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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 computationFri, 03 Jan 2014 11:39:25 -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/2014/Jan/03/t138876719043d8b8nmbv9plz8.htm/, Retrieved Sun, 19 May 2024 07:09:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232756, Retrieved Sun, 19 May 2024 07:09:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2014-01-03 16:39:25] [1177af5e7ddeef06deae586abecaeb9d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
 15,13 
 15,25 
 15,33 
 15,36 
 15,40 
 15,40 
 15,41 
 15,47 
 15,54 
 15,55 
 15,59 
 15,65 
 15,75 
 15,86 
 15,89 
 15,94 
 15,93 
 15,95 
 15,99 
 15,99 
 16,06 
 16,08 
 16,07 
 16,11 
 16,15 
 16,18 
 16,30 
 16,42 
 16,49 
 16,50 
 16,58 
 16,64 
 16,66 
 16,81 
 16,91 
 16,92 
 16,95 
 17,11 
 17,16 
 17,16 
 17,27 
 17,34 
 17,39 
 17,43 
 17,45 
 17,50 
 17,56 
 17,65 
 17,62 
 17,70 
 17,72 
 17,71 
 17,74 
 17,75 
 17,78 
 17,80 
 17,86 
 17,88 
 17,89 
 17,94 
 17,98 
 18,10 
 18,14 
 18,19 
 18,23 
 18,24 
 18,27 
 18,30 
 18,34 
 18,36 
 18,36 
 18,40 
 18,43 
 18,47 
 18,56 
 18,58 
 18,61 
 18,61 
 18,69 
 18,74 
 18,75 
 18,81 
 18,85 
 18,88

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232756&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232756&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232756&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 time5 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
115.13NANA0.998451NA
215.25NANA1.00104NA
315.33NANA1.00181NA
415.36NANA1.00147NA
515.4NANA1.00142NA
615.4NANA0.999969NA
715.4115.447715.44920.9999070.997558
815.4715.489615.50040.9993020.998735
915.5415.540415.54920.9994380.999973
1015.5515.587915.59670.9994380.997569
1115.5915.623815.64290.9987770.997838
1215.6515.671915.68790.9989780.998604
1315.7515.710615.7350.9984511.00251
1415.8615.797315.78081.001041.00397
1515.8915.852715.82421.001811.00235
1615.9415.891315.86791.001471.00307
1715.9315.932615.911.001420.999838
1815.9515.948715.94920.9999691.00008
1915.9915.983515.9850.9999071.00041
2015.9916.003816.0150.9993020.999137
2116.0616.036416.04540.9994381.00147
2216.0816.073516.08250.9994381.00041
2316.0716.106116.12580.9987770.997758
2416.1116.155516.17210.9989780.997181
2516.1516.194516.21960.9984510.997255
2616.1816.288216.27121.001040.993355
2716.316.352816.32331.001810.99677
2816.4216.402916.37871.001471.00104
2916.4916.467516.44421.001421.00137
3016.516.512416.51290.9999690.999249
3116.5816.578516.580.9999071.00009
3216.6416.640516.65210.9993020.999973
