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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 04:40:53 -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/t1386841288xotdexqzp96kk0o.htm/, Retrieved Tue, 07 Dec 2021 11:58:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232234, Retrieved Tue, 07 Dec 2021 11:58:19 +0000
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IsPrivate?No (this computation is public)
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Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation Plot] [standard deviatio...] [2013-12-05 09:37:59] [08f91d6d86abec7b504e1e24533558b8]
- RMPD    [Classical Decomposition] [decomp eigen reeks] [2013-12-12 09:40:53] [efb3549c5c864f6f07b072e448ef7cfe] [Current]
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Dataseries X:
82,81
83,42
83,45
83,71
84,8
85,95
86,22
86,75
87,06
87,17
87,63
87,78
88,4
89,35
89,53
90,66
90,81
91,55
91,58
91,76
91,78
91,71
91,57
91,95
92,16
92,26
92,44
93,12
93,55
93,63
93,74
94,08
94,24
94,66
94,69
94,69
94,69
94,72
95,15
95,28
96,12
96,5
96,67
96,83
97,4
97,75
97,46
97,46
97,56
97,97
98,89
99,1
99,3
100
99,73
99,34
99,78
99,5
99,6
99,52
99,63
99,61
99,73
100,53
100,87
100,9
101,08
102,95
102,58
102,6
102,45
102,41
102,38
102,65
103,33
103,68
104,13
104,3
104,11
104,17
104,23
104,47
104,86
104,9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232234&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]7 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=232234&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232234&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 time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
182.81NANA-0.449838NA
283.42NANA-0.405046NA
383.45NANA-0.226921NA
483.71NANA0.0837037NA
584.8NANA0.245579NA
685.95NANA0.357037NA
786.2285.982985.79540.1875230.23706
886.7586.641886.27540.3664120.108171
987.0687.05986.77580.2831480.00101852
1087.1787.416887.31880.0980787-0.246829
1187.6387.685687.8588-0.173171-0.0555787
1287.7887.97688.3425-0.366505-0.195995
1388.488.349388.7992-0.4498380.0506713
1489.3588.826289.2312-0.4050460.523796
1589.5389.409789.6367-0.2269210.120255
1690.6690.106290.02250.08370370.553796
1790.8190.621490.37580.2455790.188588
1891.5591.070890.71370.3570370.479213
1991.5891.231791.04420.1875230.34831
2091.7691.688591.32210.3664120.0715046
2191.7891.847791.56460.283148-0.0677315
2291.7191.886491.78830.0980787-0.176412
2391.5791.831892.005-0.173171-0.261829
2491.9591.839392.2058-0.3665050.110671
2592.1691.932792.3825-0.4498380.227338
2692.2692.164192.5692-0.4050460.0958796
2792.4492.541492.7683-0.226921-0.101412
2893.1293.077592.99370.08370370.0425463
2993.5593.492293.24670.2455790.0577546
