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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 26 Dec 2013 14:07:42 -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/26/t1388085076syz2shuhtvqrdec.htm/, Retrieved Sat, 27 Apr 2024 08:00:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232626, Retrieved Sat, 27 Apr 2024 08:00:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-26 19:07:42] [76c30f62b7052b57088120e90a652e05] [Current]
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Dataseries X:
27,65
28,19
28,98
28,99
29,02
29
29,04
29,19
29,23
29,26
29,02
28,47
28,53
28,48
28,68
28,89
29,2
29,21
29,15
29,22
29,34
29,13
28,84
28,76
28,75
28,89
28,82
29,12
29,21
29,3
29,32
29,52
29,64
29,54
29,54
29,34
29,34
29,54
29,94
30,17
30,23
30,34
30,34
30,36
30,3
30,28
29,89
29,58
29,68
29,73
30,07
30,32
30,55
30,62
30,67
30,79
30,8
30,5
30,07
29,41
29,42
29,99
30,14
30,41
30,78
30,88
30,92
30,93
31,62
31,48
31,3
31,11
31,16
31,22
31,66
32,11
32,27
32,36
32,42
32,52
32,41
31,87
31,04
30,58




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232626&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232626&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
127.65NANA0.983751NA
228.19NANA0.987607NA
328.98NANA0.994131NA
428.99NANA1.00223NA
529.02NANA1.00792NA
629NANA1.00953NA
729.0429.067728.87331.006730.999047
829.1929.166228.92211.008441.00082
929.2329.27328.92171.012150.998531
1029.2629.098728.9051.00671.00554
1129.0228.813228.90830.9967091.00718
1228.4728.464828.92460.9841031.00018
1328.5328.467728.93790.9837511.00219
1428.4828.58528.94380.9876070.996325
1528.6828.779728.94960.9941310.996537
1628.8929.013328.94881.002230.99575
1729.229.164928.93581.007921.0012
1829.2129.216428.94041.009530.999782
1929.1529.156628.96171.006730.999773
2029.2229.232628.98791.008440.99957
2129.3429.363229.01081.012150.999209
2229.1329.220729.02621.00670.996896
2328.8428.940729.03620.9967090.996521
2428.7628.578829.04040.9841031.00634
2528.7528.579229.05120.9837511.00598
2628.8928.710529.07080.9876071.00625
2728.8228.925129.09580.9941310.996368
2829.1229.190429.12541.002230.99759
2929.2129.402629.17171.007920.993448
3029.329.503729.2251.009530.993097
3129.3229.470829.27381.006730.994883
3229.5229.572929.32541.008440.998211
3329.6429.756329.39921.012150.996092
3429.5429.687229.48961.00670.995043
3529.5429.478529.57580.9967091.00209
3629.3429.190129.66170.9841031.00513
3729.3429.264129.74750.9837511.00259
3829.5429.455429.8250.9876071.00287
3929.9429.712129.88750.9941311.00767
4030.1730.012629.94581.002231.00524
4130.2330.228729.99121.007921.00004
4230.3430.30230.01581.009531.00125
4330.3430.242230.041.006731.00323
4430.3630.315830.06211.008441.00146
4530.330.440830.07541.012150.995376
4630.2830.288730.08711.00670.999714
4729.8930.007630.10670.9967090.996082
4829.5829.652730.13170.9841030.997549
4929.6829.66730.15710.9837511.00044
