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R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 05 Dec 2013 13:29:36 -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/2013/Dec/05/t1386268221qj3hmfbolevw4bk.htm/, Retrieved Thu, 28 Mar 2024 21:56:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231205, Retrieved Thu, 28 Mar 2024 21:56:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact54
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-05 18:29:36] [6e7c8e41ae9c2cf944b21192a5249437] [Current]
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Dataseries X:
26,73
26,85
27,01
27,09
27,11
27,16
27,13
27,19
27,49
27,63
27,72
27,77
27,81
27,92
28,07
28,14
28,17
28,20
28,21
28,20
28,19
28,24
28,25
28,26
28,33
28,67
28,81
28,99
29,16
29,25
29,25
29,38
29,48
29,65
29,69
29,73
29,81
30,05
30,29
30,37
30,50
30,67
30,76
30,84
30,86
31,09
31,20
31,19
31,18
31,31
31,39
31,39
31,37
31,36
31,37
31,35
31,34
31,47
31,48
31,54
31,55
31,55
31,57
31,66
31,74
31,78
31,80
31,68
31,70
31,70
31,75
31,73
31,82
31,90
31,82
31,51
31,42
30,97
30,99
30,92
30,95
30,82
30,72
30,73




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231205&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231205&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231205&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
126.73NANA-0.0541262NA
226.85NANA0.0431655NA
327.01NANA0.0849016NA
427.09NANA0.0570544NA
527.11NANA0.0640683NA
627.16NANA0.00101273NA
727.1327.274127.285-0.0108623-0.144138
827.1927.313327.3746-0.0612789-0.123304
927.4927.403627.4633-0.05975120.0864178
1027.6327.547427.5512-0.003848380.0825984
1127.7227.626427.6392-0.01280670.09364
1227.7727.679127.7267-0.04752890.0908623
1327.8127.760927.815-0.05412620.0491262
1427.9227.945227.90210.0431655-0.0252488
1528.0728.058227.97330.08490160.011765
1628.1428.08528.02790.05705440.0550289
1728.1728.139528.07540.06406830.030515
1828.228.118928.11790.001012730.0810706
1928.2128.149128.16-0.01086230.0608623
2028.228.151628.2129-0.06127890.0483623
2128.1928.215228.275-0.0597512-0.0252488
2228.2428.337428.3412-0.00384838-0.0974016
2328.2528.405128.4179-0.0128067-0.15511
2428.2628.455428.5029-0.0475289-0.195388
2528.3328.535928.59-0.0541262-0.205874
2628.6728.725728.68250.0431655-0.0556655
2728.8128.870328.78540.0849016-0.0603183
2828.9928.95528.89790.05705440.0350289
2929.1629.080729.01670.06406830.079265
3029.2529.138929.13790.001012730.111071
3129.2529.2529.2608-0.01086232.89352e-05
3229.3829.318729.38-0.06127890.0612789
3329.4829.439429.4992-0.05975120.0405845
3429.6529.614529.6183-0.003848380.035515
3529.6929.718929.7317-0.0128067-0.02886
3629.7329.799129.8467-0.0475289-0.0691377
3729.8129.914629.9687-0.0541262-0.104624