3093.6393.847993.49080.357037-0.21787
3193.7493.897993.71040.187523-0.15794
3294.0894.284793.91830.366412-0.204745
3394.2494.416994.13370.283148-0.176898
3494.6694.434794.33670.09807870.225255
3594.6994.360694.5338-0.1731710.329421
3694.6994.393994.7604-0.3665050.296088
3794.6994.552295.0021-0.4498380.137755
3894.7294.833795.2388-0.405046-0.113704
3995.1595.258195.485-0.226921-0.108079
4095.2895.829195.74540.0837037-0.54912
4196.1296.235295.98960.245579-0.115162
4296.596.577596.22040.357037-0.0774537
4396.6796.642996.45540.1875230.0270602
4496.8397.076896.71040.366412-0.246829
4597.497.284897.00170.2831480.115185
4697.7597.414797.31670.09807870.335255
4797.4697.435297.6083-0.1731710.024838
4897.4697.520297.8867-0.366505-0.060162
4997.5697.710298.16-0.449838-0.150162
5097.9797.98798.3921-0.405046-0.017037
5198.8998.368998.5958-0.2269210.521088
5299.198.851698.76790.08370370.24838
5399.399.175698.930.2455790.124421
5410099.46299.1050.3570370.537963
5599.7399.464699.27710.1875230.265394
5699.3499.798199.43170.366412-0.458079
5799.7899.818199.5350.283148-0.0381481
5899.599.727799.62960.0980787-0.227662
5999.699.581499.7546-0.1731710.018588
6099.5299.49199.8575-0.3665050.0290046
6199.6399.501499.9512-0.4498380.128588
6299.6199.7529100.158-0.405046-0.14287
6399.73100.198100.425-0.226921-0.468079
64100.53100.755100.6710.0837037-0.224537
65100.87101.164100.9190.245579-0.294329
66100.9101.515101.1580.357037-0.614954
67101.08101.58101.3930.187523-0.50044
68102.95102.001101.6340.3664120.949421
69102.58102.194101.9110.2831480.386019
70102.6102.29102.1920.09807870.309838
71102.45102.286102.459-0.1731710.164005
72102.41102.37102.737-0.3665050.039838
73102.38102.555103.005-0.449838-0.174745
74102.65102.777103.182-0.405046-0.12662
75103.33103.074103.301-0.2269210.255671
76103.68103.532103.4480.08370370.14838
77104.13103.872103.6260.2455790.258171
78104.3104.187103.830.3570370.112546
79104.11NANA0.187523NA
80104.17NANA0.366412NA
81104.23NANA0.283148NA
82104.47NANA0.0980787NA
83104.86NANA-0.173171NA
84104.9NANA-0.366505NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 82.81 & NA & NA & -0.449838 & NA \tabularnewline
2 & 83.42 & NA & NA & -0.405046 & NA \tabularnewline
3 & 83.45 & NA & NA & -0.226921 & NA \tabularnewline
4 & 83.71 & NA & NA & 0.0837037 & NA \tabularnewline
5 & 84.8 & NA & NA & 0.245579 & NA \tabularnewline
6 & 85.95 & NA & NA & 0.357037 & NA \tabularnewline
7 & 86.22 & 85.9829 & 85.7954 & 0.187523 & 0.23706 \tabularnewline
8 & 86.75 & 86.6418 & 86.2754 & 0.366412 & 0.108171 \tabularnewline
9 & 87.06 & 87.059 & 86.7758 & 0.283148 & 0.00101852 \tabularnewline
10 & 87.17 & 87.4168 & 87.3188 & 0.0980787 & -0.246829 \tabularnewline
