999862 \tabularnewline
22 & 5835.1 & 7657.02295425756 & 8307.45458333333 & 0.921705063500355 & 0.762058574834948 \tabularnewline
23 & 12600.08 & 12360.2139748687 & 8352.88375 & 1.47975409987822 & 1.01940630037789 \tabularnewline
24 & 28541.72 & 26586.9156668105 & 8447.50916666667 & 3.1473082943456 & 1.07352505110737 \tabularnewline
25 & 4717.02 & 4065.04519746698 & 8566.2575 & 0.474541560006453 & 1.16038562201948 \tabularnewline
26 & 5702.63 & 5291.80236006703 & 8757.71458333333 & 0.604244670194867 & 1.07763472858192 \tabularnewline
27 & 9957.58 & 8874.11303805545 & 9028.59833333333 & 0.982889337904476 & 1.12209298634108 \tabularnewline
28 & 5304.78 & 6119.82113180836 & 9317.4375 & 0.656813757195405 & 0.866819452030696 \tabularnewline
29 & 6492.43 & 6468.12884644227 & 9584.4025 & 0.674859893085904 & 1.00375706083392 \tabularnewline
30 & 6630.8 & 6740.11300003194 & 9920.69625 & 0.679399190357424 & 0.983781725910023 \tabularnewline
31 & 7349.62 & 7935.12234791794 & 10200.8366666667 & 0.77788936409967 & 0.926213822264307 \tabularnewline
32 & 8176.62 & 7845.277235125 & 10255.67125 & 0.764969648878419 & 1.04223467889592 \tabularnewline
33 & 8573.17 & 8659.57372351028 & 10362.98875 & 0.835625120553207 & 0.990022173577009 \tabularnewline
34 & 9690.5 & 9687.135195096 & 10510.01625 & 0.921705063500355 & 1.00034734777994 \tabularnewline
35 & 15151.84 & 15686.7542159168 & 10600.9195833333 & 1.47975409987822 & 0.96590026154843 \tabularnewline
36 & 34061.01 & 33588.691776509 & 10672.19625 & 3.1473082943456 & 1.01406182255128 \tabularnewline
37 & 5921.1 & 5091.40108330613 & 10729.0941666667 & 0.474541560006453 & 1.16296082416573 \tabularnewline
38 & 5814.58 & 6497.45527526742 & 10753.0204166667 & 0.604244670194867 & 0.894901119540324 \tabularnewline
39 & 12421.25 & 10541.2837899507 & 10724.7920833333 & 0.982889337904476 & 1.1783431930598 \tabularnewline
40 & 6369.77 & 6997.83334208325 & 10654.2125 & 0.656813757195405 & 0.910248885421973 \tabularnewline
41 & 7609.12 & 7233.657853314 & 10718.755 & 0.674859893085904 & 1.05190488053205 \tabularnewline
42 & 7224.75 & 7248.80266974121 & 10669.4308333333 & 0.679399190357424 & 0.996681842390108 \tabularnewline
43 & 8121.22 & 8136.2456430059 & 10459.3866666667 & 0.77788936409967 & 0.998153246145066 \tabularnewline
44 & 7979.25 & 7987.12683206594 & 10441.1029166667 & 0.764969648878419 & 0.99901380906657 \tabularnewline
45 & 8093.06 & 8650.79652615027 & 10352.485 & 0.835625120553207 & 0.935527725745912 \tabularnewline
46 & 8476.7 & 9529.22292296048 & 10338.69 & 0.921705063500355 & 0.889547874840408 \tabularnewline
47 & 17914.66 & 15518.5024753754 & 10487.2170833333 & 1.47975409987822 & 1.15440649176212 \tabularnewline
48 & 30114.41 & 33543.9055794804 & 10657.96625 & 3.1473082943456 & 0.897760993532657 \tabularnewline
49 & 4826.64 & 5179.05266622668 & 10913.8020833333 & 0.474541560006453 & 0.93195422233784 \tabularnewline
50 & 6470.23 & 6789.18107727692 & 11235.8145833333 & 0.604244670194867 & 0.953020684873992 \tabularnewline
51 & 9638.77 & 11375.9960075705 & 11574.0354166667 & 0.982889337904476 & 0.847290205937628 \tabularnewline