3830.0530.135730.09250.0431655-0.0856655
3930.2930.295730.21080.0849016-0.00573495
4030.3730.385430.32830.0570544-0.0153877
4130.530.515330.45120.0640683-0.0153183
4230.6730.57630.5750.001012730.0939873
4330.7630.682130.6929-0.01086230.0779456
4430.8430.741230.8025-0.06127890.0987789
4530.8630.841130.9008-0.05975120.0189178
4631.0930.985330.9892-0.003848380.104682
4731.231.055131.0679-0.01280670.14489
4831.1931.085431.1329-0.04752890.104612
4931.1831.13331.1871-0.05412620.0470428
5031.3131.276931.23370.04316550.0330845
5131.3931.359931.2750.08490160.0300984
5231.3931.367931.31080.05705440.0221123
5331.3731.402431.33830.0640683-0.0324016
5431.3631.365631.36460.00101273-0.00559606
5531.3731.383731.3946-0.0108623-0.0137211
5631.3531.358731.42-0.0612789-0.00872106
5731.3431.377731.4375-0.0597512-0.0377488
5831.4731.452431.4562-0.003848380.0175984
5931.4831.470131.4829-0.01280670.00989005
6031.5431.468331.5158-0.04752890.0716956
6131.5531.497131.5513-0.05412620.0528762
6231.5531.626131.58290.0431655-0.0760822
6331.5731.696631.61170.0849016-0.126568
6431.6631.693331.63620.0570544-0.0333044
6531.7431.721231.65710.06406830.0188484
6631.7831.677331.67620.001012730.102737
6731.831.684631.6954-0.01086230.115446
6831.6831.6631.7212-0.06127890.0200289
6931.731.686531.7462-0.05975120.0135012
7031.731.746631.7504-0.00384838-0.0465683
7131.7531.71831.7308-0.01280670.0319734
7231.7331.636231.6837-0.04752890.0937789
7331.8231.562131.6162-0.05412620.257876
7431.931.59431.55080.04316550.306001
7531.8231.572831.48790.08490160.247182
7631.5131.477131.420.05705440.0329456
7731.4231.404531.34040.06406830.015515
7830.9731.256831.25580.00101273-0.286846
7930.99NANA-0.0108623NA
8030.92NANA-0.0612789NA
8130.95NANA-0.0597512NA
8230.82NANA-0.00384838NA
8330.72NANA-0.0128067NA
8430.73NANA-0.0475289NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 26.73 & NA & NA & -0.0541262 & NA \tabularnewline
2 & 26.85 & NA & NA & 0.0431655 & NA \tabularnewline
3 & 27.01 & NA & NA & 0.0849016 & NA \tabularnewline
4 & 27.09 & NA & NA & 0.0570544 & NA \tabularnewline
5 & 27.11 & NA & NA & 0.0640683 & NA \tabularnewline
6 & 27.16 & NA & NA & 0.00101273 & NA \tabularnewline
7 & 27.13 & 27.2741 & 27.285 & -0.0108623 & -0.144138 \tabularnewline
8 & 27.19 & 27.3133 & 27.3746 & -0.0612789 & -0.123304 \tabularnewline
9 & 27.49 & 27.4036 & 27.4633 & -0.0597512 & 0.0864178 \tabularnewline
10 & 27.63 & 27.5474 & 27.5512 & -0.00384838 & 0.0825984 \tabularnewline
11 & 27.72 & 27.6264 & 27.6392 & -0.0128067 & 0.09364 \tabularnewline
12 & 27.77 & 27.6791 & 27.7267 & -0.0475289 & 0.0908623 \tabularnewline
13 & 27.81 & 27.7609 & 27.815 & -0.0541262 & 0.0491262 \tabularnewline
14 & 27.92 & 27.9452 & 27.9021 & 0.0431655 & -0.0252488 \tabularnewline