5029.7329.814630.18880.9876070.997162
5130.0730.050130.22750.9941311.00066
5230.3230.32530.25751.002230.999836
5330.5530.513930.27421.007921.00118
5430.6230.563230.27461.009531.00186
5530.6730.460330.25671.006731.00688
5630.7930.51230.25671.008441.00911
5730.830.638130.27041.012151.00528
5830.530.479930.27711.00671.00066
5930.0730.190730.29040.9967090.996001
6029.4129.82930.31080.9841030.985954
6129.4229.839230.33210.9837510.985951
6229.9929.972230.34830.9876071.00059
6330.1430.2130.38830.9941310.997683
6430.4130.531330.46331.002230.996028
6530.7830.797430.55541.007920.999437
6630.8830.9730.67751.009530.997094
6730.9231.028330.82081.006730.99651
6830.9331.205730.94461.008440.991164
6931.6231.436531.05921.012151.00584
7031.4831.402331.19331.00671.00247
7131.331.223131.32620.9967091.00246
7231.1130.9531.450.9841031.00517
7331.1631.061131.57420.9837511.00318
7431.2231.3131.70290.9876070.997125
7531.6631.615431.80210.9941311.00141
7632.1131.922331.85121.002231.00588
7732.2732.108931.85671.007921.00502
7832.3632.127231.82371.009531.00725
7932.42NANA1.00673NA
8032.52NANA1.00844NA
8132.41NANA1.01215NA
8231.87NANA1.0067NA
8331.04NANA0.996709NA
8430.58NANA0.984103NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 27.65 & NA & NA & 0.983751 & NA \tabularnewline
2 & 28.19 & NA & NA & 0.987607 & NA \tabularnewline
3 & 28.98 & NA & NA & 0.994131 & NA \tabularnewline
4 & 28.99 & NA & NA & 1.00223 & NA \tabularnewline
5 & 29.02 & NA & NA & 1.00792 & NA \tabularnewline
6 & 29 & NA & NA & 1.00953 & NA \tabularnewline
7 & 29.04 & 29.0677 & 28.8733 & 1.00673 & 0.999047 \tabularnewline
8 & 29.19 & 29.1662 & 28.9221 & 1.00844 & 1.00082 \tabularnewline
9 & 29.23 & 29.273 & 28.9217 & 1.01215 & 0.998531 \tabularnewline
10 & 29.26 & 29.0987 & 28.905 & 1.0067 & 1.00554 \tabularnewline
11 & 29.02 & 28.8132 & 28.9083 & 0.996709 & 1.00718 \tabularnewline
12 & 28.47 & 28.4648 & 28.9246 & 0.984103 & 1.00018 \tabularnewline
13 & 28.53 & 28.4677 & 28.9379 & 0.983751 & 1.00219 \tabularnewline
14 & 28.48 & 28.585 & 28.9438 & 0.987607 & 0.996325 \tabularnewline
15 & 28.68 & 28.7797 & 28.9496 & 0.994131 & 0.996537 \tabularnewline
16 & 28.89 & 29.0133 & 28.9488 & 1.00223 & 0.99575 \tabularnewline
17 & 29.2 & 29.1649 & 28.9358 & 1.00792 & 1.0012 \tabularnewline
18 & 29.21 & 29.2164 & 28.9404 & 1.00953 & 0.999782 \tabularnewline
19 & 29.15 & 29.1566 & 28.9617 & 1.00673 & 0.999773 \tabularnewline
20 & 29.22 & 29.2326 & 28.9879 & 1.00844 & 0.99957 \tabularnewline
21 & 29.34 & 29.3632 & 29.0108 & 1.01215 & 0.999209 \tabularnewline
22 & 29.13 & 29.2207 & 29.0262 & 1.0067 & 0.996896 \tabularnewline
23 & 28.84 & 28.9407 & 29.0362 & 0.996709 & 0.996521 \tabularnewline
24 & 28.76 & 28.5788 & 29.0404 & 0.984103 & 1.00634 \tabularnewline
25 & 28.75 & 28.5792 & 29.0512 & 0.983751 & 1.00598 \tabularnewline
26 & 28.89 & 28.7105 & 29.0708 & 0.987607 & 1.00625 \tabularnewline
