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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 17:10:49 -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/12/t1386886270tn8bkqk8t8xvjmo.htm/, Retrieved Sun, 05 Dec 2021 16:53:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232275, Retrieved Sun, 05 Dec 2021 16:53:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact46
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 22:10:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
47,43
47,43
47,51
47,96
47,99
48,05
48,05
48,01
48
48,06
48,23
48,4
48,4
48,5
48,41
48,35
48,53
48,52
48,52
48,49
48,45
48,65
48,74
48,74
48,74
48,79
48,82
48,82
49,2
49,3
49,3
49,34
49,47
49,65
49,7
49,75
49,75
49,7
50,09
50,19
50,53
50,55
50,55
50,55
50,58
50,61
50,94
51,01
51,01
51,04
51,15
51,31
51,31
51,34
51,34
51,34
51,47
51,95
51,97
51,92
51,92
51,91
51,97
52,14
52,33
52,4
52,4
52,41
52,71
53,17
53,33
53,32
53,32
53,3
53,31
53,72
53,87
53,91
53,91
53,96
54,02
54,33
54,48
54,54




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 8 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232275&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232275&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232275&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 time8 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
147.43NANA-0.00780671NA
247.43NANA-0.0731539NA
347.51NANA-0.0712789NA
447.96NANA-0.0266262NA
547.99NANA0.0930961NA
648.05NANA0.0487211NA
748.0547.949347.9671-0.01773730.100654
848.0147.949348.0521-0.1027370.0606539
94848.040448.1342-0.0937789-0.0403877
1048.0648.248948.18790.0609433-0.18886
1148.2348.343448.22670.116777-0.113443
1248.448.342348.26870.07358220.0576678
1348.448.300148.3079-0.007806710.09989
1448.548.274348.3475-0.07315390.225654
1548.4148.31548.3862-0.07127890.0950289
1648.3548.40348.4296-0.0266262-0.0529572
1748.5348.568548.47540.0930961-0.0385127
1848.5248.559648.51080.0487211-0.0395544
1948.5248.521448.5392-0.0177373-0.0014294
2048.4948.462748.5654-0.1027370.0273206
2148.4548.500848.5946-0.0937789-0.0508044
2248.6548.692248.63130.0609433-0.0421933
2348.7448.795548.67880.116777-0.0555266
2448.7448.812748.73920.0735822-0.0727488
2548.7448.796448.8042-0.00780671-0.05636
2648.7948.798948.8721-0.0731539-0.0089294
2748.8248.878748.95-0.0712789-0.0587211
2848.8249.007549.0342-0.0266262-0.187541
2949.249.208949.11580.0930961-0.0089294
3049.349.246649.19790.04872110.0533623
3149.349.264349.2821-0.01773730.0356539
3249.3449.259349.3621-0.1027370.0806539
3349.4749.359149.4529-0.09377890.110862
3449.6549.623949.56290.06094330.02614
3549.749.792249.67540.116777-0.0921933
3649.7549.856549.78290.0735822-0.106499