52 & 8821.17 & 7839.38335764463 & 11935.47375 & 0.656813757195405 & 1.12523773842466 \tabularnewline
53 & 8722.37 & 8308.90340402749 & 12312.0420833333 & 0.674859893085904 & 1.04976187300145 \tabularnewline
54 & 10209.48 & 8898.50846044726 & 13097.6141666667 & 0.679399190357424 & 1.14732486296775 \tabularnewline
55 & 11276.55 & 10763.3118873652 & 13836.55875 & 0.77788936409967 & 1.04768403238758 \tabularnewline
56 & 12552.22 & 10781.1399073746 & 14093.5525 & 0.764969648878419 & 1.16427577304826 \tabularnewline
57 & 11637.39 & 12065.8818435743 & 14439.3479166667 & 0.835625120553207 & 0.964487316457315 \tabularnewline
58 & 13606.89 & 13603.9880701016 & 14759.5891666667 & 0.921705063500355 & 1.00021331464593 \tabularnewline
59 & 21822.11 & 22048.7362383567 & 14900.2704166667 & 1.47975409987822 & 0.989721576969004 \tabularnewline
60 & 45060.69 & 47352.4715590151 & 15045.3870833333 & 3.1473082943456 & 0.95160164858219 \tabularnewline
61 & 7615.03 & 7304.34398770277 & 15392.4220833333 & 0.474541560006453 & 1.04253441689223 \tabularnewline
62 & 9849.69 & 9622.86702411178 & 15925.4479166667 & 0.604244670194867 & 1.0235712470431 \tabularnewline
63 & 14558.4 & 16456.9719994651 & 16743.46375 & 0.982889337904476 & 0.884634184251708 \tabularnewline
64 & 11587.33 & 11656.3527857466 & 17746.8158333333 & 0.656813757195405 & 0.994078526361095 \tabularnewline
65 & 9332.56 & 12707.3511221739 & 18829.61375 & 0.674859893085904 & 0.734422139616101 \tabularnewline
66 & 13082.09 & 14204.3811782521 & 20907.2683333333 & 0.679399190357424 & 0.92098978729391 \tabularnewline
67 & 16732.78 & 17504.5743679014 & 22502.6529166667 & 0.77788936409967 & 0.955908989748606 \tabularnewline
68 & 19888.61 & 17342.788509561 & 22671.21125 & 0.764969648878419 & 1.14679424182769 \tabularnewline
69 & 23933.38 & 19247.0474095281 & 23033.1125 & 0.835625120553207 & 1.24348319463026 \tabularnewline
70 & 25391.35 & 21730.469593096 & 23576.3808333333 & 0.921705063500355 & 1.16846761599975 \tabularnewline
71 & 36024.8 & 35653.9579723915 & 24094.5154166667 & 1.47975409987822 & 1.01040114614752 \tabularnewline
72 & 80721.71 & 77430.7395922322 & 24602.21 & 3.1473082943456 & 1.04250211770027 \tabularnewline
73 & 10243.24 & 11970.209022453 & 25224.7854166667 & 0.474541560006453 & 0.855727747175202 \tabularnewline
74 & 11266.88 & 15698.1539203483 & 25979.7970833333 & 0.604244670194867 & 0.717720061681623 \tabularnewline
75 & 21826.84 & 26160.6264381485 & 26616.0445833333 & 0.982889337904476 & 0.834339347783018 \tabularnewline
76 & 17357.33 & 17810.2461312094 & 27116.1283333333 & 0.656813757195405 & 0.97456991173099 \tabularnewline
77 & 15997.79 & 18750.6064573847 & 27784.4433333333 & 0.674859893085904 & 0.853187870822144 \tabularnewline
78 & 18601.53 & 19854.7387261997 & 29223.9658333333 & 0.679399190357424 & 0.936881127297535 \tabularnewline
79 & 26155.15 & NA & NA & 0.77788936409967 & NA \tabularnewline
80 & 28586.52 & NA & NA & 0.764969648878419 & NA \tabularnewline
81 & 30505.41 & NA & NA & 0.835625120553207 & NA \tabularnewline
82 & 30821.33 & NA & NA & 0.921705063500355 & NA \tabularnewline
83 & 46634.38 & NA & NA & 1.47975409987822 & NA \tabularnewline