27 & 28.82 & 28.9251 & 29.0958 & 0.994131 & 0.996368 \tabularnewline
28 & 29.12 & 29.1904 & 29.1254 & 1.00223 & 0.99759 \tabularnewline
29 & 29.21 & 29.4026 & 29.1717 & 1.00792 & 0.993448 \tabularnewline
30 & 29.3 & 29.5037 & 29.225 & 1.00953 & 0.993097 \tabularnewline
31 & 29.32 & 29.4708 & 29.2738 & 1.00673 & 0.994883 \tabularnewline
32 & 29.52 & 29.5729 & 29.3254 & 1.00844 & 0.998211 \tabularnewline
33 & 29.64 & 29.7563 & 29.3992 & 1.01215 & 0.996092 \tabularnewline
34 & 29.54 & 29.6872 & 29.4896 & 1.0067 & 0.995043 \tabularnewline
35 & 29.54 & 29.4785 & 29.5758 & 0.996709 & 1.00209 \tabularnewline
36 & 29.34 & 29.1901 & 29.6617 & 0.984103 & 1.00513 \tabularnewline
37 & 29.34 & 29.2641 & 29.7475 & 0.983751 & 1.00259 \tabularnewline
38 & 29.54 & 29.4554 & 29.825 & 0.987607 & 1.00287 \tabularnewline
39 & 29.94 & 29.7121 & 29.8875 & 0.994131 & 1.00767 \tabularnewline
40 & 30.17 & 30.0126 & 29.9458 & 1.00223 & 1.00524 \tabularnewline
41 & 30.23 & 30.2287 & 29.9912 & 1.00792 & 1.00004 \tabularnewline
42 & 30.34 & 30.302 & 30.0158 & 1.00953 & 1.00125 \tabularnewline
43 & 30.34 & 30.2422 & 30.04 & 1.00673 & 1.00323 \tabularnewline
44 & 30.36 & 30.3158 & 30.0621 & 1.00844 & 1.00146 \tabularnewline
45 & 30.3 & 30.4408 & 30.0754 & 1.01215 & 0.995376 \tabularnewline
46 & 30.28 & 30.2887 & 30.0871 & 1.0067 & 0.999714 \tabularnewline
47 & 29.89 & 30.0076 & 30.1067 & 0.996709 & 0.996082 \tabularnewline
48 & 29.58 & 29.6527 & 30.1317 & 0.984103 & 0.997549 \tabularnewline
49 & 29.68 & 29.667 & 30.1571 & 0.983751 & 1.00044 \tabularnewline
50 & 29.73 & 29.8146 & 30.1888 & 0.987607 & 0.997162 \tabularnewline
51 & 30.07 & 30.0501 & 30.2275 & 0.994131 & 1.00066 \tabularnewline
52 & 30.32 & 30.325 & 30.2575 & 1.00223 & 0.999836 \tabularnewline
53 & 30.55 & 30.5139 & 30.2742 & 1.00792 & 1.00118 \tabularnewline
54 & 30.62 & 30.5632 & 30.2746 & 1.00953 & 1.00186 \tabularnewline
55 & 30.67 & 30.4603 & 30.2567 & 1.00673 & 1.00688 \tabularnewline
56 & 30.79 & 30.512 & 30.2567 & 1.00844 & 1.00911 \tabularnewline
57 & 30.8 & 30.6381 & 30.2704 & 1.01215 & 1.00528 \tabularnewline
58 & 30.5 & 30.4799 & 30.2771 & 1.0067 & 1.00066 \tabularnewline
59 & 30.07 & 30.1907 & 30.2904 & 0.996709 & 0.996001 \tabularnewline
60 & 29.41 & 29.829 & 30.3108 & 0.984103 & 0.985954 \tabularnewline
61 & 29.42 & 29.8392 & 30.3321 & 0.983751 & 0.985951 \tabularnewline
62 & 29.99 & 29.9722 & 30.3483 & 0.987607 & 1.00059 \tabularnewline
63 & 30.14 & 30.21 & 30.3883 & 0.994131 & 0.997683 \tabularnewline
64 & 30.41 & 30.5313 & 30.4633 & 1.00223 & 0.996028 \tabularnewline
65 & 30.78 & 30.7974 & 30.5554 & 1.00792 & 0.999437 \tabularnewline
66 & 30.88 & 30.97 & 30.6775 & 1.00953 & 0.997094 \tabularnewline
67 & 30.92 & 31.0283 & 30.8208 & 1.00673 & 0.99651 \tabularnewline
68 & 30.93 & 31.2057 & 30.9446 & 1.00844 & 0.991164 \tabularnewline
69 & 31.62 & 31.4365 & 31.0592 & 1.01215 & 1.00584 \tabularnewline