3749.7549.879349.8871-0.00780671-0.129277
3849.749.916449.9896-0.0731539-0.216429
3950.0950.01550.0863-0.07127890.0750289
4050.1950.145950.1725-0.02662620.0441262
4150.5350.357350.26420.09309610.172737
4250.5550.417150.36830.04872110.132946
4350.5550.455650.4733-0.01773730.0944039
4450.5550.478950.5817-0.1027370.0710706
4550.5850.587950.6817-0.0937789-0.00788773
4650.6150.833450.77250.0609433-0.223443
4750.9450.968450.85170.116777-0.0284433
4851.0150.990750.91710.07358220.0193345
4951.0150.975150.9829-0.007806710.03489
5051.0450.975651.0488-0.07315390.0644039
5151.1551.047551.1188-0.07127890.102529
5251.3151.18551.2117-0.02662620.124959
5351.3151.403551.31040.0930961-0.0935127
5451.3451.4451.39120.0487211-0.0999711
5551.3451.449351.4671-0.0177373-0.109346
5651.3451.438551.5412-0.102737-0.0985127
5751.4751.517951.6117-0.0937789-0.0478877
5851.9551.741451.68040.06094330.20864
5951.9751.874351.75750.1167770.0957234
6051.9251.917751.84420.07358220.00225116
6151.9251.924751.9325-0.00780671-0.00469329
6251.9151.948152.0212-0.0731539-0.0380961
6351.9752.046252.1175-0.0712789-0.0762211
6452.1452.193452.22-0.0266262-0.0533738
6552.3352.420652.32750.0930961-0.0905961
6652.452.491252.44250.0487211-0.0912211
6752.452.541452.5592-0.0177373-0.141429
6852.4152.572752.6754-0.102737-0.162679
6952.7152.695452.7892-0.09377890.0146123
7053.1752.971852.91080.06094330.198223
7153.3353.157653.04080.1167770.17239
7253.3253.241553.16790.07358220.0785012
7353.3253.285953.2937-0.007806710.0340567
7453.353.348153.4212-0.0731539-0.0480961
7553.3153.469153.5404-0.0712789-0.159138
7653.7253.616753.6433-0.02662620.103293
7753.8753.832753.73960.09309610.0373206
7853.9153.887153.83830.04872110.0229456
7953.91NANA-0.0177373NA
8053.96NANA-0.102737NA
8154.02NANA-0.0937789NA
8254.33NANA0.0609433NA
8354.48NANA0.116777NA
8454.54NANA0.0735822NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 47.43 & NA & NA & -0.00780671 & NA \tabularnewline
2 & 47.43 & NA & NA & -0.0731539 & NA \tabularnewline
3 & 47.51 & NA & NA & -0.0712789 & NA \tabularnewline
4 & 47.96 & NA & NA & -0.0266262 & NA \tabularnewline
5 & 47.99 & NA & NA & 0.0930961 & NA \tabularnewline
6 & 48.05 & NA & NA & 0.0487211 & NA \tabularnewline
7 & 48.05 & 47.9493 & 47.9671 & -0.0177373 & 0.100654 \tabularnewline
8 & 48.01 & 47.9493 & 48.0521 & -0.102737 & 0.0606539 \tabularnewline
9 & 48 & 48.0404 & 48.1342 & -0.0937789 & -0.0403877 \tabularnewline
10 & 48.06 & 48.2489 & 48.1879 & 0.0609433 & -0.18886 \tabularnewline
11 & 48.23 & 48.3434 & 48.2267 & 0.116777 & -0.113443 \tabularnewline
12 & 48.4 & 48.3423 & 48.2687 & 0.0735822 & 0.0576678 \tabularnewline
13 & 48.4 & 48.3001 & 48.3079 & -0.00780671 & 0.09989 \tabularnewline