15 & 28.07 & 28.0582 & 27.9733 & 0.0849016 & 0.011765 \tabularnewline
16 & 28.14 & 28.085 & 28.0279 & 0.0570544 & 0.0550289 \tabularnewline
17 & 28.17 & 28.1395 & 28.0754 & 0.0640683 & 0.030515 \tabularnewline
18 & 28.2 & 28.1189 & 28.1179 & 0.00101273 & 0.0810706 \tabularnewline
19 & 28.21 & 28.1491 & 28.16 & -0.0108623 & 0.0608623 \tabularnewline
20 & 28.2 & 28.1516 & 28.2129 & -0.0612789 & 0.0483623 \tabularnewline
21 & 28.19 & 28.2152 & 28.275 & -0.0597512 & -0.0252488 \tabularnewline
22 & 28.24 & 28.3374 & 28.3412 & -0.00384838 & -0.0974016 \tabularnewline
23 & 28.25 & 28.4051 & 28.4179 & -0.0128067 & -0.15511 \tabularnewline
24 & 28.26 & 28.4554 & 28.5029 & -0.0475289 & -0.195388 \tabularnewline
25 & 28.33 & 28.5359 & 28.59 & -0.0541262 & -0.205874 \tabularnewline
26 & 28.67 & 28.7257 & 28.6825 & 0.0431655 & -0.0556655 \tabularnewline
27 & 28.81 & 28.8703 & 28.7854 & 0.0849016 & -0.0603183 \tabularnewline
28 & 28.99 & 28.955 & 28.8979 & 0.0570544 & 0.0350289 \tabularnewline
29 & 29.16 & 29.0807 & 29.0167 & 0.0640683 & 0.079265 \tabularnewline
30 & 29.25 & 29.1389 & 29.1379 & 0.00101273 & 0.111071 \tabularnewline
31 & 29.25 & 29.25 & 29.2608 & -0.0108623 & 2.89352e-05 \tabularnewline
32 & 29.38 & 29.3187 & 29.38 & -0.0612789 & 0.0612789 \tabularnewline
33 & 29.48 & 29.4394 & 29.4992 & -0.0597512 & 0.0405845 \tabularnewline
34 & 29.65 & 29.6145 & 29.6183 & -0.00384838 & 0.035515 \tabularnewline
35 & 29.69 & 29.7189 & 29.7317 & -0.0128067 & -0.02886 \tabularnewline
36 & 29.73 & 29.7991 & 29.8467 & -0.0475289 & -0.0691377 \tabularnewline
37 & 29.81 & 29.9146 & 29.9687 & -0.0541262 & -0.104624 \tabularnewline
38 & 30.05 & 30.1357 & 30.0925 & 0.0431655 & -0.0856655 \tabularnewline
39 & 30.29 & 30.2957 & 30.2108 & 0.0849016 & -0.00573495 \tabularnewline
40 & 30.37 & 30.3854 & 30.3283 & 0.0570544 & -0.0153877 \tabularnewline
41 & 30.5 & 30.5153 & 30.4512 & 0.0640683 & -0.0153183 \tabularnewline
42 & 30.67 & 30.576 & 30.575 & 0.00101273 & 0.0939873 \tabularnewline
43 & 30.76 & 30.6821 & 30.6929 & -0.0108623 & 0.0779456 \tabularnewline
44 & 30.84 & 30.7412 & 30.8025 & -0.0612789 & 0.0987789 \tabularnewline
45 & 30.86 & 30.8411 & 30.9008 & -0.0597512 & 0.0189178 \tabularnewline
46 & 31.09 & 30.9853 & 30.9892 & -0.00384838 & 0.104682 \tabularnewline
47 & 31.2 & 31.0551 & 31.0679 & -0.0128067 & 0.14489 \tabularnewline
48 & 31.19 & 31.0854 & 31.1329 & -0.0475289 & 0.104612 \tabularnewline
49 & 31.18 & 31.133 & 31.1871 & -0.0541262 & 0.0470428 \tabularnewline
50 & 31.31 & 31.2769 & 31.2337 & 0.0431655 & 0.0330845 \tabularnewline
51 & 31.39 & 31.3599 & 31.275 & 0.0849016 & 0.0300984 \tabularnewline
52 & 31.39 & 31.3679 & 31.3108 & 0.0570544 & 0.0221123 \tabularnewline