84 & 104660.67 & NA & NA & 3.1473082943456 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121522&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]1664.81[/C][C]NA[/C][C]NA[/C][C]0.474541560006453[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2397.53[/C][C]NA[/C][C]NA[/C][C]0.604244670194867[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2840.71[/C][C]NA[/C][C]NA[/C][C]0.982889337904476[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3547.29[/C][C]NA[/C][C]NA[/C][C]0.656813757195405[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]3752.96[/C][C]NA[/C][C]NA[/C][C]0.674859893085904[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3714.74[/C][C]NA[/C][C]NA[/C][C]0.679399190357424[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]4349.61[/C][C]4217.0419613662[/C][C]5421.13333333333[/C][C]0.77788936409967[/C][C]1.03143626263345[/C][/ROW]
[ROW][C]8[/C][C]3566.34[/C][C]4262.88612094492[/C][C]5572.62125[/C][C]0.764969648878419[/C][C]0.836602221785245[/C][/ROW]
[ROW][C]9[/C][C]5021.82[/C][C]4906.7924487741[/C][C]5872.00208333333[/C][C]0.835625120553207[/C][C]1.02344251411217[/C][/ROW]
[ROW][C]10[/C][C]6423.48[/C][C]5628.97648489268[/C][C]6107.13416666667[/C][C]0.921705063500355[/C][C]1.14114528942156[/C][/ROW]
[ROW][C]11[/C][C]7600.6[/C][C]9247.09928421017[/C][C]6249.07833333333[/C][C]1.47975409987822[/C][C]0.821944240717558[/C][/ROW]
[ROW][C]12[/C][C]19756.21[/C][C]20111.6147316978[/C][C]6390.1[/C][C]3.1473082943456[/C][C]0.982328384048764[/C][/ROW]
[ROW][C]13[/C][C]2499.81[/C][C]3092.99288187021[/C][C]6517.85458333333[/C][C]0.474541560006453[/C][C]0.808217184932047[/C][/ROW]
[ROW][C]14[/C][C]5198.24[/C][C]4014.29518637318[/C][C]6643.49291666667[/C][C]0.604244670194867[/C][C]1.29493217580157[/C][/ROW]
[ROW][C]15[/C][C]7225.14[/C][C]6597.81873400405[/C][C]6712.67708333333[/C][C]0.982889337904476[/C][C]1.09508010014929[/C][/ROW]
[ROW][C]16[/C][C]4806.03[/C][C]4405.86508506216[/C][C]6707.93666666667[/C][C]0.656813757195405[/C][C]1.09082550355311[/C][/ROW]
[ROW][C]17[/C][C]5900.88[/C][C]4650.95385812665[/C][C]6891.7325[/C][C]0.674859893085904[/C][C]1.26874619271686[/C][/ROW]
[ROW][C]18[/C][C]4951.34[/C][C]5072.4671075385[/C][C]7466.10708333333[/C][C]0.679399190357424[/C][C]0.976120671663206[/C][/ROW]
[ROW][C]19[/C][C]6179.12[/C][C]6164.42607736116[/C][C]7924.55375[/C][C]0.77788936409967[/C][C]1.00238366434351[/C][/ROW]
[ROW][C]20[/C][C]4752.15[/C][C]6148.79065783847[/C][C]8037.95375[/C][C]0.764969648878419[/C][C]0.772859292898834[/C][/ROW]
[ROW][C]21[/C][C]5496.43[/C][C]6829.4150904682[/C][C]8172.82166666666[/C][C]0.835625120553207[/C][C]0.804817092999862[/C][/ROW]
[ROW][C]22[/C][C]5835.1[/C][C]7657.02295425756[/C][C]8307.45458333333[/C][C]0.921705063500355[/C][C]0.762058574834948[/C][/ROW]
[ROW][C]23[/C][C]12600.08[/C][C]12360.2139748687[/C][C]8352.88375[/C][C]1.47975409987822[/C][C]1.01940630037789[/C][/ROW]
[ROW][C]24[/C][C]28541.72[/C][C]26586.9156668105[/C][C]8447.50916666667[/C][C]3.1473082943456[/C][C]1.07352505110737[/C][/ROW]
[ROW][C]25[/C][C]4717.02[/C][C]4065.04519746698[/C][C]8566.2575[/C][C]0.474541560006453[/C][C]1.16038562201948[/C][/ROW]
[ROW][C]26[/C][C]5702.63[/C][C]5291.80236006703[/C][C]8757.71458333333[/C][C]0.604244670194867[/C][C]1.07763472858192[/C][/ROW]