11 & 87.63 & 87.6856 & 87.8588 & -0.173171 & -0.0555787 \tabularnewline
12 & 87.78 & 87.976 & 88.3425 & -0.366505 & -0.195995 \tabularnewline
13 & 88.4 & 88.3493 & 88.7992 & -0.449838 & 0.0506713 \tabularnewline
14 & 89.35 & 88.8262 & 89.2312 & -0.405046 & 0.523796 \tabularnewline
15 & 89.53 & 89.4097 & 89.6367 & -0.226921 & 0.120255 \tabularnewline
16 & 90.66 & 90.1062 & 90.0225 & 0.0837037 & 0.553796 \tabularnewline
17 & 90.81 & 90.6214 & 90.3758 & 0.245579 & 0.188588 \tabularnewline
18 & 91.55 & 91.0708 & 90.7137 & 0.357037 & 0.479213 \tabularnewline
19 & 91.58 & 91.2317 & 91.0442 & 0.187523 & 0.34831 \tabularnewline
20 & 91.76 & 91.6885 & 91.3221 & 0.366412 & 0.0715046 \tabularnewline
21 & 91.78 & 91.8477 & 91.5646 & 0.283148 & -0.0677315 \tabularnewline
22 & 91.71 & 91.8864 & 91.7883 & 0.0980787 & -0.176412 \tabularnewline
23 & 91.57 & 91.8318 & 92.005 & -0.173171 & -0.261829 \tabularnewline
24 & 91.95 & 91.8393 & 92.2058 & -0.366505 & 0.110671 \tabularnewline
25 & 92.16 & 91.9327 & 92.3825 & -0.449838 & 0.227338 \tabularnewline
26 & 92.26 & 92.1641 & 92.5692 & -0.405046 & 0.0958796 \tabularnewline
27 & 92.44 & 92.5414 & 92.7683 & -0.226921 & -0.101412 \tabularnewline
28 & 93.12 & 93.0775 & 92.9937 & 0.0837037 & 0.0425463 \tabularnewline
29 & 93.55 & 93.4922 & 93.2467 & 0.245579 & 0.0577546 \tabularnewline
30 & 93.63 & 93.8479 & 93.4908 & 0.357037 & -0.21787 \tabularnewline
31 & 93.74 & 93.8979 & 93.7104 & 0.187523 & -0.15794 \tabularnewline
32 & 94.08 & 94.2847 & 93.9183 & 0.366412 & -0.204745 \tabularnewline
33 & 94.24 & 94.4169 & 94.1337 & 0.283148 & -0.176898 \tabularnewline
34 & 94.66 & 94.4347 & 94.3367 & 0.0980787 & 0.225255 \tabularnewline
35 & 94.69 & 94.3606 & 94.5338 & -0.173171 & 0.329421 \tabularnewline
36 & 94.69 & 94.3939 & 94.7604 & -0.366505 & 0.296088 \tabularnewline
37 & 94.69 & 94.5522 & 95.0021 & -0.449838 & 0.137755 \tabularnewline
38 & 94.72 & 94.8337 & 95.2388 & -0.405046 & -0.113704 \tabularnewline
39 & 95.15 & 95.2581 & 95.485 & -0.226921 & -0.108079 \tabularnewline
40 & 95.28 & 95.8291 & 95.7454 & 0.0837037 & -0.54912 \tabularnewline
41 & 96.12 & 96.2352 & 95.9896 & 0.245579 & -0.115162 \tabularnewline
42 & 96.5 & 96.5775 & 96.2204 & 0.357037 & -0.0774537 \tabularnewline
43 & 96.67 & 96.6429 & 96.4554 & 0.187523 & 0.0270602 \tabularnewline
44 & 96.83 & 97.0768 & 96.7104 & 0.366412 & -0.246829 \tabularnewline
45 & 97.4 & 97.2848 & 97.0017 & 0.283148 & 0.115185 \tabularnewline
46 & 97.75 & 97.4147 & 97.3167 & 0.0980787 & 0.335255 \tabularnewline
47 & 97.46 & 97.4352 & 97.6083 & -0.173171 & 0.024838 \tabularnewline
48 & 97.46 & 97.5202 & 97.8867 & -0.366505 & -0.060162 \tabularnewline