70 & 31.48 & 31.4023 & 31.1933 & 1.0067 & 1.00247 \tabularnewline
71 & 31.3 & 31.2231 & 31.3262 & 0.996709 & 1.00246 \tabularnewline
72 & 31.11 & 30.95 & 31.45 & 0.984103 & 1.00517 \tabularnewline
73 & 31.16 & 31.0611 & 31.5742 & 0.983751 & 1.00318 \tabularnewline
74 & 31.22 & 31.31 & 31.7029 & 0.987607 & 0.997125 \tabularnewline
75 & 31.66 & 31.6154 & 31.8021 & 0.994131 & 1.00141 \tabularnewline
76 & 32.11 & 31.9223 & 31.8512 & 1.00223 & 1.00588 \tabularnewline
77 & 32.27 & 32.1089 & 31.8567 & 1.00792 & 1.00502 \tabularnewline
78 & 32.36 & 32.1272 & 31.8237 & 1.00953 & 1.00725 \tabularnewline
79 & 32.42 & NA & NA & 1.00673 & NA \tabularnewline
80 & 32.52 & NA & NA & 1.00844 & NA \tabularnewline
81 & 32.41 & NA & NA & 1.01215 & NA \tabularnewline
82 & 31.87 & NA & NA & 1.0067 & NA \tabularnewline
83 & 31.04 & NA & NA & 0.996709 & NA \tabularnewline
84 & 30.58 & NA & NA & 0.984103 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232626&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]27.65[/C][C]NA[/C][C]NA[/C][C]0.983751[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]28.19[/C][C]NA[/C][C]NA[/C][C]0.987607[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]28.98[/C][C]NA[/C][C]NA[/C][C]0.994131[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]28.99[/C][C]NA[/C][C]NA[/C][C]1.00223[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]29.02[/C][C]NA[/C][C]NA[/C][C]1.00792[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]NA[/C][C]NA[/C][C]1.00953[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]29.04[/C][C]29.0677[/C][C]28.8733[/C][C]1.00673[/C][C]0.999047[/C][/ROW]
[ROW][C]8[/C][C]29.19[/C][C]29.1662[/C][C]28.9221[/C][C]1.00844[/C][C]1.00082[/C][/ROW]
[ROW][C]9[/C][C]29.23[/C][C]29.273[/C][C]28.9217[/C][C]1.01215[/C][C]0.998531[/C][/ROW]
[ROW][C]10[/C][C]29.26[/C][C]29.0987[/C][C]28.905[/C][C]1.0067[/C][C]1.00554[/C][/ROW]
[ROW][C]11[/C][C]29.02[/C][C]28.8132[/C][C]28.9083[/C][C]0.996709[/C][C]1.00718[/C][/ROW]
[ROW][C]12[/C][C]28.47[/C][C]28.4648[/C][C]28.9246[/C][C]0.984103[/C][C]1.00018[/C][/ROW]
[ROW][C]13[/C][C]28.53[/C][C]28.4677[/C][C]28.9379[/C][C]0.983751[/C][C]1.00219[/C][/ROW]
[ROW][C]14[/C][C]28.48[/C][C]28.585[/C][C]28.9438[/C][C]0.987607[/C][C]0.996325[/C][/ROW]
[ROW][C]15[/C][C]28.68[/C][C]28.7797[/C][C]28.9496[/C][C]0.994131[/C][C]0.996537[/C][/ROW]
[ROW][C]16[/C][C]28.89[/C][C]29.0133[/C][C]28.9488[/C][C]1.00223[/C][C]0.99575[/C][/ROW]
[ROW][C]17[/C][C]29.2[/C][C]29.1649[/C][C]28.9358[/C][C]1.00792[/C][C]1.0012[/C][/ROW]
[ROW][C]18[/C][C]29.21[/C][C]29.2164[/C][C]28.9404[/C][C]1.00953[/C][C]0.999782[/C][/ROW]
[ROW][C]19[/C][C]29.15[/C][C]29.1566[/C][C]28.9617[/C][C]1.00673[/C][C]0.999773[/C][/ROW]
[ROW][C]20[/C][C]29.22[/C][C]29.2326[/C][C]28.9879[/C][C]1.00844[/C][C]0.99957[/C][/ROW]
[ROW][C]21[/C][C]29.34[/C][C]29.3632[/C][C]29.0108[/C][C]1.01215[/C][C]0.999209[/C][/ROW]