[ROW][C]27[/C][C]9957.58[/C][C]8874.11303805545[/C][C]9028.59833333333[/C][C]0.982889337904476[/C][C]1.12209298634108[/C][/ROW]
[ROW][C]28[/C][C]5304.78[/C][C]6119.82113180836[/C][C]9317.4375[/C][C]0.656813757195405[/C][C]0.866819452030696[/C][/ROW]
[ROW][C]29[/C][C]6492.43[/C][C]6468.12884644227[/C][C]9584.4025[/C][C]0.674859893085904[/C][C]1.00375706083392[/C][/ROW]
[ROW][C]30[/C][C]6630.8[/C][C]6740.11300003194[/C][C]9920.69625[/C][C]0.679399190357424[/C][C]0.983781725910023[/C][/ROW]
[ROW][C]31[/C][C]7349.62[/C][C]7935.12234791794[/C][C]10200.8366666667[/C][C]0.77788936409967[/C][C]0.926213822264307[/C][/ROW]
[ROW][C]32[/C][C]8176.62[/C][C]7845.277235125[/C][C]10255.67125[/C][C]0.764969648878419[/C][C]1.04223467889592[/C][/ROW]
[ROW][C]33[/C][C]8573.17[/C][C]8659.57372351028[/C][C]10362.98875[/C][C]0.835625120553207[/C][C]0.990022173577009[/C][/ROW]
[ROW][C]34[/C][C]9690.5[/C][C]9687.135195096[/C][C]10510.01625[/C][C]0.921705063500355[/C][C]1.00034734777994[/C][/ROW]
[ROW][C]35[/C][C]15151.84[/C][C]15686.7542159168[/C][C]10600.9195833333[/C][C]1.47975409987822[/C][C]0.96590026154843[/C][/ROW]
[ROW][C]36[/C][C]34061.01[/C][C]33588.691776509[/C][C]10672.19625[/C][C]3.1473082943456[/C][C]1.01406182255128[/C][/ROW]
[ROW][C]37[/C][C]5921.1[/C][C]5091.40108330613[/C][C]10729.0941666667[/C][C]0.474541560006453[/C][C]1.16296082416573[/C][/ROW]
[ROW][C]38[/C][C]5814.58[/C][C]6497.45527526742[/C][C]10753.0204166667[/C][C]0.604244670194867[/C][C]0.894901119540324[/C][/ROW]
[ROW][C]39[/C][C]12421.25[/C][C]10541.2837899507[/C][C]10724.7920833333[/C][C]0.982889337904476[/C][C]1.1783431930598[/C][/ROW]
[ROW][C]40[/C][C]6369.77[/C][C]6997.83334208325[/C][C]10654.2125[/C][C]0.656813757195405[/C][C]0.910248885421973[/C][/ROW]
[ROW][C]41[/C][C]7609.12[/C][C]7233.657853314[/C][C]10718.755[/C][C]0.674859893085904[/C][C]1.05190488053205[/C][/ROW]
[ROW][C]42[/C][C]7224.75[/C][C]7248.80266974121[/C][C]10669.4308333333[/C][C]0.679399190357424[/C][C]0.996681842390108[/C][/ROW]
[ROW][C]43[/C][C]8121.22[/C][C]8136.2456430059[/C][C]10459.3866666667[/C][C]0.77788936409967[/C][C]0.998153246145066[/C][/ROW]
[ROW][C]44[/C][C]7979.25[/C][C]7987.12683206594[/C][C]10441.1029166667[/C][C]0.764969648878419[/C][C]0.99901380906657[/C][/ROW]
[ROW][C]45[/C][C]8093.06[/C][C]8650.79652615027[/C][C]10352.485[/C][C]0.835625120553207[/C][C]0.935527725745912[/C][/ROW]
[ROW][C]46[/C][C]8476.7[/C][C]9529.22292296048[/C][C]10338.69[/C][C]0.921705063500355[/C][C]0.889547874840408[/C][/ROW]
[ROW][C]47[/C][C]17914.66[/C][C]15518.5024753754[/C][C]10487.2170833333[/C][C]1.47975409987822[/C][C]1.15440649176212[/C][/ROW]
[ROW][C]48[/C][C]30114.41[/C][C]33543.9055794804[/C][C]10657.96625[/C][C]3.1473082943456[/C][C]0.897760993532657[/C][/ROW]
[ROW][C]49[/C][C]4826.64[/C][C]5179.05266622668[/C][C]10913.8020833333[/C][C]0.474541560006453[/C][C]0.93195422233784[/C][/ROW]
[ROW][C]50[/C][C]6470.23[/C][C]6789.18107727692[/C][C]11235.8145833333[/C][C]0.604244670194867[/C][C]0.953020684873992[/C][/ROW]
[ROW][C]51[/C][C]9638.77[/C][C]11375.9960075705[/C][C]11574.0354166667[/C][C]0.982889337904476[/C][C]0.847290205937628[/C][/ROW]