53 & 31.37 & 31.4024 & 31.3383 & 0.0640683 & -0.0324016 \tabularnewline
54 & 31.36 & 31.3656 & 31.3646 & 0.00101273 & -0.00559606 \tabularnewline
55 & 31.37 & 31.3837 & 31.3946 & -0.0108623 & -0.0137211 \tabularnewline
56 & 31.35 & 31.3587 & 31.42 & -0.0612789 & -0.00872106 \tabularnewline
57 & 31.34 & 31.3777 & 31.4375 & -0.0597512 & -0.0377488 \tabularnewline
58 & 31.47 & 31.4524 & 31.4562 & -0.00384838 & 0.0175984 \tabularnewline
59 & 31.48 & 31.4701 & 31.4829 & -0.0128067 & 0.00989005 \tabularnewline
60 & 31.54 & 31.4683 & 31.5158 & -0.0475289 & 0.0716956 \tabularnewline
61 & 31.55 & 31.4971 & 31.5513 & -0.0541262 & 0.0528762 \tabularnewline
62 & 31.55 & 31.6261 & 31.5829 & 0.0431655 & -0.0760822 \tabularnewline
63 & 31.57 & 31.6966 & 31.6117 & 0.0849016 & -0.126568 \tabularnewline
64 & 31.66 & 31.6933 & 31.6362 & 0.0570544 & -0.0333044 \tabularnewline
65 & 31.74 & 31.7212 & 31.6571 & 0.0640683 & 0.0188484 \tabularnewline
66 & 31.78 & 31.6773 & 31.6762 & 0.00101273 & 0.102737 \tabularnewline
67 & 31.8 & 31.6846 & 31.6954 & -0.0108623 & 0.115446 \tabularnewline
68 & 31.68 & 31.66 & 31.7212 & -0.0612789 & 0.0200289 \tabularnewline
69 & 31.7 & 31.6865 & 31.7462 & -0.0597512 & 0.0135012 \tabularnewline
70 & 31.7 & 31.7466 & 31.7504 & -0.00384838 & -0.0465683 \tabularnewline
71 & 31.75 & 31.718 & 31.7308 & -0.0128067 & 0.0319734 \tabularnewline
72 & 31.73 & 31.6362 & 31.6837 & -0.0475289 & 0.0937789 \tabularnewline
73 & 31.82 & 31.5621 & 31.6162 & -0.0541262 & 0.257876 \tabularnewline
74 & 31.9 & 31.594 & 31.5508 & 0.0431655 & 0.306001 \tabularnewline
75 & 31.82 & 31.5728 & 31.4879 & 0.0849016 & 0.247182 \tabularnewline
76 & 31.51 & 31.4771 & 31.42 & 0.0570544 & 0.0329456 \tabularnewline
77 & 31.42 & 31.4045 & 31.3404 & 0.0640683 & 0.015515 \tabularnewline
78 & 30.97 & 31.2568 & 31.2558 & 0.00101273 & -0.286846 \tabularnewline
79 & 30.99 & NA & NA & -0.0108623 & NA \tabularnewline
80 & 30.92 & NA & NA & -0.0612789 & NA \tabularnewline
81 & 30.95 & NA & NA & -0.0597512 & NA \tabularnewline
82 & 30.82 & NA & NA & -0.00384838 & NA \tabularnewline
83 & 30.72 & NA & NA & -0.0128067 & NA \tabularnewline
84 & 30.73 & NA & NA & -0.0475289 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231205&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]26.73[/C][C]NA[/C][C]NA[/C][C]-0.0541262[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]26.85[/C][C]NA[/C][C]NA[/C][C]0.0431655[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]27.01[/C][C]NA[/C][C]NA[/C][C]0.0849016[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]27.09[/C][C]NA[/C][C]NA[/C][C]0.0570544[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]27.11[/C][C]NA[/C][C]NA[/C][C]0.0640683[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]27.16[/C][C]NA[/C][C]NA[/C][C]0.00101273[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]27.13[/C][C]27.2741[/C][C]27.285[/C][C]-0.0108623[/C][C]-0.144138[/C][/ROW]