49 & 97.56 & 97.7102 & 98.16 & -0.449838 & -0.150162 \tabularnewline
50 & 97.97 & 97.987 & 98.3921 & -0.405046 & -0.017037 \tabularnewline
51 & 98.89 & 98.3689 & 98.5958 & -0.226921 & 0.521088 \tabularnewline
52 & 99.1 & 98.8516 & 98.7679 & 0.0837037 & 0.24838 \tabularnewline
53 & 99.3 & 99.1756 & 98.93 & 0.245579 & 0.124421 \tabularnewline
54 & 100 & 99.462 & 99.105 & 0.357037 & 0.537963 \tabularnewline
55 & 99.73 & 99.4646 & 99.2771 & 0.187523 & 0.265394 \tabularnewline
56 & 99.34 & 99.7981 & 99.4317 & 0.366412 & -0.458079 \tabularnewline
57 & 99.78 & 99.8181 & 99.535 & 0.283148 & -0.0381481 \tabularnewline
58 & 99.5 & 99.7277 & 99.6296 & 0.0980787 & -0.227662 \tabularnewline
59 & 99.6 & 99.5814 & 99.7546 & -0.173171 & 0.018588 \tabularnewline
60 & 99.52 & 99.491 & 99.8575 & -0.366505 & 0.0290046 \tabularnewline
61 & 99.63 & 99.5014 & 99.9512 & -0.449838 & 0.128588 \tabularnewline
62 & 99.61 & 99.7529 & 100.158 & -0.405046 & -0.14287 \tabularnewline
63 & 99.73 & 100.198 & 100.425 & -0.226921 & -0.468079 \tabularnewline
64 & 100.53 & 100.755 & 100.671 & 0.0837037 & -0.224537 \tabularnewline
65 & 100.87 & 101.164 & 100.919 & 0.245579 & -0.294329 \tabularnewline
66 & 100.9 & 101.515 & 101.158 & 0.357037 & -0.614954 \tabularnewline
67 & 101.08 & 101.58 & 101.393 & 0.187523 & -0.50044 \tabularnewline
68 & 102.95 & 102.001 & 101.634 & 0.366412 & 0.949421 \tabularnewline
69 & 102.58 & 102.194 & 101.911 & 0.283148 & 0.386019 \tabularnewline
70 & 102.6 & 102.29 & 102.192 & 0.0980787 & 0.309838 \tabularnewline
71 & 102.45 & 102.286 & 102.459 & -0.173171 & 0.164005 \tabularnewline
72 & 102.41 & 102.37 & 102.737 & -0.366505 & 0.039838 \tabularnewline
73 & 102.38 & 102.555 & 103.005 & -0.449838 & -0.174745 \tabularnewline
74 & 102.65 & 102.777 & 103.182 & -0.405046 & -0.12662 \tabularnewline
75 & 103.33 & 103.074 & 103.301 & -0.226921 & 0.255671 \tabularnewline
76 & 103.68 & 103.532 & 103.448 & 0.0837037 & 0.14838 \tabularnewline
77 & 104.13 & 103.872 & 103.626 & 0.245579 & 0.258171 \tabularnewline
78 & 104.3 & 104.187 & 103.83 & 0.357037 & 0.112546 \tabularnewline
79 & 104.11 & NA & NA & 0.187523 & NA \tabularnewline
80 & 104.17 & NA & NA & 0.366412 & NA \tabularnewline
81 & 104.23 & NA & NA & 0.283148 & NA \tabularnewline
82 & 104.47 & NA & NA & 0.0980787 & NA \tabularnewline
83 & 104.86 & NA & NA & -0.173171 & NA \tabularnewline