3316.6616.717316.72670.9994380.996575
3416.8116.783916.79330.9994381.00156
3516.9116.83616.85670.9987771.00439
3616.9216.906916.92420.9989781.00078
3716.9516.966616.99290.9984510.999022
3817.1117.077417.05961.001041.00191
3917.1617.156317.12541.001811.00021
4017.1617.212417.18711.001470.996956
4117.2717.267417.24291.001421.00015
4217.3417.299917.30040.9999691.00232
4317.3917.357117.35880.9999071.00189
4417.4317.399117.41120.9993021.00178
4517.4517.449317.45920.9994381.00004
4617.517.495617.50540.9994381.00025
4717.5617.526517.54790.9987771.00191
4817.6517.566617.58460.9989781.00475
4917.6217.590617.61790.9984511.00167
5017.717.66817.64961.001041.00181
5117.7217.71417.68211.001811.00034
5217.7117.741117.7151.001470.998248
5317.7417.769817.74461.001420.998325
5417.7517.769917.77040.9999690.998882
5517.7817.795817.79750.9999070.99911
5617.817.816717.82920.9993020.999062
5717.8617.853317.86330.9994381.00038
5817.8817.890817.90080.9994380.999398
5917.8917.919317.94120.9987770.998365
6017.9417.963717.98210.9989780.998681
6117.9817.99518.02290.9984510.999166
6218.118.08318.06421.001041.00094
6318.1418.137718.1051.001811.00013
6418.1918.171718.1451.001471.00101
6518.2318.210418.18461.001421.00108
6618.2418.222818.22330.9999691.00095
6718.2718.259518.26120.9999071.00057
6818.318.282618.29540.9993021.00095
6918.3418.31818.32830.9994381.0012
7018.3618.351818.36210.9994381.00045
7118.3618.371718.39420.9987770.999365
7218.418.406618.42540.9989780.999643
7318.4318.429718.45830.9984511.00001
7418.4718.513518.49421.001040.997652
7518.5618.563118.52961.001810.999836
7618.5818.592818.56541.001470.999314
7718.6118.63118.60461.001420.998874
7818.6118.644418.6450.9999690.998154
7918.69NANA0.999907NA
8018.74NANA0.999302NA
8118.75NANA0.999438NA
8218.81NANA0.999438NA
8318.85NANA0.998777NA
8418.88NANA0.998978NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 15.13 & NA & NA & 0.998451 & NA \tabularnewline
2 & 15.25 & NA & NA & 1.00104 & NA \tabularnewline
3 & 15.33 & NA & NA & 1.00181 & NA \tabularnewline
4 & 15.36 & NA & NA & 1.00147 & NA \tabularnewline
5 & 15.4 & NA & NA & 1.00142 & NA \tabularnewline
6 & 15.4 & NA & NA & 0.999969 & NA \tabularnewline
7 & 15.41 & 15.4477 & 15.4492 & 0.999907 & 0.997558 \tabularnewline
8 & 15.47 & 15.4896 & 15.5004 & 0.999302 & 0.998735 \tabularnewline
9 & 15.54 & 15.5404 & 15.5492 & 0.999438 & 0.999973 \tabularnewline
10 & 15.55 & 15.5879 & 15.5967 & 0.999438 & 0.997569 \tabularnewline
11 & 15.59 & 15.6238 & 15.6429 & 0.998777 & 0.997838 \tabularnewline
12 & 15.65 & 15.6719 & 15.6879 & 0.998978 & 0.998604 \tabularnewline