14 & 48.5 & 48.2743 & 48.3475 & -0.0731539 & 0.225654 \tabularnewline
15 & 48.41 & 48.315 & 48.3862 & -0.0712789 & 0.0950289 \tabularnewline
16 & 48.35 & 48.403 & 48.4296 & -0.0266262 & -0.0529572 \tabularnewline
17 & 48.53 & 48.5685 & 48.4754 & 0.0930961 & -0.0385127 \tabularnewline
18 & 48.52 & 48.5596 & 48.5108 & 0.0487211 & -0.0395544 \tabularnewline
19 & 48.52 & 48.5214 & 48.5392 & -0.0177373 & -0.0014294 \tabularnewline
20 & 48.49 & 48.4627 & 48.5654 & -0.102737 & 0.0273206 \tabularnewline
21 & 48.45 & 48.5008 & 48.5946 & -0.0937789 & -0.0508044 \tabularnewline
22 & 48.65 & 48.6922 & 48.6313 & 0.0609433 & -0.0421933 \tabularnewline
23 & 48.74 & 48.7955 & 48.6788 & 0.116777 & -0.0555266 \tabularnewline
24 & 48.74 & 48.8127 & 48.7392 & 0.0735822 & -0.0727488 \tabularnewline
25 & 48.74 & 48.7964 & 48.8042 & -0.00780671 & -0.05636 \tabularnewline
26 & 48.79 & 48.7989 & 48.8721 & -0.0731539 & -0.0089294 \tabularnewline
27 & 48.82 & 48.8787 & 48.95 & -0.0712789 & -0.0587211 \tabularnewline
28 & 48.82 & 49.0075 & 49.0342 & -0.0266262 & -0.187541 \tabularnewline
29 & 49.2 & 49.2089 & 49.1158 & 0.0930961 & -0.0089294 \tabularnewline
30 & 49.3 & 49.2466 & 49.1979 & 0.0487211 & 0.0533623 \tabularnewline
31 & 49.3 & 49.2643 & 49.2821 & -0.0177373 & 0.0356539 \tabularnewline
32 & 49.34 & 49.2593 & 49.3621 & -0.102737 & 0.0806539 \tabularnewline
33 & 49.47 & 49.3591 & 49.4529 & -0.0937789 & 0.110862 \tabularnewline
34 & 49.65 & 49.6239 & 49.5629 & 0.0609433 & 0.02614 \tabularnewline
35 & 49.7 & 49.7922 & 49.6754 & 0.116777 & -0.0921933 \tabularnewline
36 & 49.75 & 49.8565 & 49.7829 & 0.0735822 & -0.106499 \tabularnewline
37 & 49.75 & 49.8793 & 49.8871 & -0.00780671 & -0.129277 \tabularnewline
38 & 49.7 & 49.9164 & 49.9896 & -0.0731539 & -0.216429 \tabularnewline
39 & 50.09 & 50.015 & 50.0863 & -0.0712789 & 0.0750289 \tabularnewline
40 & 50.19 & 50.1459 & 50.1725 & -0.0266262 & 0.0441262 \tabularnewline
41 & 50.53 & 50.3573 & 50.2642 & 0.0930961 & 0.172737 \tabularnewline
42 & 50.55 & 50.4171 & 50.3683 & 0.0487211 & 0.132946 \tabularnewline
43 & 50.55 & 50.4556 & 50.4733 & -0.0177373 & 0.0944039 \tabularnewline
44 & 50.55 & 50.4789 & 50.5817 & -0.102737 & 0.0710706 \tabularnewline
45 & 50.58 & 50.5879 & 50.6817 & -0.0937789 & -0.00788773 \tabularnewline
46 & 50.61 & 50.8334 & 50.7725 & 0.0609433 & -0.223443 \tabularnewline
47 & 50.94 & 50.9684 & 50.8517 & 0.116777 & -0.0284433 \tabularnewline
48 & 51.01 & 50.9907 & 50.9171 & 0.0735822 & 0.0193345 \tabularnewline
49 & 51.01 & 50.9751 & 50.9829 & -0.00780671 & 0.03489 \tabularnewline
50 & 51.04 & 50.9756 & 51.0488 & -0.0731539 & 0.0644039 \tabularnewline
51 & 51.15 & 51.0475 & 51.1188 & -0.0712789 & 0.102529 \tabularnewline