[ROW][C]8[/C][C]27.19[/C][C]27.3133[/C][C]27.3746[/C][C]-0.0612789[/C][C]-0.123304[/C][/ROW]
[ROW][C]9[/C][C]27.49[/C][C]27.4036[/C][C]27.4633[/C][C]-0.0597512[/C][C]0.0864178[/C][/ROW]
[ROW][C]10[/C][C]27.63[/C][C]27.5474[/C][C]27.5512[/C][C]-0.00384838[/C][C]0.0825984[/C][/ROW]
[ROW][C]11[/C][C]27.72[/C][C]27.6264[/C][C]27.6392[/C][C]-0.0128067[/C][C]0.09364[/C][/ROW]
[ROW][C]12[/C][C]27.77[/C][C]27.6791[/C][C]27.7267[/C][C]-0.0475289[/C][C]0.0908623[/C][/ROW]
[ROW][C]13[/C][C]27.81[/C][C]27.7609[/C][C]27.815[/C][C]-0.0541262[/C][C]0.0491262[/C][/ROW]
[ROW][C]14[/C][C]27.92[/C][C]27.9452[/C][C]27.9021[/C][C]0.0431655[/C][C]-0.0252488[/C][/ROW]
[ROW][C]15[/C][C]28.07[/C][C]28.0582[/C][C]27.9733[/C][C]0.0849016[/C][C]0.011765[/C][/ROW]
[ROW][C]16[/C][C]28.14[/C][C]28.085[/C][C]28.0279[/C][C]0.0570544[/C][C]0.0550289[/C][/ROW]
[ROW][C]17[/C][C]28.17[/C][C]28.1395[/C][C]28.0754[/C][C]0.0640683[/C][C]0.030515[/C][/ROW]
[ROW][C]18[/C][C]28.2[/C][C]28.1189[/C][C]28.1179[/C][C]0.00101273[/C][C]0.0810706[/C][/ROW]
[ROW][C]19[/C][C]28.21[/C][C]28.1491[/C][C]28.16[/C][C]-0.0108623[/C][C]0.0608623[/C][/ROW]
[ROW][C]20[/C][C]28.2[/C][C]28.1516[/C][C]28.2129[/C][C]-0.0612789[/C][C]0.0483623[/C][/ROW]
[ROW][C]21[/C][C]28.19[/C][C]28.2152[/C][C]28.275[/C][C]-0.0597512[/C][C]-0.0252488[/C][/ROW]
[ROW][C]22[/C][C]28.24[/C][C]28.3374[/C][C]28.3412[/C][C]-0.00384838[/C][C]-0.0974016[/C][/ROW]
[ROW][C]23[/C][C]28.25[/C][C]28.4051[/C][C]28.4179[/C][C]-0.0128067[/C][C]-0.15511[/C][/ROW]
[ROW][C]24[/C][C]28.26[/C][C]28.4554[/C][C]28.5029[/C][C]-0.0475289[/C][C]-0.195388[/C][/ROW]
[ROW][C]25[/C][C]28.33[/C][C]28.5359[/C][C]28.59[/C][C]-0.0541262[/C][C]-0.205874[/C][/ROW]
[ROW][C]26[/C][C]28.67[/C][C]28.7257[/C][C]28.6825[/C][C]0.0431655[/C][C]-0.0556655[/C][/ROW]
[ROW][C]27[/C][C]28.81[/C][C]28.8703[/C][C]28.7854[/C][C]0.0849016[/C][C]-0.0603183[/C][/ROW]
[ROW][C]28[/C][C]28.99[/C][C]28.955[/C][C]28.8979[/C][C]0.0570544[/C][C]0.0350289[/C][/ROW]
[ROW][C]29[/C][C]29.16[/C][C]29.0807[/C][C]29.0167[/C][C]0.0640683[/C][C]0.079265[/C][/ROW]
[ROW][C]30[/C][C]29.25[/C][C]29.1389[/C][C]29.1379[/C][C]0.00101273[/C][C]0.111071[/C][/ROW]
[ROW][C]31[/C][C]29.25[/C][C]29.25[/C][C]29.2608[/C][C]-0.0108623[/C][C]2.89352e-05[/C][/ROW]
[ROW][C]32[/C][C]29.38[/C][C]29.3187[/C][C]29.38[/C][C]-0.0612789[/C][C]0.0612789[/C][/ROW]
[ROW][C]33[/C][C]29.48[/C][C]29.4394[/C][C]29.4992[/C][C]-0.0597512[/C][C]0.0405845[/C][/ROW]
[ROW][C]34[/C][C]29.65[/C][C]29.6145[/C][C]29.6183[/C][C]-0.00384838[/C][C]0.035515[/C][/ROW]