13 & 15.75 & 15.7106 & 15.735 & 0.998451 & 1.00251 \tabularnewline
14 & 15.86 & 15.7973 & 15.7808 & 1.00104 & 1.00397 \tabularnewline
15 & 15.89 & 15.8527 & 15.8242 & 1.00181 & 1.00235 \tabularnewline
16 & 15.94 & 15.8913 & 15.8679 & 1.00147 & 1.00307 \tabularnewline
17 & 15.93 & 15.9326 & 15.91 & 1.00142 & 0.999838 \tabularnewline
18 & 15.95 & 15.9487 & 15.9492 & 0.999969 & 1.00008 \tabularnewline
19 & 15.99 & 15.9835 & 15.985 & 0.999907 & 1.00041 \tabularnewline
20 & 15.99 & 16.0038 & 16.015 & 0.999302 & 0.999137 \tabularnewline
21 & 16.06 & 16.0364 & 16.0454 & 0.999438 & 1.00147 \tabularnewline
22 & 16.08 & 16.0735 & 16.0825 & 0.999438 & 1.00041 \tabularnewline
23 & 16.07 & 16.1061 & 16.1258 & 0.998777 & 0.997758 \tabularnewline
24 & 16.11 & 16.1555 & 16.1721 & 0.998978 & 0.997181 \tabularnewline
25 & 16.15 & 16.1945 & 16.2196 & 0.998451 & 0.997255 \tabularnewline
26 & 16.18 & 16.2882 & 16.2712 & 1.00104 & 0.993355 \tabularnewline
27 & 16.3 & 16.3528 & 16.3233 & 1.00181 & 0.99677 \tabularnewline
28 & 16.42 & 16.4029 & 16.3787 & 1.00147 & 1.00104 \tabularnewline
29 & 16.49 & 16.4675 & 16.4442 & 1.00142 & 1.00137 \tabularnewline
30 & 16.5 & 16.5124 & 16.5129 & 0.999969 & 0.999249 \tabularnewline
31 & 16.58 & 16.5785 & 16.58 & 0.999907 & 1.00009 \tabularnewline
32 & 16.64 & 16.6405 & 16.6521 & 0.999302 & 0.999973 \tabularnewline
33 & 16.66 & 16.7173 & 16.7267 & 0.999438 & 0.996575 \tabularnewline
34 & 16.81 & 16.7839 & 16.7933 & 0.999438 & 1.00156 \tabularnewline
35 & 16.91 & 16.836 & 16.8567 & 0.998777 & 1.00439 \tabularnewline
36 & 16.92 & 16.9069 & 16.9242 & 0.998978 & 1.00078 \tabularnewline
37 & 16.95 & 16.9666 & 16.9929 & 0.998451 & 0.999022 \tabularnewline
38 & 17.11 & 17.0774 & 17.0596 & 1.00104 & 1.00191 \tabularnewline
39 & 17.16 & 17.1563 & 17.1254 & 1.00181 & 1.00021 \tabularnewline
40 & 17.16 & 17.2124 & 17.1871 & 1.00147 & 0.996956 \tabularnewline
41 & 17.27 & 17.2674 & 17.2429 & 1.00142 & 1.00015 \tabularnewline
42 & 17.34 & 17.2999 & 17.3004 & 0.999969 & 1.00232 \tabularnewline
43 & 17.39 & 17.3571 & 17.3588 & 0.999907 & 1.00189 \tabularnewline
44 & 17.43 & 17.3991 & 17.4112 & 0.999302 & 1.00178 \tabularnewline
45 & 17.45 & 17.4493 & 17.4592 & 0.999438 & 1.00004 \tabularnewline
46 & 17.5 & 17.4956 & 17.5054 & 0.999438 & 1.00025 \tabularnewline
47 & 17.56 & 17.5265 & 17.5479 & 0.998777 & 1.00191 \tabularnewline
48 & 17.65 & 17.5666 & 17.5846 & 0.998978 & 1.00475 \tabularnewline
49 & 17.62 & 17.5906 & 17.6179 & 0.998451 & 1.00167 \tabularnewline
50 & 17.7 & 17.668 & 17.6496 & 1.00104 & 1.00181 \tabularnewline
51 & 17.72 & 17.714 & 17.6821 & 1.00181 & 1.00034 \tabularnewline