[ROW][C]52[/C][C]8821.17[/C][C]7839.38335764463[/C][C]11935.47375[/C][C]0.656813757195405[/C][C]1.12523773842466[/C][/ROW]
[ROW][C]53[/C][C]8722.37[/C][C]8308.90340402749[/C][C]12312.0420833333[/C][C]0.674859893085904[/C][C]1.04976187300145[/C][/ROW]
[ROW][C]54[/C][C]10209.48[/C][C]8898.50846044726[/C][C]13097.6141666667[/C][C]0.679399190357424[/C][C]1.14732486296775[/C][/ROW]
[ROW][C]55[/C][C]11276.55[/C][C]10763.3118873652[/C][C]13836.55875[/C][C]0.77788936409967[/C][C]1.04768403238758[/C][/ROW]
[ROW][C]56[/C][C]12552.22[/C][C]10781.1399073746[/C][C]14093.5525[/C][C]0.764969648878419[/C][C]1.16427577304826[/C][/ROW]
[ROW][C]57[/C][C]11637.39[/C][C]12065.8818435743[/C][C]14439.3479166667[/C][C]0.835625120553207[/C][C]0.964487316457315[/C][/ROW]
[ROW][C]58[/C][C]13606.89[/C][C]13603.9880701016[/C][C]14759.5891666667[/C][C]0.921705063500355[/C][C]1.00021331464593[/C][/ROW]
[ROW][C]59[/C][C]21822.11[/C][C]22048.7362383567[/C][C]14900.2704166667[/C][C]1.47975409987822[/C][C]0.989721576969004[/C][/ROW]
[ROW][C]60[/C][C]45060.69[/C][C]47352.4715590151[/C][C]15045.3870833333[/C][C]3.1473082943456[/C][C]0.95160164858219[/C][/ROW]
[ROW][C]61[/C][C]7615.03[/C][C]7304.34398770277[/C][C]15392.4220833333[/C][C]0.474541560006453[/C][C]1.04253441689223[/C][/ROW]
[ROW][C]62[/C][C]9849.69[/C][C]9622.86702411178[/C][C]15925.4479166667[/C][C]0.604244670194867[/C][C]1.0235712470431[/C][/ROW]
[ROW][C]63[/C][C]14558.4[/C][C]16456.9719994651[/C][C]16743.46375[/C][C]0.982889337904476[/C][C]0.884634184251708[/C][/ROW]
[ROW][C]64[/C][C]11587.33[/C][C]11656.3527857466[/C][C]17746.8158333333[/C][C]0.656813757195405[/C][C]0.994078526361095[/C][/ROW]
[ROW][C]65[/C][C]9332.56[/C][C]12707.3511221739[/C][C]18829.61375[/C][C]0.674859893085904[/C][C]0.734422139616101[/C][/ROW]
[ROW][C]66[/C][C]13082.09[/C][C]14204.3811782521[/C][C]20907.2683333333[/C][C]0.679399190357424[/C][C]0.92098978729391[/C][/ROW]
[ROW][C]67[/C][C]16732.78[/C][C]17504.5743679014[/C][C]22502.6529166667[/C][C]0.77788936409967[/C][C]0.955908989748606[/C][/ROW]
[ROW][C]68[/C][C]19888.61[/C][C]17342.788509561[/C][C]22671.21125[/C][C]0.764969648878419[/C][C]1.14679424182769[/C][/ROW]
[ROW][C]69[/C][C]23933.38[/C][C]19247.0474095281[/C][C]23033.1125[/C][C]0.835625120553207[/C][C]1.24348319463026[/C][/ROW]
[ROW][C]70[/C][C]25391.35[/C][C]21730.469593096[/C][C]23576.3808333333[/C][C]0.921705063500355[/C][C]1.16846761599975[/C][/ROW]
[ROW][C]71[/C][C]36024.8[/C][C]35653.9579723915[/C][C]24094.5154166667[/C][C]1.47975409987822[/C][C]1.01040114614752[/C][/ROW]
[ROW][C]72[/C][C]80721.71[/C][C]77430.7395922322[/C][C]24602.21[/C][C]3.1473082943456[/C][C]1.04250211770027[/C][/ROW]
[ROW][C]73[/C][C]10243.24[/C][C]11970.209022453[/C][C]25224.7854166667[/C][C]0.474541560006453[/C][C]0.855727747175202[/C][/ROW]
[ROW][C]74[/C][C]11266.88[/C][C]15698.1539203483[/C][C]25979.7970833333[/C][C]0.604244670194867[/C][C]0.717720061681623[/C][/ROW]
[ROW][C]75[/C][C]21826.84[/C][C]26160.6264381485[/C][C]26616.0445833333[/C][C]0.982889337904476[/C][C]0.834339347783018[/C][/ROW]
[ROW][C]76[/C][C]17357.33[/C][C]17810.2461312094[/C][C]27116.1283333333[/C][C]0.656813757195405[/C][C]0.97456991173099[/C][/ROW]