[ROW][C]35[/C][C]29.69[/C][C]29.7189[/C][C]29.7317[/C][C]-0.0128067[/C][C]-0.02886[/C][/ROW]
[ROW][C]36[/C][C]29.73[/C][C]29.7991[/C][C]29.8467[/C][C]-0.0475289[/C][C]-0.0691377[/C][/ROW]
[ROW][C]37[/C][C]29.81[/C][C]29.9146[/C][C]29.9687[/C][C]-0.0541262[/C][C]-0.104624[/C][/ROW]
[ROW][C]38[/C][C]30.05[/C][C]30.1357[/C][C]30.0925[/C][C]0.0431655[/C][C]-0.0856655[/C][/ROW]
[ROW][C]39[/C][C]30.29[/C][C]30.2957[/C][C]30.2108[/C][C]0.0849016[/C][C]-0.00573495[/C][/ROW]
[ROW][C]40[/C][C]30.37[/C][C]30.3854[/C][C]30.3283[/C][C]0.0570544[/C][C]-0.0153877[/C][/ROW]
[ROW][C]41[/C][C]30.5[/C][C]30.5153[/C][C]30.4512[/C][C]0.0640683[/C][C]-0.0153183[/C][/ROW]
[ROW][C]42[/C][C]30.67[/C][C]30.576[/C][C]30.575[/C][C]0.00101273[/C][C]0.0939873[/C][/ROW]
[ROW][C]43[/C][C]30.76[/C][C]30.6821[/C][C]30.6929[/C][C]-0.0108623[/C][C]0.0779456[/C][/ROW]
[ROW][C]44[/C][C]30.84[/C][C]30.7412[/C][C]30.8025[/C][C]-0.0612789[/C][C]0.0987789[/C][/ROW]
[ROW][C]45[/C][C]30.86[/C][C]30.8411[/C][C]30.9008[/C][C]-0.0597512[/C][C]0.0189178[/C][/ROW]
[ROW][C]46[/C][C]31.09[/C][C]30.9853[/C][C]30.9892[/C][C]-0.00384838[/C][C]0.104682[/C][/ROW]
[ROW][C]47[/C][C]31.2[/C][C]31.0551[/C][C]31.0679[/C][C]-0.0128067[/C][C]0.14489[/C][/ROW]
[ROW][C]48[/C][C]31.19[/C][C]31.0854[/C][C]31.1329[/C][C]-0.0475289[/C][C]0.104612[/C][/ROW]
[ROW][C]49[/C][C]31.18[/C][C]31.133[/C][C]31.1871[/C][C]-0.0541262[/C][C]0.0470428[/C][/ROW]
[ROW][C]50[/C][C]31.31[/C][C]31.2769[/C][C]31.2337[/C][C]0.0431655[/C][C]0.0330845[/C][/ROW]
[ROW][C]51[/C][C]31.39[/C][C]31.3599[/C][C]31.275[/C][C]0.0849016[/C][C]0.0300984[/C][/ROW]
[ROW][C]52[/C][C]31.39[/C][C]31.3679[/C][C]31.3108[/C][C]0.0570544[/C][C]0.0221123[/C][/ROW]
[ROW][C]53[/C][C]31.37[/C][C]31.4024[/C][C]31.3383[/C][C]0.0640683[/C][C]-0.0324016[/C][/ROW]
[ROW][C]54[/C][C]31.36[/C][C]31.3656[/C][C]31.3646[/C][C]0.00101273[/C][C]-0.00559606[/C][/ROW]
[ROW][C]55[/C][C]31.37[/C][C]31.3837[/C][C]31.3946[/C][C]-0.0108623[/C][C]-0.0137211[/C][/ROW]
[ROW][C]56[/C][C]31.35[/C][C]31.3587[/C][C]31.42[/C][C]-0.0612789[/C][C]-0.00872106[/C][/ROW]
[ROW][C]57[/C][C]31.34[/C][C]31.3777[/C][C]31.4375[/C][C]-0.0597512[/C][C]-0.0377488[/C][/ROW]
[ROW][C]58[/C][C]31.47[/C][C]31.4524[/C][C]31.4562[/C][C]-0.00384838[/C][C]0.0175984[/C][/ROW]
[ROW][C]59[/C][C]31.48[/C][C]31.4701[/C][C]31.4829[/C][C]-0.0128067[/C][C]0.00989005[/C][/ROW]
[ROW][C]60[/C][C]31.54[/C][C]31.4683[/C][C]31.5158[/C][C]-0.0475289[/C][C]0.0716956[/C][/ROW]
[ROW][C]61[/C][C]31.55[/C][C]31.4971[/C][C]31.5513[/C][C]-0.0541262[/C][C]0.0528762[/C][/ROW]
[ROW][C]62[/C][C]31.55[/C][C]31.6261[/C][C]31.5829[/C][C]0.0431655[/C][C]-0.0760822[/C][/ROW]
[ROW][C]63[/C][C]31.57[/C][C]31.6966[/C][C]31.6117[/C][C]0.0849016[/C][C]-0.126568[/C][/ROW]