52 & 17.71 & 17.7411 & 17.715 & 1.00147 & 0.998248 \tabularnewline
53 & 17.74 & 17.7698 & 17.7446 & 1.00142 & 0.998325 \tabularnewline
54 & 17.75 & 17.7699 & 17.7704 & 0.999969 & 0.998882 \tabularnewline
55 & 17.78 & 17.7958 & 17.7975 & 0.999907 & 0.99911 \tabularnewline
56 & 17.8 & 17.8167 & 17.8292 & 0.999302 & 0.999062 \tabularnewline
57 & 17.86 & 17.8533 & 17.8633 & 0.999438 & 1.00038 \tabularnewline
58 & 17.88 & 17.8908 & 17.9008 & 0.999438 & 0.999398 \tabularnewline
59 & 17.89 & 17.9193 & 17.9412 & 0.998777 & 0.998365 \tabularnewline
60 & 17.94 & 17.9637 & 17.9821 & 0.998978 & 0.998681 \tabularnewline
61 & 17.98 & 17.995 & 18.0229 & 0.998451 & 0.999166 \tabularnewline
62 & 18.1 & 18.083 & 18.0642 & 1.00104 & 1.00094 \tabularnewline
63 & 18.14 & 18.1377 & 18.105 & 1.00181 & 1.00013 \tabularnewline
64 & 18.19 & 18.1717 & 18.145 & 1.00147 & 1.00101 \tabularnewline
65 & 18.23 & 18.2104 & 18.1846 & 1.00142 & 1.00108 \tabularnewline
66 & 18.24 & 18.2228 & 18.2233 & 0.999969 & 1.00095 \tabularnewline
67 & 18.27 & 18.2595 & 18.2612 & 0.999907 & 1.00057 \tabularnewline
68 & 18.3 & 18.2826 & 18.2954 & 0.999302 & 1.00095 \tabularnewline
69 & 18.34 & 18.318 & 18.3283 & 0.999438 & 1.0012 \tabularnewline
70 & 18.36 & 18.3518 & 18.3621 & 0.999438 & 1.00045 \tabularnewline
71 & 18.36 & 18.3717 & 18.3942 & 0.998777 & 0.999365 \tabularnewline
72 & 18.4 & 18.4066 & 18.4254 & 0.998978 & 0.999643 \tabularnewline
73 & 18.43 & 18.4297 & 18.4583 & 0.998451 & 1.00001 \tabularnewline
74 & 18.47 & 18.5135 & 18.4942 & 1.00104 & 0.997652 \tabularnewline
75 & 18.56 & 18.5631 & 18.5296 & 1.00181 & 0.999836 \tabularnewline
76 & 18.58 & 18.5928 & 18.5654 & 1.00147 & 0.999314 \tabularnewline
77 & 18.61 & 18.631 & 18.6046 & 1.00142 & 0.998874 \tabularnewline
78 & 18.61 & 18.6444 & 18.645 & 0.999969 & 0.998154 \tabularnewline
79 & 18.69 & NA & NA & 0.999907 & NA \tabularnewline
80 & 18.74 & NA & NA & 0.999302 & NA \tabularnewline
81 & 18.75 & NA & NA & 0.999438 & NA \tabularnewline
82 & 18.81 & NA & NA & 0.999438 & NA \tabularnewline
83 & 18.85 & NA & NA & 0.998777 & NA \tabularnewline
84 & 18.88 & NA & NA & 0.998978 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232756&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]15.13[/C][C]NA[/C][C]NA[/C][C]0.998451[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]15.25[/C][C]NA[/C][C]NA[/C][C]1.00104[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]15.33[/C][C]NA[/C][C]NA[/C][C]1.00181[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]15.36[/C][C]NA[/C][C]NA[/C][C]1.00147[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]15.4[/C][C]NA[/C][C]NA[/C][C]1.00142[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]15.4[/C][C]NA[/C][C]NA[/C][C]0.999969[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]15.41[/C][C]15.4477[/C][C]15.4492[/C][C]0.999907[/C][C]0.997558[/C][/ROW]