52 & 51.31 & 51.185 & 51.2117 & -0.0266262 & 0.124959 \tabularnewline
53 & 51.31 & 51.4035 & 51.3104 & 0.0930961 & -0.0935127 \tabularnewline
54 & 51.34 & 51.44 & 51.3912 & 0.0487211 & -0.0999711 \tabularnewline
55 & 51.34 & 51.4493 & 51.4671 & -0.0177373 & -0.109346 \tabularnewline
56 & 51.34 & 51.4385 & 51.5412 & -0.102737 & -0.0985127 \tabularnewline
57 & 51.47 & 51.5179 & 51.6117 & -0.0937789 & -0.0478877 \tabularnewline
58 & 51.95 & 51.7414 & 51.6804 & 0.0609433 & 0.20864 \tabularnewline
59 & 51.97 & 51.8743 & 51.7575 & 0.116777 & 0.0957234 \tabularnewline
60 & 51.92 & 51.9177 & 51.8442 & 0.0735822 & 0.00225116 \tabularnewline
61 & 51.92 & 51.9247 & 51.9325 & -0.00780671 & -0.00469329 \tabularnewline
62 & 51.91 & 51.9481 & 52.0212 & -0.0731539 & -0.0380961 \tabularnewline
63 & 51.97 & 52.0462 & 52.1175 & -0.0712789 & -0.0762211 \tabularnewline
64 & 52.14 & 52.1934 & 52.22 & -0.0266262 & -0.0533738 \tabularnewline
65 & 52.33 & 52.4206 & 52.3275 & 0.0930961 & -0.0905961 \tabularnewline
66 & 52.4 & 52.4912 & 52.4425 & 0.0487211 & -0.0912211 \tabularnewline
67 & 52.4 & 52.5414 & 52.5592 & -0.0177373 & -0.141429 \tabularnewline
68 & 52.41 & 52.5727 & 52.6754 & -0.102737 & -0.162679 \tabularnewline
69 & 52.71 & 52.6954 & 52.7892 & -0.0937789 & 0.0146123 \tabularnewline
70 & 53.17 & 52.9718 & 52.9108 & 0.0609433 & 0.198223 \tabularnewline
71 & 53.33 & 53.1576 & 53.0408 & 0.116777 & 0.17239 \tabularnewline
72 & 53.32 & 53.2415 & 53.1679 & 0.0735822 & 0.0785012 \tabularnewline
73 & 53.32 & 53.2859 & 53.2937 & -0.00780671 & 0.0340567 \tabularnewline
74 & 53.3 & 53.3481 & 53.4212 & -0.0731539 & -0.0480961 \tabularnewline
75 & 53.31 & 53.4691 & 53.5404 & -0.0712789 & -0.159138 \tabularnewline
76 & 53.72 & 53.6167 & 53.6433 & -0.0266262 & 0.103293 \tabularnewline
77 & 53.87 & 53.8327 & 53.7396 & 0.0930961 & 0.0373206 \tabularnewline
78 & 53.91 & 53.8871 & 53.8383 & 0.0487211 & 0.0229456 \tabularnewline
79 & 53.91 & NA & NA & -0.0177373 & NA \tabularnewline
80 & 53.96 & NA & NA & -0.102737 & NA \tabularnewline
81 & 54.02 & NA & NA & -0.0937789 & NA \tabularnewline
82 & 54.33 & NA & NA & 0.0609433 & NA \tabularnewline
83 & 54.48 & NA & NA & 0.116777 & NA \tabularnewline
84 & 54.54 & NA & NA & 0.0735822 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232275&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]47.43[/C][C]NA[/C][C]NA[/C][C]-0.00780671[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]47.43[/C][C]NA[/C][C]NA[/C][C]-0.0731539[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]47.51[/C][C]NA[/C][C]NA[/C][C]-0.0712789[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]47.96[/C][C]NA[/C][C]NA[/C][C]-0.0266262[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]47.99[/C][C]NA[/C][C]NA[/C][C]0.0930961[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]48.05[/C][C]NA[/C][C]NA[/C][C]0.0487211[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]48.05[/C][C]47.9493[/C][C]47.9671[/C][C]-0.0177373[/C][C]0.100654[/C][/ROW]