[ROW][C]22[/C][C]29.13[/C][C]29.2207[/C][C]29.0262[/C][C]1.0067[/C][C]0.996896[/C][/ROW]
[ROW][C]23[/C][C]28.84[/C][C]28.9407[/C][C]29.0362[/C][C]0.996709[/C][C]0.996521[/C][/ROW]
[ROW][C]24[/C][C]28.76[/C][C]28.5788[/C][C]29.0404[/C][C]0.984103[/C][C]1.00634[/C][/ROW]
[ROW][C]25[/C][C]28.75[/C][C]28.5792[/C][C]29.0512[/C][C]0.983751[/C][C]1.00598[/C][/ROW]
[ROW][C]26[/C][C]28.89[/C][C]28.7105[/C][C]29.0708[/C][C]0.987607[/C][C]1.00625[/C][/ROW]
[ROW][C]27[/C][C]28.82[/C][C]28.9251[/C][C]29.0958[/C][C]0.994131[/C][C]0.996368[/C][/ROW]
[ROW][C]28[/C][C]29.12[/C][C]29.1904[/C][C]29.1254[/C][C]1.00223[/C][C]0.99759[/C][/ROW]
[ROW][C]29[/C][C]29.21[/C][C]29.4026[/C][C]29.1717[/C][C]1.00792[/C][C]0.993448[/C][/ROW]
[ROW][C]30[/C][C]29.3[/C][C]29.5037[/C][C]29.225[/C][C]1.00953[/C][C]0.993097[/C][/ROW]
[ROW][C]31[/C][C]29.32[/C][C]29.4708[/C][C]29.2738[/C][C]1.00673[/C][C]0.994883[/C][/ROW]
[ROW][C]32[/C][C]29.52[/C][C]29.5729[/C][C]29.3254[/C][C]1.00844[/C][C]0.998211[/C][/ROW]
[ROW][C]33[/C][C]29.64[/C][C]29.7563[/C][C]29.3992[/C][C]1.01215[/C][C]0.996092[/C][/ROW]
[ROW][C]34[/C][C]29.54[/C][C]29.6872[/C][C]29.4896[/C][C]1.0067[/C][C]0.995043[/C][/ROW]
[ROW][C]35[/C][C]29.54[/C][C]29.4785[/C][C]29.5758[/C][C]0.996709[/C][C]1.00209[/C][/ROW]
[ROW][C]36[/C][C]29.34[/C][C]29.1901[/C][C]29.6617[/C][C]0.984103[/C][C]1.00513[/C][/ROW]
[ROW][C]37[/C][C]29.34[/C][C]29.2641[/C][C]29.7475[/C][C]0.983751[/C][C]1.00259[/C][/ROW]
[ROW][C]38[/C][C]29.54[/C][C]29.4554[/C][C]29.825[/C][C]0.987607[/C][C]1.00287[/C][/ROW]
[ROW][C]39[/C][C]29.94[/C][C]29.7121[/C][C]29.8875[/C][C]0.994131[/C][C]1.00767[/C][/ROW]
[ROW][C]40[/C][C]30.17[/C][C]30.0126[/C][C]29.9458[/C][C]1.00223[/C][C]1.00524[/C][/ROW]
[ROW][C]41[/C][C]30.23[/C][C]30.2287[/C][C]29.9912[/C][C]1.00792[/C][C]1.00004[/C][/ROW]
[ROW][C]42[/C][C]30.34[/C][C]30.302[/C][C]30.0158[/C][C]1.00953[/C][C]1.00125[/C][/ROW]
[ROW][C]43[/C][C]30.34[/C][C]30.2422[/C][C]30.04[/C][C]1.00673[/C][C]1.00323[/C][/ROW]
[ROW][C]44[/C][C]30.36[/C][C]30.3158[/C][C]30.0621[/C][C]1.00844[/C][C]1.00146[/C][/ROW]
[ROW][C]45[/C][C]30.3[/C][C]30.4408[/C][C]30.0754[/C][C]1.01215[/C][C]0.995376[/C][/ROW]
[ROW][C]46[/C][C]30.28[/C][C]30.2887[/C][C]30.0871[/C][C]1.0067[/C][C]0.999714[/C][/ROW]
[ROW][C]47[/C][C]29.89[/C][C]30.0076[/C][C]30.1067[/C][C]0.996709[/C][C]0.996082[/C][/ROW]
[ROW][C]48[/C][C]29.58[/C][C]29.6527[/C][C]30.1317[/C][C]0.984103[/C][C]0.997549[/C][/ROW]
[ROW][C]49[/C][C]29.68[/C][C]29.667[/C][C]30.1571[/C][C]0.983751[/C][C]1.00044[/C][/ROW]
[ROW][C]50[/C][C]29.73[/C][C]29.8146[/C][C]30.1888[/C][C]0.987607[/C][C]0.997162[/C][/ROW]
[ROW][C]51[/C][C]30.07[/C][C]30.0501[/C][C]30.2275[/C][C]0.994131[/C][C]1.00066[/C][/ROW]
[ROW][C]52[/C][C]30.32[/C][C]30.325[/C][C]30.2575[/C][C]1.00223[/C][C]0.999836[/C][/ROW]
[ROW][C]53[/C][C]30.55[/C][C]30.5139[/C][C]30.2742[/C][C]1.00792[/C][C]1.00118[/C][/ROW]