[ROW][C]8[/C][C]15.47[/C][C]15.4896[/C][C]15.5004[/C][C]0.999302[/C][C]0.998735[/C][/ROW]
[ROW][C]9[/C][C]15.54[/C][C]15.5404[/C][C]15.5492[/C][C]0.999438[/C][C]0.999973[/C][/ROW]
[ROW][C]10[/C][C]15.55[/C][C]15.5879[/C][C]15.5967[/C][C]0.999438[/C][C]0.997569[/C][/ROW]
[ROW][C]11[/C][C]15.59[/C][C]15.6238[/C][C]15.6429[/C][C]0.998777[/C][C]0.997838[/C][/ROW]
[ROW][C]12[/C][C]15.65[/C][C]15.6719[/C][C]15.6879[/C][C]0.998978[/C][C]0.998604[/C][/ROW]
[ROW][C]13[/C][C]15.75[/C][C]15.7106[/C][C]15.735[/C][C]0.998451[/C][C]1.00251[/C][/ROW]
[ROW][C]14[/C][C]15.86[/C][C]15.7973[/C][C]15.7808[/C][C]1.00104[/C][C]1.00397[/C][/ROW]
[ROW][C]15[/C][C]15.89[/C][C]15.8527[/C][C]15.8242[/C][C]1.00181[/C][C]1.00235[/C][/ROW]
[ROW][C]16[/C][C]15.94[/C][C]15.8913[/C][C]15.8679[/C][C]1.00147[/C][C]1.00307[/C][/ROW]
[ROW][C]17[/C][C]15.93[/C][C]15.9326[/C][C]15.91[/C][C]1.00142[/C][C]0.999838[/C][/ROW]
[ROW][C]18[/C][C]15.95[/C][C]15.9487[/C][C]15.9492[/C][C]0.999969[/C][C]1.00008[/C][/ROW]
[ROW][C]19[/C][C]15.99[/C][C]15.9835[/C][C]15.985[/C][C]0.999907[/C][C]1.00041[/C][/ROW]
[ROW][C]20[/C][C]15.99[/C][C]16.0038[/C][C]16.015[/C][C]0.999302[/C][C]0.999137[/C][/ROW]
[ROW][C]21[/C][C]16.06[/C][C]16.0364[/C][C]16.0454[/C][C]0.999438[/C][C]1.00147[/C][/ROW]
[ROW][C]22[/C][C]16.08[/C][C]16.0735[/C][C]16.0825[/C][C]0.999438[/C][C]1.00041[/C][/ROW]
[ROW][C]23[/C][C]16.07[/C][C]16.1061[/C][C]16.1258[/C][C]0.998777[/C][C]0.997758[/C][/ROW]
[ROW][C]24[/C][C]16.11[/C][C]16.1555[/C][C]16.1721[/C][C]0.998978[/C][C]0.997181[/C][/ROW]
[ROW][C]25[/C][C]16.15[/C][C]16.1945[/C][C]16.2196[/C][C]0.998451[/C][C]0.997255[/C][/ROW]
[ROW][C]26[/C][C]16.18[/C][C]16.2882[/C][C]16.2712[/C][C]1.00104[/C][C]0.993355[/C][/ROW]
[ROW][C]27[/C][C]16.3[/C][C]16.3528[/C][C]16.3233[/C][C]1.00181[/C][C]0.99677[/C][/ROW]
[ROW][C]28[/C][C]16.42[/C][C]16.4029[/C][C]16.3787[/C][C]1.00147[/C][C]1.00104[/C][/ROW]
[ROW][C]29[/C][C]16.49[/C][C]16.4675[/C][C]16.4442[/C][C]1.00142[/C][C]1.00137[/C][/ROW]
[ROW][C]30[/C][C]16.5[/C][C]16.5124[/C][C]16.5129[/C][C]0.999969[/C][C]0.999249[/C][/ROW]
[ROW][C]31[/C][C]16.58[/C][C]16.5785[/C][C]16.58[/C][C]0.999907[/C][C]1.00009[/C][/ROW]
[ROW][C]32[/C][C]16.64[/C][C]16.6405[/C][C]16.6521[/C][C]0.999302[/C][C]0.999973[/C][/ROW]
[ROW][C]33[/C][C]16.66[/C][C]16.7173[/C][C]16.7267[/C][C]0.999438[/C][C]0.996575[/C][/ROW]