[ROW][C]8[/C][C]48.01[/C][C]47.9493[/C][C]48.0521[/C][C]-0.102737[/C][C]0.0606539[/C][/ROW]
[ROW][C]9[/C][C]48[/C][C]48.0404[/C][C]48.1342[/C][C]-0.0937789[/C][C]-0.0403877[/C][/ROW]
[ROW][C]10[/C][C]48.06[/C][C]48.2489[/C][C]48.1879[/C][C]0.0609433[/C][C]-0.18886[/C][/ROW]
[ROW][C]11[/C][C]48.23[/C][C]48.3434[/C][C]48.2267[/C][C]0.116777[/C][C]-0.113443[/C][/ROW]
[ROW][C]12[/C][C]48.4[/C][C]48.3423[/C][C]48.2687[/C][C]0.0735822[/C][C]0.0576678[/C][/ROW]
[ROW][C]13[/C][C]48.4[/C][C]48.3001[/C][C]48.3079[/C][C]-0.00780671[/C][C]0.09989[/C][/ROW]
[ROW][C]14[/C][C]48.5[/C][C]48.2743[/C][C]48.3475[/C][C]-0.0731539[/C][C]0.225654[/C][/ROW]
[ROW][C]15[/C][C]48.41[/C][C]48.315[/C][C]48.3862[/C][C]-0.0712789[/C][C]0.0950289[/C][/ROW]
[ROW][C]16[/C][C]48.35[/C][C]48.403[/C][C]48.4296[/C][C]-0.0266262[/C][C]-0.0529572[/C][/ROW]
[ROW][C]17[/C][C]48.53[/C][C]48.5685[/C][C]48.4754[/C][C]0.0930961[/C][C]-0.0385127[/C][/ROW]
[ROW][C]18[/C][C]48.52[/C][C]48.5596[/C][C]48.5108[/C][C]0.0487211[/C][C]-0.0395544[/C][/ROW]
[ROW][C]19[/C][C]48.52[/C][C]48.5214[/C][C]48.5392[/C][C]-0.0177373[/C][C]-0.0014294[/C][/ROW]
[ROW][C]20[/C][C]48.49[/C][C]48.4627[/C][C]48.5654[/C][C]-0.102737[/C][C]0.0273206[/C][/ROW]
[ROW][C]21[/C][C]48.45[/C][C]48.5008[/C][C]48.5946[/C][C]-0.0937789[/C][C]-0.0508044[/C][/ROW]
[ROW][C]22[/C][C]48.65[/C][C]48.6922[/C][C]48.6313[/C][C]0.0609433[/C][C]-0.0421933[/C][/ROW]
[ROW][C]23[/C][C]48.74[/C][C]48.7955[/C][C]48.6788[/C][C]0.116777[/C][C]-0.0555266[/C][/ROW]
[ROW][C]24[/C][C]48.74[/C][C]48.8127[/C][C]48.7392[/C][C]0.0735822[/C][C]-0.0727488[/C][/ROW]
[ROW][C]25[/C][C]48.74[/C][C]48.7964[/C][C]48.8042[/C][C]-0.00780671[/C][C]-0.05636[/C][/ROW]
[ROW][C]26[/C][C]48.79[/C][C]48.7989[/C][C]48.8721[/C][C]-0.0731539[/C][C]-0.0089294[/C][/ROW]
[ROW][C]27[/C][C]48.82[/C][C]48.8787[/C][C]48.95[/C][C]-0.0712789[/C][C]-0.0587211[/C][/ROW]
[ROW][C]28[/C][C]48.82[/C][C]49.0075[/C][C]49.0342[/C][C]-0.0266262[/C][C]-0.187541[/C][/ROW]
[ROW][C]29[/C][C]49.2[/C][C]49.2089[/C][C]49.1158[/C][C]0.0930961[/C][C]-0.0089294[/C][/ROW]
[ROW][C]30[/C][C]49.3[/C][C]49.2466[/C][C]49.1979[/C][C]0.0487211[/C][C]0.0533623[/C][/ROW]
[ROW][C]31[/C][C]49.3[/C][C]49.2643[/C][C]49.2821[/C][C]-0.0177373[/C][C]0.0356539[/C][/ROW]
[ROW][C]32[/C][C]49.34[/C][C]49.2593[/C][C]49.3621[/C][C]-0.102737[/C][C]0.0806539[/C][/ROW]
[ROW][C]33[/C][C]49.47[/C][C]49.3591[/C][C]49.4529[/C][C]-0.0937789[/C][C]0.110862[/C][/ROW]