[ROW][C]54[/C][C]30.62[/C][C]30.5632[/C][C]30.2746[/C][C]1.00953[/C][C]1.00186[/C][/ROW]
[ROW][C]55[/C][C]30.67[/C][C]30.4603[/C][C]30.2567[/C][C]1.00673[/C][C]1.00688[/C][/ROW]
[ROW][C]56[/C][C]30.79[/C][C]30.512[/C][C]30.2567[/C][C]1.00844[/C][C]1.00911[/C][/ROW]
[ROW][C]57[/C][C]30.8[/C][C]30.6381[/C][C]30.2704[/C][C]1.01215[/C][C]1.00528[/C][/ROW]
[ROW][C]58[/C][C]30.5[/C][C]30.4799[/C][C]30.2771[/C][C]1.0067[/C][C]1.00066[/C][/ROW]
[ROW][C]59[/C][C]30.07[/C][C]30.1907[/C][C]30.2904[/C][C]0.996709[/C][C]0.996001[/C][/ROW]
[ROW][C]60[/C][C]29.41[/C][C]29.829[/C][C]30.3108[/C][C]0.984103[/C][C]0.985954[/C][/ROW]
[ROW][C]61[/C][C]29.42[/C][C]29.8392[/C][C]30.3321[/C][C]0.983751[/C][C]0.985951[/C][/ROW]
[ROW][C]62[/C][C]29.99[/C][C]29.9722[/C][C]30.3483[/C][C]0.987607[/C][C]1.00059[/C][/ROW]
[ROW][C]63[/C][C]30.14[/C][C]30.21[/C][C]30.3883[/C][C]0.994131[/C][C]0.997683[/C][/ROW]
[ROW][C]64[/C][C]30.41[/C][C]30.5313[/C][C]30.4633[/C][C]1.00223[/C][C]0.996028[/C][/ROW]
[ROW][C]65[/C][C]30.78[/C][C]30.7974[/C][C]30.5554[/C][C]1.00792[/C][C]0.999437[/C][/ROW]
[ROW][C]66[/C][C]30.88[/C][C]30.97[/C][C]30.6775[/C][C]1.00953[/C][C]0.997094[/C][/ROW]
[ROW][C]67[/C][C]30.92[/C][C]31.0283[/C][C]30.8208[/C][C]1.00673[/C][C]0.99651[/C][/ROW]
[ROW][C]68[/C][C]30.93[/C][C]31.2057[/C][C]30.9446[/C][C]1.00844[/C][C]0.991164[/C][/ROW]
[ROW][C]69[/C][C]31.62[/C][C]31.4365[/C][C]31.0592[/C][C]1.01215[/C][C]1.00584[/C][/ROW]
[ROW][C]70[/C][C]31.48[/C][C]31.4023[/C][C]31.1933[/C][C]1.0067[/C][C]1.00247[/C][/ROW]
[ROW][C]71[/C][C]31.3[/C][C]31.2231[/C][C]31.3262[/C][C]0.996709[/C][C]1.00246[/C][/ROW]
[ROW][C]72[/C][C]31.11[/C][C]30.95[/C][C]31.45[/C][C]0.984103[/C][C]1.00517[/C][/ROW]
[ROW][C]73[/C][C]31.16[/C][C]31.0611[/C][C]31.5742[/C][C]0.983751[/C][C]1.00318[/C][/ROW]
[ROW][C]74[/C][C]31.22[/C][C]31.31[/C][C]31.7029[/C][C]0.987607[/C][C]0.997125[/C][/ROW]
[ROW][C]75[/C][C]31.66[/C][C]31.6154[/C][C]31.8021[/C][C]0.994131[/C][C]1.00141[/C][/ROW]
[ROW][C]76[/C][C]32.11[/C][C]31.9223[/C][C]31.8512[/C][C]1.00223[/C][C]1.00588[/C][/ROW]
[ROW][C]77[/C][C]32.27[/C][C]32.1089[/C][C]31.8567[/C][C]1.00792[/C][C]1.00502[/C][/ROW]
[ROW][C]78[/C][C]32.36[/C][C]32.1272[/C][C]31.8237[/C][C]1.00953[/C][C]1.00725[/C][/ROW]
[ROW][C]79[/C][C]32.42[/C][C]NA[/C][C]NA[/C][C]1.00673[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]32.52[/C][C]NA[/C][C]NA[/C][C]1.00844[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]32.41[/C][C]NA[/C][C]NA[/C][C]1.01215[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]31.87[/C][C]NA[/C][C]NA[/C][C]1.0067[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]31.04[/C][C]NA[/C][C]NA[/C][C]0.996709[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]30.58[/C][C]NA[/C][C]NA[/C][C]0.984103[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232626&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
127.65NANA0.983751NA
228.19NANA0.987607NA
328.98NANA0.994131NA