[ROW][C]77[/C][C]15997.79[/C][C]18750.6064573847[/C][C]27784.4433333333[/C][C]0.674859893085904[/C][C]0.853187870822144[/C][/ROW]
[ROW][C]78[/C][C]18601.53[/C][C]19854.7387261997[/C][C]29223.9658333333[/C][C]0.679399190357424[/C][C]0.936881127297535[/C][/ROW]
[ROW][C]79[/C][C]26155.15[/C][C]NA[/C][C]NA[/C][C]0.77788936409967[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]28586.52[/C][C]NA[/C][C]NA[/C][C]0.764969648878419[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]30505.41[/C][C]NA[/C][C]NA[/C][C]0.835625120553207[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]30821.33[/C][C]NA[/C][C]NA[/C][C]0.921705063500355[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]46634.38[/C][C]NA[/C][C]NA[/C][C]1.47975409987822[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]104660.67[/C][C]NA[/C][C]NA[/C][C]3.1473082943456[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121522&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121522&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
11664.81NANA0.474541560006453NA
22397.53NANA0.604244670194867NA
32840.71NANA0.982889337904476NA
43547.29NANA0.656813757195405NA
53752.96NANA0.674859893085904NA
63714.74NANA0.679399190357424NA
74349.614217.04196136625421.133333333330.777889364099671.03143626263345
83566.344262.886120944925572.621250.7649696488784190.836602221785245
95021.824906.79244877415872.002083333330.8356251205532071.02344251411217
106423.485628.976484892686107.134166666670.9217050635003551.14114528942156
117600.69247.099284210176249.078333333331.479754099878220.821944240717558
1219756.2120111.61473169786390.13.14730829434560.982328384048764
132499.813092.992881870216517.854583333330.4745415600064530.808217184932047
145198.244014.295186373186643.492916666670.6042446701948671.29493217580157
157225.146597.818734004056712.677083333330.9828893379044761.09508010014929
164806.034405.865085062166707.936666666670.6568137571954051.09082550355311
175900.884650.953858126656891.73250.6748598930859041.26874619271686
184951.345072.46710753857466.107083333330.6793991903574240.976120671663206
196179.126164.426077361167924.553750.777889364099671.00238366434351
204752.156148.790657838478037.953750.7649696488784190.772859292898834
215496.436829.41509046828172.821666666660.8356251205532070.804817092999862
225835.17657.022954257568307.454583333330.9217050635003550.762058574834948
2312600.0812360.21397486878352.883751.479754099878221.01940630037789
2428541.7226586.91566681058447.509166666673.14730829434561.07352505110737
254717.024065.045197466988566.25750.4745415600064531.16038562201948
265702.635291.802360067038757.714583333330.6042446701948671.07763472858192
279957.588874.113038055459028.598333333330.9828893379044761.12209298634108
285304.786119.821131808369317.43750.6568137571954050.866819452030696
296492.436468.128846442279584.40250.6748598930859041.00375706083392
306630.86740.113000031949920.696250.6793991903574240.983781725910023
317349.627935.1223479179410200.83666666670.777889364099670.926213822264307
328176.627845.27723512510255.671250.7649696488784191.04223467889592
338573.178659.5737235102810362.988750.8356251205532070.990022173577009