[ROW][C]64[/C][C]31.66[/C][C]31.6933[/C][C]31.6362[/C][C]0.0570544[/C][C]-0.0333044[/C][/ROW]
[ROW][C]65[/C][C]31.74[/C][C]31.7212[/C][C]31.6571[/C][C]0.0640683[/C][C]0.0188484[/C][/ROW]
[ROW][C]66[/C][C]31.78[/C][C]31.6773[/C][C]31.6762[/C][C]0.00101273[/C][C]0.102737[/C][/ROW]
[ROW][C]67[/C][C]31.8[/C][C]31.6846[/C][C]31.6954[/C][C]-0.0108623[/C][C]0.115446[/C][/ROW]
[ROW][C]68[/C][C]31.68[/C][C]31.66[/C][C]31.7212[/C][C]-0.0612789[/C][C]0.0200289[/C][/ROW]
[ROW][C]69[/C][C]31.7[/C][C]31.6865[/C][C]31.7462[/C][C]-0.0597512[/C][C]0.0135012[/C][/ROW]
[ROW][C]70[/C][C]31.7[/C][C]31.7466[/C][C]31.7504[/C][C]-0.00384838[/C][C]-0.0465683[/C][/ROW]
[ROW][C]71[/C][C]31.75[/C][C]31.718[/C][C]31.7308[/C][C]-0.0128067[/C][C]0.0319734[/C][/ROW]
[ROW][C]72[/C][C]31.73[/C][C]31.6362[/C][C]31.6837[/C][C]-0.0475289[/C][C]0.0937789[/C][/ROW]
[ROW][C]73[/C][C]31.82[/C][C]31.5621[/C][C]31.6162[/C][C]-0.0541262[/C][C]0.257876[/C][/ROW]
[ROW][C]74[/C][C]31.9[/C][C]31.594[/C][C]31.5508[/C][C]0.0431655[/C][C]0.306001[/C][/ROW]
[ROW][C]75[/C][C]31.82[/C][C]31.5728[/C][C]31.4879[/C][C]0.0849016[/C][C]0.247182[/C][/ROW]
[ROW][C]76[/C][C]31.51[/C][C]31.4771[/C][C]31.42[/C][C]0.0570544[/C][C]0.0329456[/C][/ROW]
[ROW][C]77[/C][C]31.42[/C][C]31.4045[/C][C]31.3404[/C][C]0.0640683[/C][C]0.015515[/C][/ROW]
[ROW][C]78[/C][C]30.97[/C][C]31.2568[/C][C]31.2558[/C][C]0.00101273[/C][C]-0.286846[/C][/ROW]
[ROW][C]79[/C][C]30.99[/C][C]NA[/C][C]NA[/C][C]-0.0108623[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]30.92[/C][C]NA[/C][C]NA[/C][C]-0.0612789[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]30.95[/C][C]NA[/C][C]NA[/C][C]-0.0597512[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]30.82[/C][C]NA[/C][C]NA[/C][C]-0.00384838[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]30.72[/C][C]NA[/C][C]NA[/C][C]-0.0128067[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]30.73[/C][C]NA[/C][C]NA[/C][C]-0.0475289[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231205&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231205&T=1

As an alternative you can also use a QR Code:  

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

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
126.73NANA-0.0541262NA
226.85NANA0.0431655NA
327.01NANA0.0849016NA
427.09NANA0.0570544NA
527.11NANA0.0640683NA
627.16NANA0.00101273NA
727.1327.274127.285-0.0108623-0.144138
827.1927.313327.3746-0.0612789-0.123304
927.4927.403627.4633-0.05975120.0864178
1027.6327.547427.5512-0.003848380.0825984
1127.7227.626427.6392-0.01280670.09364
1227.7727.679127.7267-0.04752890.0908623
1327.8127.760927.815-0.05412620.0491262
1427.9227.945227.90210.0431655-0.0252488
1528.0728.058227.97330.08490160.011765
1628.1428.08528.02790.05705440.0550289
1728.1728.139528.07540.06406830.030515