428.99NANA1.00223NA
529.02NANA1.00792NA
629NANA1.00953NA
729.0429.067728.87331.006730.999047
829.1929.166228.92211.008441.00082
929.2329.27328.92171.012150.998531
1029.2629.098728.9051.00671.00554
1129.0228.813228.90830.9967091.00718
1228.4728.464828.92460.9841031.00018
1328.5328.467728.93790.9837511.00219
1428.4828.58528.94380.9876070.996325
1528.6828.779728.94960.9941310.996537
1628.8929.013328.94881.002230.99575
1729.229.164928.93581.007921.0012
1829.2129.216428.94041.009530.999782
1929.1529.156628.96171.006730.999773
2029.2229.232628.98791.008440.99957
2129.3429.363229.01081.012150.999209
2229.1329.220729.02621.00670.996896
2328.8428.940729.03620.9967090.996521
2428.7628.578829.04040.9841031.00634
2528.7528.579229.05120.9837511.00598
2628.8928.710529.07080.9876071.00625
2728.8228.925129.09580.9941310.996368
2829.1229.190429.12541.002230.99759
2929.2129.402629.17171.007920.993448
3029.329.503729.2251.009530.993097
3129.3229.470829.27381.006730.994883
3229.5229.572929.32541.008440.998211
3329.6429.756329.39921.012150.996092
3429.5429.687229.48961.00670.995043
3529.5429.478529.57580.9967091.00209
3629.3429.190129.66170.9841031.00513
3729.3429.264129.74750.9837511.00259
3829.5429.455429.8250.9876071.00287
3929.9429.712129.88750.9941311.00767
4030.1730.012629.94581.002231.00524
4130.2330.228729.99121.007921.00004
4230.3430.30230.01581.009531.00125
4330.3430.242230.041.006731.00323
4430.3630.315830.06211.008441.00146
4530.330.440830.07541.012150.995376
4630.2830.288730.08711.00670.999714
4729.8930.007630.10670.9967090.996082
4829.5829.652730.13170.9841030.997549
4929.6829.66730.15710.9837511.00044
5029.7329.814630.18880.9876070.997162
5130.0730.050130.22750.9941311.00066
5230.3230.32530.25751.002230.999836
5330.5530.513930.27421.007921.00118
5430.6230.563230.27461.009531.00186
5530.6730.460330.25671.006731.00688
5630.7930.51230.25671.008441.00911
5730.830.638130.27041.012151.00528
5830.530.479930.27711.00671.00066
5930.0730.190730.29040.9967090.996001
6029.4129.82930.31080.9841030.985954
6129.4229.839230.33210.9837510.985951
6229.9929.972230.34830.9876071.00059
6330.1430.2130.38830.9941310.997683
6430.4130.531330.46331.002230.996028
6530.7830.797430.55541.007920.999437
6630.8830.9730.67751.009530.997094
6730.9231.028330.82081.006730.99651
6830.9331.205730.94461.008440.991164
6931.6231.436531.05921.012151.00584
7031.4831.402331.19331.00671.00247
7131.331.223131.32620.9967091.00246
7231.1130.9531.450.9841031.00517
7331.1631.061131.57420.9837511.00318
7431.2231.3131.70290.9876070.997125
7531.6631.615431.80210.9941311.00141
7632.1131.922331.85121.002231.00588
7732.2732.108931.85671.007921.00502
7832.3632.127231.82371.009531.00725
7932.42NANA1.00673NA
8032.52NANA1.00844NA
8132.41NANA1.01215NA
8231.87NANA1.0067NA
8331.04NANA0.996709NA
8430.58NANA0.984103NA



Parameters (Session):
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')