349690.59687.13519509610510.016250.9217050635003551.00034734777994
3515151.8415686.754215916810600.91958333331.479754099878220.96590026154843
3634061.0133588.69177650910672.196253.14730829434561.01406182255128
375921.15091.4010833061310729.09416666670.4745415600064531.16296082416573
385814.586497.4552752674210753.02041666670.6042446701948670.894901119540324
3912421.2510541.283789950710724.79208333330.9828893379044761.1783431930598
406369.776997.8333420832510654.21250.6568137571954050.910248885421973
417609.127233.65785331410718.7550.6748598930859041.05190488053205
427224.757248.8026697412110669.43083333330.6793991903574240.996681842390108
438121.228136.245643005910459.38666666670.777889364099670.998153246145066
447979.257987.1268320659410441.10291666670.7649696488784190.99901380906657
458093.068650.7965261502710352.4850.8356251205532070.935527725745912
468476.79529.2229229604810338.690.9217050635003550.889547874840408
4717914.6615518.502475375410487.21708333331.479754099878221.15440649176212
4830114.4133543.905579480410657.966253.14730829434560.897760993532657
494826.645179.0526662266810913.80208333330.4745415600064530.93195422233784
506470.236789.1810772769211235.81458333330.6042446701948670.953020684873992
519638.7711375.996007570511574.03541666670.9828893379044760.847290205937628
528821.177839.3833576446311935.473750.6568137571954051.12523773842466
538722.378308.9034040274912312.04208333330.6748598930859041.04976187300145
5410209.488898.5084604472613097.61416666670.6793991903574241.14732486296775
5511276.5510763.311887365213836.558750.777889364099671.04768403238758
5612552.2210781.139907374614093.55250.7649696488784191.16427577304826
5711637.3912065.881843574314439.34791666670.8356251205532070.964487316457315
5813606.8913603.988070101614759.58916666670.9217050635003551.00021331464593
5921822.1122048.736238356714900.27041666671.479754099878220.989721576969004
6045060.6947352.471559015115045.38708333333.14730829434560.95160164858219
617615.037304.3439877027715392.42208333330.4745415600064531.04253441689223
629849.699622.8670241117815925.44791666670.6042446701948671.0235712470431
6314558.416456.971999465116743.463750.9828893379044760.884634184251708
6411587.3311656.352785746617746.81583333330.6568137571954050.994078526361095
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6613082.0914204.381178252120907.26833333330.6793991903574240.92098978729391
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6923933.3819247.047409528123033.11250.8356251205532071.24348319463026
7025391.3521730.46959309623576.38083333330.9217050635003551.16846761599975
7136024.835653.957972391524094.51541666671.479754099878221.01040114614752
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7715997.7918750.606457384727784.44333333330.6748598930859040.853187870822144
7818601.5319854.738726199729223.96583333330.6793991903574240.936881127297535
7926155.15NANA0.77788936409967NA
8028586.52NANA0.764969648878419NA
8130505.41NANA0.835625120553207NA
8230821.33NANA0.921705063500355NA
8346634.38NANA1.47975409987822NA
84104660.67NANA3.1473082943456NA


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')