[ROW][C]34[/C][C]49.65[/C][C]49.6239[/C][C]49.5629[/C][C]0.0609433[/C][C]0.02614[/C][/ROW]
[ROW][C]35[/C][C]49.7[/C][C]49.7922[/C][C]49.6754[/C][C]0.116777[/C][C]-0.0921933[/C][/ROW]
[ROW][C]36[/C][C]49.75[/C][C]49.8565[/C][C]49.7829[/C][C]0.0735822[/C][C]-0.106499[/C][/ROW]
[ROW][C]37[/C][C]49.75[/C][C]49.8793[/C][C]49.8871[/C][C]-0.00780671[/C][C]-0.129277[/C][/ROW]
[ROW][C]38[/C][C]49.7[/C][C]49.9164[/C][C]49.9896[/C][C]-0.0731539[/C][C]-0.216429[/C][/ROW]
[ROW][C]39[/C][C]50.09[/C][C]50.015[/C][C]50.0863[/C][C]-0.0712789[/C][C]0.0750289[/C][/ROW]
[ROW][C]40[/C][C]50.19[/C][C]50.1459[/C][C]50.1725[/C][C]-0.0266262[/C][C]0.0441262[/C][/ROW]
[ROW][C]41[/C][C]50.53[/C][C]50.3573[/C][C]50.2642[/C][C]0.0930961[/C][C]0.172737[/C][/ROW]
[ROW][C]42[/C][C]50.55[/C][C]50.4171[/C][C]50.3683[/C][C]0.0487211[/C][C]0.132946[/C][/ROW]
[ROW][C]43[/C][C]50.55[/C][C]50.4556[/C][C]50.4733[/C][C]-0.0177373[/C][C]0.0944039[/C][/ROW]
[ROW][C]44[/C][C]50.55[/C][C]50.4789[/C][C]50.5817[/C][C]-0.102737[/C][C]0.0710706[/C][/ROW]
[ROW][C]45[/C][C]50.58[/C][C]50.5879[/C][C]50.6817[/C][C]-0.0937789[/C][C]-0.00788773[/C][/ROW]
[ROW][C]46[/C][C]50.61[/C][C]50.8334[/C][C]50.7725[/C][C]0.0609433[/C][C]-0.223443[/C][/ROW]
[ROW][C]47[/C][C]50.94[/C][C]50.9684[/C][C]50.8517[/C][C]0.116777[/C][C]-0.0284433[/C][/ROW]
[ROW][C]48[/C][C]51.01[/C][C]50.9907[/C][C]50.9171[/C][C]0.0735822[/C][C]0.0193345[/C][/ROW]
[ROW][C]49[/C][C]51.01[/C][C]50.9751[/C][C]50.9829[/C][C]-0.00780671[/C][C]0.03489[/C][/ROW]
[ROW][C]50[/C][C]51.04[/C][C]50.9756[/C][C]51.0488[/C][C]-0.0731539[/C][C]0.0644039[/C][/ROW]
[ROW][C]51[/C][C]51.15[/C][C]51.0475[/C][C]51.1188[/C][C]-0.0712789[/C][C]0.102529[/C][/ROW]
[ROW][C]52[/C][C]51.31[/C][C]51.185[/C][C]51.2117[/C][C]-0.0266262[/C][C]0.124959[/C][/ROW]
[ROW][C]53[/C][C]51.31[/C][C]51.4035[/C][C]51.3104[/C][C]0.0930961[/C][C]-0.0935127[/C][/ROW]
[ROW][C]54[/C][C]51.34[/C][C]51.44[/C][C]51.3912[/C][C]0.0487211[/C][C]-0.0999711[/C][/ROW]
[ROW][C]55[/C][C]51.34[/C][C]51.4493[/C][C]51.4671[/C][C]-0.0177373[/C][C]-0.109346[/C][/ROW]
[ROW][C]56[/C][C]51.34[/C][C]51.4385[/C][C]51.5412[/C][C]-0.102737[/C][C]-0.0985127[/C][/ROW]
[ROW][C]57[/C][C]51.47[/C][C]51.5179[/C][C]51.6117[/C][C]-0.0937789[/C][C]-0.0478877[/C][/ROW]
[ROW][C]58[/C][C]51.95[/C][C]51.7414[/C][C]51.6804[/C][C]0.0609433[/C][C]0.20864[/C][/ROW]
[ROW][C]59[/C][C]51.97[/C][C]51.8743[/C][C]51.7575[/C][C]0.116777[/C][C]0.0957234[/C][/ROW]
[ROW][C]60[/C][C]51.92[/C][C]51.9177[/C][C]51.8442[/C][C]0.0735822[/C][C]0.00225116[/C][/ROW]
[ROW][C]61[/C][C]51.92[/C][C]51.9247[/C][C]51.9325[/C][C]-0.00780671[/C][C]-0.00469329[/C][/ROW]
[ROW][C]62[/C][C]51.91[/C][C]51.9481[/C][C]52.0212[/C][C]-0.0731539[/C][C]-0.0380961[/C][/ROW]