[ROW][C]34[/C][C]16.81[/C][C]16.7839[/C][C]16.7933[/C][C]0.999438[/C][C]1.00156[/C][/ROW]
[ROW][C]35[/C][C]16.91[/C][C]16.836[/C][C]16.8567[/C][C]0.998777[/C][C]1.00439[/C][/ROW]
[ROW][C]36[/C][C]16.92[/C][C]16.9069[/C][C]16.9242[/C][C]0.998978[/C][C]1.00078[/C][/ROW]
[ROW][C]37[/C][C]16.95[/C][C]16.9666[/C][C]16.9929[/C][C]0.998451[/C][C]0.999022[/C][/ROW]
[ROW][C]38[/C][C]17.11[/C][C]17.0774[/C][C]17.0596[/C][C]1.00104[/C][C]1.00191[/C][/ROW]
[ROW][C]39[/C][C]17.16[/C][C]17.1563[/C][C]17.1254[/C][C]1.00181[/C][C]1.00021[/C][/ROW]
[ROW][C]40[/C][C]17.16[/C][C]17.2124[/C][C]17.1871[/C][C]1.00147[/C][C]0.996956[/C][/ROW]
[ROW][C]41[/C][C]17.27[/C][C]17.2674[/C][C]17.2429[/C][C]1.00142[/C][C]1.00015[/C][/ROW]
[ROW][C]42[/C][C]17.34[/C][C]17.2999[/C][C]17.3004[/C][C]0.999969[/C][C]1.00232[/C][/ROW]
[ROW][C]43[/C][C]17.39[/C][C]17.3571[/C][C]17.3588[/C][C]0.999907[/C][C]1.00189[/C][/ROW]
[ROW][C]44[/C][C]17.43[/C][C]17.3991[/C][C]17.4112[/C][C]0.999302[/C][C]1.00178[/C][/ROW]
[ROW][C]45[/C][C]17.45[/C][C]17.4493[/C][C]17.4592[/C][C]0.999438[/C][C]1.00004[/C][/ROW]
[ROW][C]46[/C][C]17.5[/C][C]17.4956[/C][C]17.5054[/C][C]0.999438[/C][C]1.00025[/C][/ROW]
[ROW][C]47[/C][C]17.56[/C][C]17.5265[/C][C]17.5479[/C][C]0.998777[/C][C]1.00191[/C][/ROW]
[ROW][C]48[/C][C]17.65[/C][C]17.5666[/C][C]17.5846[/C][C]0.998978[/C][C]1.00475[/C][/ROW]
[ROW][C]49[/C][C]17.62[/C][C]17.5906[/C][C]17.6179[/C][C]0.998451[/C][C]1.00167[/C][/ROW]
[ROW][C]50[/C][C]17.7[/C][C]17.668[/C][C]17.6496[/C][C]1.00104[/C][C]1.00181[/C][/ROW]
[ROW][C]51[/C][C]17.72[/C][C]17.714[/C][C]17.6821[/C][C]1.00181[/C][C]1.00034[/C][/ROW]
[ROW][C]52[/C][C]17.71[/C][C]17.7411[/C][C]17.715[/C][C]1.00147[/C][C]0.998248[/C][/ROW]
[ROW][C]53[/C][C]17.74[/C][C]17.7698[/C][C]17.7446[/C][C]1.00142[/C][C]0.998325[/C][/ROW]
[ROW][C]54[/C][C]17.75[/C][C]17.7699[/C][C]17.7704[/C][C]0.999969[/C][C]0.998882[/C][/ROW]
[ROW][C]55[/C][C]17.78[/C][C]17.7958[/C][C]17.7975[/C][C]0.999907[/C][C]0.99911[/C][/ROW]
[ROW][C]56[/C][C]17.8[/C][C]17.8167[/C][C]17.8292[/C][C]0.999302[/C][C]0.999062[/C][/ROW]
[ROW][C]57[/C][C]17.86[/C][C]17.8533[/C][C]17.8633[/C][C]0.999438[/C][C]1.00038[/C][/ROW]
[ROW][C]58[/C][C]17.88[/C][C]17.8908[/C][C]17.9008[/C][C]0.999438[/C][C]0.999398[/C][/ROW]
[ROW][C]59[/C][C]17.89[/C][C]17.9193[/C][C]17.9412[/C][C]0.998777[/C][C]0.998365[/C][/ROW]
[ROW][C]60[/C][C]17.94[/C][C]17.9637[/C][C]17.9821[/C][C]0.998978[/C][C]0.998681[/C][/ROW]
[ROW][C]61[/C][C]17.98[/C][C]17.995[/C][C]18.0229[/C][C]0.998451[/C][C]0.999166[/C][/ROW]