84 & 104.9 & NA & NA & -0.366505 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232234&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]82.81[/C][C]NA[/C][C]NA[/C][C]-0.449838[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]83.42[/C][C]NA[/C][C]NA[/C][C]-0.405046[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]83.45[/C][C]NA[/C][C]NA[/C][C]-0.226921[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]83.71[/C][C]NA[/C][C]NA[/C][C]0.0837037[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]84.8[/C][C]NA[/C][C]NA[/C][C]0.245579[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]85.95[/C][C]NA[/C][C]NA[/C][C]0.357037[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]86.22[/C][C]85.9829[/C][C]85.7954[/C][C]0.187523[/C][C]0.23706[/C][/ROW]
[ROW][C]8[/C][C]86.75[/C][C]86.6418[/C][C]86.2754[/C][C]0.366412[/C][C]0.108171[/C][/ROW]
[ROW][C]9[/C][C]87.06[/C][C]87.059[/C][C]86.7758[/C][C]0.283148[/C][C]0.00101852[/C][/ROW]
[ROW][C]10[/C][C]87.17[/C][C]87.4168[/C][C]87.3188[/C][C]0.0980787[/C][C]-0.246829[/C][/ROW]
[ROW][C]11[/C][C]87.63[/C][C]87.6856[/C][C]87.8588[/C][C]-0.173171[/C][C]-0.0555787[/C][/ROW]
[ROW][C]12[/C][C]87.78[/C][C]87.976[/C][C]88.3425[/C][C]-0.366505[/C][C]-0.195995[/C][/ROW]
[ROW][C]13[/C][C]88.4[/C][C]88.3493[/C][C]88.7992[/C][C]-0.449838[/C][C]0.0506713[/C][/ROW]
[ROW][C]14[/C][C]89.35[/C][C]88.8262[/C][C]89.2312[/C][C]-0.405046[/C][C]0.523796[/C][/ROW]
[ROW][C]15[/C][C]89.53[/C][C]89.4097[/C][C]89.6367[/C][C]-0.226921[/C][C]0.120255[/C][/ROW]
[ROW][C]16[/C][C]90.66[/C][C]90.1062[/C][C]90.0225[/C][C]0.0837037[/C][C]0.553796[/C][/ROW]
[ROW][C]17[/C][C]90.81[/C][C]90.6214[/C][C]90.3758[/C][C]0.245579[/C][C]0.188588[/C][/ROW]
[ROW][C]18[/C][C]91.55[/C][C]91.0708[/C][C]90.7137[/C][C]0.357037[/C][C]0.479213[/C][/ROW]
[ROW][C]19[/C][C]91.58[/C][C]91.2317[/C][C]91.0442[/C][C]0.187523[/C][C]0.34831[/C][/ROW]
[ROW][C]20[/C][C]91.76[/C][C]91.6885[/C][C]91.3221[/C][C]0.366412[/C][C]0.0715046[/C][/ROW]
[ROW][C]21[/C][C]91.78[/C][C]91.8477[/C][C]91.5646[/C][C]0.283148[/C][C]-0.0677315[/C][/ROW]
[ROW][C]22[/C][C]91.71[/C][C]91.8864[/C][C]91.7883[/C][C]0.0980787[/C][C]-0.176412[/C][/ROW]
[ROW][C]23[/C][C]91.57[/C][C]91.8318[/C][C]92.005[/C][C]-0.173171[/C][C]-0.261829[/C][/ROW]
[ROW][C]24[/C][C]91.95[/C][C]91.8393[/C][C]92.2058[/C][C]-0.366505[/C][C]0.110671[/C][/ROW]
[ROW][C]25[/C][C]92.16[/C][C]91.9327[/C][C]92.3825[/C][C]-0.449838[/C][C]0.227338[/C][/ROW]
[ROW][C]26[/C][C]92.26[/C][C]92.1641[/C][C]92.5692[/C][C]-0.405046[/C][C]0.0958796[/C][/ROW]
[ROW][C]27[/C][C]92.44[/C][C]92.5414[/C][C]92.7683[/C][C]-0.226921[/C][C]-0.101412[/C][/ROW]
[ROW][C]28[/C][C]93.12[/C][C]93.0775[/C][C]92.9937[/C][C]0.0837037[/C][C]0.0425463[/C][/ROW]
[ROW][C]29[/C][C]93.55[/C][C]93.4922[/C][C]93.2467[/C][C]0.245579[/C][C]0.0577546[/C][/ROW]
[ROW][C]30[/C][C]93.63[/C][C]93.8479[/C][C]93.4908[/C][C]0.357037[/C][C]-0.21787[/C][/ROW]
[ROW][C]31[/C][C]93.74[/C][C]93.8979[/C][C]93.7104[/C][C]0.187523[/C][C]-0.15794[/C][/ROW]
[ROW][C]32[/C][C]94.08[/C][C]94.2847[/C][C]93.9183[/C][C]0.366412[/C][C]-0.204745[/C][/ROW]