[ROW][C]63[/C][C]51.97[/C][C]52.0462[/C][C]52.1175[/C][C]-0.0712789[/C][C]-0.0762211[/C][/ROW]
[ROW][C]64[/C][C]52.14[/C][C]52.1934[/C][C]52.22[/C][C]-0.0266262[/C][C]-0.0533738[/C][/ROW]
[ROW][C]65[/C][C]52.33[/C][C]52.4206[/C][C]52.3275[/C][C]0.0930961[/C][C]-0.0905961[/C][/ROW]
[ROW][C]66[/C][C]52.4[/C][C]52.4912[/C][C]52.4425[/C][C]0.0487211[/C][C]-0.0912211[/C][/ROW]
[ROW][C]67[/C][C]52.4[/C][C]52.5414[/C][C]52.5592[/C][C]-0.0177373[/C][C]-0.141429[/C][/ROW]
[ROW][C]68[/C][C]52.41[/C][C]52.5727[/C][C]52.6754[/C][C]-0.102737[/C][C]-0.162679[/C][/ROW]
[ROW][C]69[/C][C]52.71[/C][C]52.6954[/C][C]52.7892[/C][C]-0.0937789[/C][C]0.0146123[/C][/ROW]
[ROW][C]70[/C][C]53.17[/C][C]52.9718[/C][C]52.9108[/C][C]0.0609433[/C][C]0.198223[/C][/ROW]
[ROW][C]71[/C][C]53.33[/C][C]53.1576[/C][C]53.0408[/C][C]0.116777[/C][C]0.17239[/C][/ROW]
[ROW][C]72[/C][C]53.32[/C][C]53.2415[/C][C]53.1679[/C][C]0.0735822[/C][C]0.0785012[/C][/ROW]
[ROW][C]73[/C][C]53.32[/C][C]53.2859[/C][C]53.2937[/C][C]-0.00780671[/C][C]0.0340567[/C][/ROW]
[ROW][C]74[/C][C]53.3[/C][C]53.3481[/C][C]53.4212[/C][C]-0.0731539[/C][C]-0.0480961[/C][/ROW]
[ROW][C]75[/C][C]53.31[/C][C]53.4691[/C][C]53.5404[/C][C]-0.0712789[/C][C]-0.159138[/C][/ROW]
[ROW][C]76[/C][C]53.72[/C][C]53.6167[/C][C]53.6433[/C][C]-0.0266262[/C][C]0.103293[/C][/ROW]
[ROW][C]77[/C][C]53.87[/C][C]53.8327[/C][C]53.7396[/C][C]0.0930961[/C][C]0.0373206[/C][/ROW]
[ROW][C]78[/C][C]53.91[/C][C]53.8871[/C][C]53.8383[/C][C]0.0487211[/C][C]0.0229456[/C][/ROW]
[ROW][C]79[/C][C]53.91[/C][C]NA[/C][C]NA[/C][C]-0.0177373[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]53.96[/C][C]NA[/C][C]NA[/C][C]-0.102737[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]54.02[/C][C]NA[/C][C]NA[/C][C]-0.0937789[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]54.33[/C][C]NA[/C][C]NA[/C][C]0.0609433[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]54.48[/C][C]NA[/C][C]NA[/C][C]0.116777[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]54.54[/C][C]NA[/C][C]NA[/C][C]0.0735822[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232275&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232275&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
147.43NANA-0.00780671NA
247.43NANA-0.0731539NA
347.51NANA-0.0712789NA
447.96NANA-0.0266262NA
547.99NANA0.0930961NA
648.05NANA0.0487211NA
748.0547.949347.9671-0.01773730.100654
848.0147.949348.0521-0.1027370.0606539
94848.040448.1342-0.0937789-0.0403877
1048.0648.248948.18790.0609433-0.18886
1148.2348.343448.22670.116777-0.113443
1248.448.342348.26870.07358220.0576678
1348.448.300148.3079-0.007806710.09989
1448.548.274348.3475-0.07315390.225654
1548.4148.31548.3862-0.07127890.0950289
1648.3548.40348.4296-0.0266262-0.0529572