[ROW][C]62[/C][C]18.1[/C][C]18.083[/C][C]18.0642[/C][C]1.00104[/C][C]1.00094[/C][/ROW]
[ROW][C]63[/C][C]18.14[/C][C]18.1377[/C][C]18.105[/C][C]1.00181[/C][C]1.00013[/C][/ROW]
[ROW][C]64[/C][C]18.19[/C][C]18.1717[/C][C]18.145[/C][C]1.00147[/C][C]1.00101[/C][/ROW]
[ROW][C]65[/C][C]18.23[/C][C]18.2104[/C][C]18.1846[/C][C]1.00142[/C][C]1.00108[/C][/ROW]
[ROW][C]66[/C][C]18.24[/C][C]18.2228[/C][C]18.2233[/C][C]0.999969[/C][C]1.00095[/C][/ROW]
[ROW][C]67[/C][C]18.27[/C][C]18.2595[/C][C]18.2612[/C][C]0.999907[/C][C]1.00057[/C][/ROW]
[ROW][C]68[/C][C]18.3[/C][C]18.2826[/C][C]18.2954[/C][C]0.999302[/C][C]1.00095[/C][/ROW]
[ROW][C]69[/C][C]18.34[/C][C]18.318[/C][C]18.3283[/C][C]0.999438[/C][C]1.0012[/C][/ROW]
[ROW][C]70[/C][C]18.36[/C][C]18.3518[/C][C]18.3621[/C][C]0.999438[/C][C]1.00045[/C][/ROW]
[ROW][C]71[/C][C]18.36[/C][C]18.3717[/C][C]18.3942[/C][C]0.998777[/C][C]0.999365[/C][/ROW]
[ROW][C]72[/C][C]18.4[/C][C]18.4066[/C][C]18.4254[/C][C]0.998978[/C][C]0.999643[/C][/ROW]
[ROW][C]73[/C][C]18.43[/C][C]18.4297[/C][C]18.4583[/C][C]0.998451[/C][C]1.00001[/C][/ROW]
[ROW][C]74[/C][C]18.47[/C][C]18.5135[/C][C]18.4942[/C][C]1.00104[/C][C]0.997652[/C][/ROW]
[ROW][C]75[/C][C]18.56[/C][C]18.5631[/C][C]18.5296[/C][C]1.00181[/C][C]0.999836[/C][/ROW]
[ROW][C]76[/C][C]18.58[/C][C]18.5928[/C][C]18.5654[/C][C]1.00147[/C][C]0.999314[/C][/ROW]
[ROW][C]77[/C][C]18.61[/C][C]18.631[/C][C]18.6046[/C][C]1.00142[/C][C]0.998874[/C][/ROW]
[ROW][C]78[/C][C]18.61[/C][C]18.6444[/C][C]18.645[/C][C]0.999969[/C][C]0.998154[/C][/ROW]
[ROW][C]79[/C][C]18.69[/C][C]NA[/C][C]NA[/C][C]0.999907[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]18.74[/C][C]NA[/C][C]NA[/C][C]0.999302[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]18.75[/C][C]NA[/C][C]NA[/C][C]0.999438[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]18.81[/C][C]NA[/C][C]NA[/C][C]0.999438[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]18.85[/C][C]NA[/C][C]NA[/C][C]0.998777[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]18.88[/C][C]NA[/C][C]NA[/C][C]0.998978[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232756&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232756&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
115.13NANA0.998451NA
215.25NANA1.00104NA
315.33NANA1.00181NA
415.36NANA1.00147NA
515.4NANA1.00142NA
615.4NANA0.999969NA
715.4115.447715.44920.9999070.997558
815.4715.489615.50040.9993020.998735
915.5415.540415.54920.9994380.999973
1015.5515.587915.59670.9994380.997569
1115.5915.623815.64290.9987770.997838
1215.6515.671915.68790.9989780.998604
1315.7515.710615.7350.9984511.00251
1415.8615.797315.78081.001041.00397