[ROW][C]33[/C][C]94.24[/C][C]94.4169[/C][C]94.1337[/C][C]0.283148[/C][C]-0.176898[/C][/ROW]
[ROW][C]34[/C][C]94.66[/C][C]94.4347[/C][C]94.3367[/C][C]0.0980787[/C][C]0.225255[/C][/ROW]
[ROW][C]35[/C][C]94.69[/C][C]94.3606[/C][C]94.5338[/C][C]-0.173171[/C][C]0.329421[/C][/ROW]
[ROW][C]36[/C][C]94.69[/C][C]94.3939[/C][C]94.7604[/C][C]-0.366505[/C][C]0.296088[/C][/ROW]
[ROW][C]37[/C][C]94.69[/C][C]94.5522[/C][C]95.0021[/C][C]-0.449838[/C][C]0.137755[/C][/ROW]
[ROW][C]38[/C][C]94.72[/C][C]94.8337[/C][C]95.2388[/C][C]-0.405046[/C][C]-0.113704[/C][/ROW]
[ROW][C]39[/C][C]95.15[/C][C]95.2581[/C][C]95.485[/C][C]-0.226921[/C][C]-0.108079[/C][/ROW]
[ROW][C]40[/C][C]95.28[/C][C]95.8291[/C][C]95.7454[/C][C]0.0837037[/C][C]-0.54912[/C][/ROW]
[ROW][C]41[/C][C]96.12[/C][C]96.2352[/C][C]95.9896[/C][C]0.245579[/C][C]-0.115162[/C][/ROW]
[ROW][C]42[/C][C]96.5[/C][C]96.5775[/C][C]96.2204[/C][C]0.357037[/C][C]-0.0774537[/C][/ROW]
[ROW][C]43[/C][C]96.67[/C][C]96.6429[/C][C]96.4554[/C][C]0.187523[/C][C]0.0270602[/C][/ROW]
[ROW][C]44[/C][C]96.83[/C][C]97.0768[/C][C]96.7104[/C][C]0.366412[/C][C]-0.246829[/C][/ROW]
[ROW][C]45[/C][C]97.4[/C][C]97.2848[/C][C]97.0017[/C][C]0.283148[/C][C]0.115185[/C][/ROW]
[ROW][C]46[/C][C]97.75[/C][C]97.4147[/C][C]97.3167[/C][C]0.0980787[/C][C]0.335255[/C][/ROW]
[ROW][C]47[/C][C]97.46[/C][C]97.4352[/C][C]97.6083[/C][C]-0.173171[/C][C]0.024838[/C][/ROW]
[ROW][C]48[/C][C]97.46[/C][C]97.5202[/C][C]97.8867[/C][C]-0.366505[/C][C]-0.060162[/C][/ROW]
[ROW][C]49[/C][C]97.56[/C][C]97.7102[/C][C]98.16[/C][C]-0.449838[/C][C]-0.150162[/C][/ROW]
[ROW][C]50[/C][C]97.97[/C][C]97.987[/C][C]98.3921[/C][C]-0.405046[/C][C]-0.017037[/C][/ROW]
[ROW][C]51[/C][C]98.89[/C][C]98.3689[/C][C]98.5958[/C][C]-0.226921[/C][C]0.521088[/C][/ROW]
[ROW][C]52[/C][C]99.1[/C][C]98.8516[/C][C]98.7679[/C][C]0.0837037[/C][C]0.24838[/C][/ROW]
[ROW][C]53[/C][C]99.3[/C][C]99.1756[/C][C]98.93[/C][C]0.245579[/C][C]0.124421[/C][/ROW]
[ROW][C]54[/C][C]100[/C][C]99.462[/C][C]99.105[/C][C]0.357037[/C][C]0.537963[/C][/ROW]
[ROW][C]55[/C][C]99.73[/C][C]99.4646[/C][C]99.2771[/C][C]0.187523[/C][C]0.265394[/C][/ROW]
[ROW][C]56[/C][C]99.34[/C][C]99.7981[/C][C]99.4317[/C][C]0.366412[/C][C]-0.458079[/C][/ROW]
[ROW][C]57[/C][C]99.78[/C][C]99.8181[/C][C]99.535[/C][C]0.283148[/C][C]-0.0381481[/C][/ROW]
[ROW][C]58[/C][C]99.5[/C][C]99.7277[/C][C]99.6296[/C][C]0.0980787[/C][C]-0.227662[/C][/ROW]
[ROW][C]59[/C][C]99.6[/C][C]99.5814[/C][C]99.7546[/C][C]-0.173171[/C][C]0.018588[/C][/ROW]
[ROW][C]60[/C][C]99.52[/C][C]99.491[/C][C]99.8575[/C][C]-0.366505[/C][C]0.0290046[/C][/ROW]
[ROW][C]61[/C][C]99.63[/C][C]99.5014[/C][C]99.9512[/C][C]-0.449838[/C][C]0.128588[/C][/ROW]