1748.5348.568548.47540.0930961-0.0385127
1848.5248.559648.51080.0487211-0.0395544
1948.5248.521448.5392-0.0177373-0.0014294
2048.4948.462748.5654-0.1027370.0273206
2148.4548.500848.5946-0.0937789-0.0508044
2248.6548.692248.63130.0609433-0.0421933
2348.7448.795548.67880.116777-0.0555266
2448.7448.812748.73920.0735822-0.0727488
2548.7448.796448.8042-0.00780671-0.05636
2648.7948.798948.8721-0.0731539-0.0089294
2748.8248.878748.95-0.0712789-0.0587211
2848.8249.007549.0342-0.0266262-0.187541
2949.249.208949.11580.0930961-0.0089294
3049.349.246649.19790.04872110.0533623
3149.349.264349.2821-0.01773730.0356539
3249.3449.259349.3621-0.1027370.0806539
3349.4749.359149.4529-0.09377890.110862
3449.6549.623949.56290.06094330.02614
3549.749.792249.67540.116777-0.0921933
3649.7549.856549.78290.0735822-0.106499
3749.7549.879349.8871-0.00780671-0.129277
3849.749.916449.9896-0.0731539-0.216429
3950.0950.01550.0863-0.07127890.0750289
4050.1950.145950.1725-0.02662620.0441262
4150.5350.357350.26420.09309610.172737
4250.5550.417150.36830.04872110.132946
4350.5550.455650.4733-0.01773730.0944039
4450.5550.478950.5817-0.1027370.0710706
4550.5850.587950.6817-0.0937789-0.00788773
4650.6150.833450.77250.0609433-0.223443
4750.9450.968450.85170.116777-0.0284433
4851.0150.990750.91710.07358220.0193345
4951.0150.975150.9829-0.007806710.03489
5051.0450.975651.0488-0.07315390.0644039
5151.1551.047551.1188-0.07127890.102529
5251.3151.18551.2117-0.02662620.124959
5351.3151.403551.31040.0930961-0.0935127
5451.3451.4451.39120.0487211-0.0999711
5551.3451.449351.4671-0.0177373-0.109346
5651.3451.438551.5412-0.102737-0.0985127
5751.4751.517951.6117-0.0937789-0.0478877
5851.9551.741451.68040.06094330.20864
5951.9751.874351.75750.1167770.0957234
6051.9251.917751.84420.07358220.00225116
6151.9251.924751.9325-0.00780671-0.00469329
6251.9151.948152.0212-0.0731539-0.0380961
6351.9752.046252.1175-0.0712789-0.0762211
6452.1452.193452.22-0.0266262-0.0533738
6552.3352.420652.32750.0930961-0.0905961
6652.452.491252.44250.0487211-0.0912211
6752.452.541452.5592-0.0177373-0.141429
6852.4152.572752.6754-0.102737-0.162679
6952.7152.695452.7892-0.09377890.0146123
7053.1752.971852.91080.06094330.198223
7153.3353.157653.04080.1167770.17239
7253.3253.241553.16790.07358220.0785012
7353.3253.285953.2937-0.007806710.0340567
7453.353.348153.4212-0.0731539-0.0480961
7553.3153.469153.5404-0.0712789-0.159138
7653.7253.616753.6433-0.02662620.103293
7753.8753.832753.73960.09309610.0373206
7853.9153.887153.83830.04872110.0229456
7953.91NANA-0.0177373NA
8053.96NANA-0.102737NA
8154.02NANA-0.0937789NA
8254.33NANA0.0609433NA
8354.48NANA0.116777NA
8454.54NANA0.0735822NA



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')