1515.8915.852715.82421.001811.00235
1615.9415.891315.86791.001471.00307
1715.9315.932615.911.001420.999838
1815.9515.948715.94920.9999691.00008
1915.9915.983515.9850.9999071.00041
2015.9916.003816.0150.9993020.999137
2116.0616.036416.04540.9994381.00147
2216.0816.073516.08250.9994381.00041
2316.0716.106116.12580.9987770.997758
2416.1116.155516.17210.9989780.997181
2516.1516.194516.21960.9984510.997255
2616.1816.288216.27121.001040.993355
2716.316.352816.32331.001810.99677
2816.4216.402916.37871.001471.00104
2916.4916.467516.44421.001421.00137
3016.516.512416.51290.9999690.999249
3116.5816.578516.580.9999071.00009
3216.6416.640516.65210.9993020.999973
3316.6616.717316.72670.9994380.996575
3416.8116.783916.79330.9994381.00156
3516.9116.83616.85670.9987771.00439
3616.9216.906916.92420.9989781.00078
3716.9516.966616.99290.9984510.999022
3817.1117.077417.05961.001041.00191
3917.1617.156317.12541.001811.00021
4017.1617.212417.18711.001470.996956
4117.2717.267417.24291.001421.00015
4217.3417.299917.30040.9999691.00232
4317.3917.357117.35880.9999071.00189
4417.4317.399117.41120.9993021.00178
4517.4517.449317.45920.9994381.00004
4617.517.495617.50540.9994381.00025
4717.5617.526517.54790.9987771.00191
4817.6517.566617.58460.9989781.00475
4917.6217.590617.61790.9984511.00167
5017.717.66817.64961.001041.00181
5117.7217.71417.68211.001811.00034
5217.7117.741117.7151.001470.998248
5317.7417.769817.74461.001420.998325
5417.7517.769917.77040.9999690.998882
5517.7817.795817.79750.9999070.99911
5617.817.816717.82920.9993020.999062
5717.8617.853317.86330.9994381.00038
5817.8817.890817.90080.9994380.999398
5917.8917.919317.94120.9987770.998365
6017.9417.963717.98210.9989780.998681
6117.9817.99518.02290.9984510.999166
6218.118.08318.06421.001041.00094
6318.1418.137718.1051.001811.00013
6418.1918.171718.1451.001471.00101
6518.2318.210418.18461.001421.00108
6618.2418.222818.22330.9999691.00095
6718.2718.259518.26120.9999071.00057
6818.318.282618.29540.9993021.00095
6918.3418.31818.32830.9994381.0012
7018.3618.351818.36210.9994381.00045
7118.3618.371718.39420.9987770.999365
7218.418.406618.42540.9989780.999643
7318.4318.429718.45830.9984511.00001
7418.4718.513518.49421.001040.997652
7518.5618.563118.52961.001810.999836
7618.5818.592818.56541.001470.999314
7718.6118.63118.60461.001420.998874
7818.6118.644418.6450.9999690.998154
7918.69NANA0.999907NA
8018.74NANA0.999302NA
8118.75NANA0.999438NA
8218.81NANA0.999438NA
8318.85NANA0.998777NA
8418.88NANA0.998978NA


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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')