1828.228.118928.11790.001012730.0810706
1928.2128.149128.16-0.01086230.0608623
2028.228.151628.2129-0.06127890.0483623
2128.1928.215228.275-0.0597512-0.0252488
2228.2428.337428.3412-0.00384838-0.0974016
2328.2528.405128.4179-0.0128067-0.15511
2428.2628.455428.5029-0.0475289-0.195388
2528.3328.535928.59-0.0541262-0.205874
2628.6728.725728.68250.0431655-0.0556655
2728.8128.870328.78540.0849016-0.0603183
2828.9928.95528.89790.05705440.0350289
2929.1629.080729.01670.06406830.079265
3029.2529.138929.13790.001012730.111071
3129.2529.2529.2608-0.01086232.89352e-05
3229.3829.318729.38-0.06127890.0612789
3329.4829.439429.4992-0.05975120.0405845
3429.6529.614529.6183-0.003848380.035515
3529.6929.718929.7317-0.0128067-0.02886
3629.7329.799129.8467-0.0475289-0.0691377
3729.8129.914629.9687-0.0541262-0.104624
3830.0530.135730.09250.0431655-0.0856655
3930.2930.295730.21080.0849016-0.00573495
4030.3730.385430.32830.0570544-0.0153877
4130.530.515330.45120.0640683-0.0153183
4230.6730.57630.5750.001012730.0939873
4330.7630.682130.6929-0.01086230.0779456
4430.8430.741230.8025-0.06127890.0987789
4530.8630.841130.9008-0.05975120.0189178
4631.0930.985330.9892-0.003848380.104682
4731.231.055131.0679-0.01280670.14489
4831.1931.085431.1329-0.04752890.104612
4931.1831.13331.1871-0.05412620.0470428
5031.3131.276931.23370.04316550.0330845
5131.3931.359931.2750.08490160.0300984
5231.3931.367931.31080.05705440.0221123
5331.3731.402431.33830.0640683-0.0324016
5431.3631.365631.36460.00101273-0.00559606
5531.3731.383731.3946-0.0108623-0.0137211
5631.3531.358731.42-0.0612789-0.00872106
5731.3431.377731.4375-0.0597512-0.0377488
5831.4731.452431.4562-0.003848380.0175984
5931.4831.470131.4829-0.01280670.00989005
6031.5431.468331.5158-0.04752890.0716956
6131.5531.497131.5513-0.05412620.0528762
6231.5531.626131.58290.0431655-0.0760822
6331.5731.696631.61170.0849016-0.126568
6431.6631.693331.63620.0570544-0.0333044
6531.7431.721231.65710.06406830.0188484
6631.7831.677331.67620.001012730.102737
6731.831.684631.6954-0.01086230.115446
6831.6831.6631.7212-0.06127890.0200289
6931.731.686531.7462-0.05975120.0135012
7031.731.746631.7504-0.00384838-0.0465683
7131.7531.71831.7308-0.01280670.0319734
7231.7331.636231.6837-0.04752890.0937789
7331.8231.562131.6162-0.05412620.257876
7431.931.59431.55080.04316550.306001
7531.8231.572831.48790.08490160.247182
7631.5131.477131.420.05705440.0329456
7731.4231.404531.34040.06406830.015515
7830.9731.256831.25580.00101273-0.286846
7930.99NANA-0.0108623NA
8030.92NANA-0.0612789NA
8130.95NANA-0.0597512NA
8230.82NANA-0.00384838NA
8330.72NANA-0.0128067NA
8430.73NANA-0.0475289NA



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; 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')