[ROW][C]62[/C][C]99.61[/C][C]99.7529[/C][C]100.158[/C][C]-0.405046[/C][C]-0.14287[/C][/ROW]
[ROW][C]63[/C][C]99.73[/C][C]100.198[/C][C]100.425[/C][C]-0.226921[/C][C]-0.468079[/C][/ROW]
[ROW][C]64[/C][C]100.53[/C][C]100.755[/C][C]100.671[/C][C]0.0837037[/C][C]-0.224537[/C][/ROW]
[ROW][C]65[/C][C]100.87[/C][C]101.164[/C][C]100.919[/C][C]0.245579[/C][C]-0.294329[/C][/ROW]
[ROW][C]66[/C][C]100.9[/C][C]101.515[/C][C]101.158[/C][C]0.357037[/C][C]-0.614954[/C][/ROW]
[ROW][C]67[/C][C]101.08[/C][C]101.58[/C][C]101.393[/C][C]0.187523[/C][C]-0.50044[/C][/ROW]
[ROW][C]68[/C][C]102.95[/C][C]102.001[/C][C]101.634[/C][C]0.366412[/C][C]0.949421[/C][/ROW]
[ROW][C]69[/C][C]102.58[/C][C]102.194[/C][C]101.911[/C][C]0.283148[/C][C]0.386019[/C][/ROW]
[ROW][C]70[/C][C]102.6[/C][C]102.29[/C][C]102.192[/C][C]0.0980787[/C][C]0.309838[/C][/ROW]
[ROW][C]71[/C][C]102.45[/C][C]102.286[/C][C]102.459[/C][C]-0.173171[/C][C]0.164005[/C][/ROW]
[ROW][C]72[/C][C]102.41[/C][C]102.37[/C][C]102.737[/C][C]-0.366505[/C][C]0.039838[/C][/ROW]
[ROW][C]73[/C][C]102.38[/C][C]102.555[/C][C]103.005[/C][C]-0.449838[/C][C]-0.174745[/C][/ROW]
[ROW][C]74[/C][C]102.65[/C][C]102.777[/C][C]103.182[/C][C]-0.405046[/C][C]-0.12662[/C][/ROW]
[ROW][C]75[/C][C]103.33[/C][C]103.074[/C][C]103.301[/C][C]-0.226921[/C][C]0.255671[/C][/ROW]
[ROW][C]76[/C][C]103.68[/C][C]103.532[/C][C]103.448[/C][C]0.0837037[/C][C]0.14838[/C][/ROW]
[ROW][C]77[/C][C]104.13[/C][C]103.872[/C][C]103.626[/C][C]0.245579[/C][C]0.258171[/C][/ROW]
[ROW][C]78[/C][C]104.3[/C][C]104.187[/C][C]103.83[/C][C]0.357037[/C][C]0.112546[/C][/ROW]
[ROW][C]79[/C][C]104.11[/C][C]NA[/C][C]NA[/C][C]0.187523[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]104.17[/C][C]NA[/C][C]NA[/C][C]0.366412[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]104.23[/C][C]NA[/C][C]NA[/C][C]0.283148[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]104.47[/C][C]NA[/C][C]NA[/C][C]0.0980787[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]104.86[/C][C]NA[/C][C]NA[/C][C]-0.173171[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]104.9[/C][C]NA[/C][C]NA[/C][C]-0.366505[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232234&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232234&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
182.81NANA-0.449838NA
283.42NANA-0.405046NA
383.45NANA-0.226921NA
483.71NANA0.0837037NA
584.8NANA0.245579NA
685.95NANA0.357037NA
786.2285.982985.79540.1875230.23706
886.7586.641886.27540.3664120.108171
987.0687.05986.77580.2831480.00101852
1087.1787.416887.31880.0980787-0.246829
1187.6387.685687.8588-0.173171-0.0555787
1287.7887.97688.3425-0.366505-0.195995
1388.488.349388.7992-0.4498380.0506713
1489.3588.826289.2312-0.4050460.523796
1589.5389.409789.6367-0.2269210.120255
1690.6690.106290.02250.08370370.553796
1790.8190.621490.37580.2455790.188588
1891.5591.070890.71370.3570370.479213
1991.5891.231791.04420.1875230.34831
2091.7691.688591.32210.3664120.0715046
2191.7891.847791.56460.283148-0.0677315
2291.7191.886491.78830.0980787-0.176412
2391.5791.831892.005-0.173171-0.261829
2491.9591.839392.2058-0.3665050.110671
2592.1691.932792.3825-0.4498380.227338
2692.2692.164192.5692-0.4050460.0958796
2792.4492.541492.7683-0.226921-0.101412
2893.1293.077592.99370.08370370.0425463
2993.5593.492293.24670.2455790.0577546
3093.6393.847993.49080.357037-0.21787
3193.7493.897993.71040.187523-0.15794
3294.0894.284793.91830.366412-0.204745
3394.2494.416994.13370.283148-0.176898
3494.6694.434794.33670.09807870.225255
3594.6994.360694.5338-0.1731710.329421
3694.6994.393994.7604-0.3665050.296088
3794.6994.552295.0021-0.4498380.137755
3894.7294.833795.2388-0.405046-0.113704
3995.1595.258195.485-0.226921-0.108079
4095.2895.829195.74540.0837037-0.54912
4196.1296.235295.98960.245579-0.115162
4296.596.577596.22040.357037-0.0774537
4396.6796.642996.45540.1875230.0270602
4496.8397.076896.71040.366412-0.246829
4597.497.284897.00170.2831480.115185
4697.7597.414797.31670.09807870.335255
4797.4697.435297.6083-0.1731710.024838
4897.4697.520297.8867-0.366505-0.060162
4997.5697.710298.16-0.449838-0.150162
5097.9797.98798.3921-0.405046-0.017037
5198.8998.368998.5958-0.2269210.521088
5299.198.851698.76790.08370370.24838
5399.399.175698.930.2455790.124421
5410099.46299.1050.3570370.537963
5599.7399.464699.27710.1875230.265394
5699.3499.798199.43170.366412-0.458079
5799.7899.818199.5350.283148-0.0381481
5899.599.727799.62960.0980787-0.227662
5999.699.581499.7546-0.1731710.018588
6099.5299.49199.8575-0.3665050.0290046
6199.6399.501499.9512-0.4498380.128588
6299.6199.7529100.158-0.405046-0.14287
6399.73100.198100.425-0.226921-0.468079
64100.53100.755100.6710.0837037-0.224537
65100.87101.164100.9190.245579-0.294329
66100.9101.515101.1580.357037-0.614954
67101.08101.58101.3930.187523-0.50044
68102.95102.001101.6340.3664120.949421
69102.58102.194101.9110.2831480.386019
70102.6102.29102.1920.09807870.309838
71102.45102.286102.459-0.1731710.164005
72102.41102.37102.737-0.3665050.039838
73102.38102.555103.005-0.449838-0.174745
74102.65102.777103.182-0.405046-0.12662
75103.33103.074103.301-0.2269210.255671
76103.68103.532103.4480.08370370.14838
77104.13103.872103.6260.2455790.258171
78104.3104.187103.830.3570370.112546
79104.11NANA0.187523NA
80104.17NANA0.366412NA
81104.23NANA0.283148NA
82104.47NANA0.0980787NA
83104.86NANA-0.173171NA
84104.9NANA-0.366505NA



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')