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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationTue, 16 Dec 2014 20:42:48 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/16/t14187625908lvrt8o7k7ukmvt.htm/, Retrieved Thu, 31 Oct 2024 23:12:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269942, Retrieved Thu, 31 Oct 2024 23:12:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [] [2014-12-15 21:50:17] [8ae5f3921d0f515f24933d117e773272]
- R PD    [Classical Decomposition] [] [2014-12-16 20:42:48] [77e76d07a5b02a0482982fb19d5d5436] [Current]
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Dataseries X:
21.94
21.95
21.96
22.1
22.13
22.18
22.18
22.27
22.3
22.04
22.05
22.06
22.06
22.06
21.97
22.03
22.08
22.13
22.13
22.4
22.4
22.12
22.22
22.14
22.14
22.19
22.29
22.24
22.26
22.29
22.29
22.29
22.29
22.35
22.39
22.43
22.43
22.11
22.12
22.05
22.05
22.08
22.08
22.09
22.09
22.24
22.25
22.24
22.24
22.25
22.28
22.23
22.29
22.31
22.31
22.31
22.39
22.42
22.42
22.42
22.15
21.95
21.96
21.97
21.66
21.66
21.68
21.75
21.55
21.59
21.54
21.54




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269942&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]2 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=269942&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269942&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
121.94NANA0.0161944NA
221.95NANA-0.0673056NA
321.96NANA-0.0447222NA
422.1NANA-0.0547222NA
522.13NANA-0.0827222NA
622.18NANA-0.0481389NA
722.1822.090822.1017-0.01088890.0892222
822.2722.172622.11120.06136110.0973889
922.322.199622.11620.08336110.100389
1022.0422.138222.11380.0244444-0.0981944
1122.0522.170222.10870.0614444-0.120194
1222.0622.166322.10460.0616944-0.106278
1322.0622.116622.10040.0161944-0.0566111
1422.0622.036422.1037-0.06730560.0235556
1521.9722.068622.1133-0.0447222-0.0986111
1622.0322.066122.1208-0.0547222-0.0361111
1722.0822.048522.1312-0.08272220.0314722
1822.1322.093522.1417-0.04813890.0364722
1922.1322.137422.1483-0.0108889-0.00744444
2022.422.218422.15710.06136110.181556
2122.422.259222.17580.08336110.140806
2222.1222.222422.19790.0244444-0.102361
2322.2222.275622.21420.0614444-0.0556111
2422.1422.2922.22830.0616944-0.150028
2522.1422.257922.24170.0161944-0.117861
2622.1922.176422.2438-0.06730560.0135556
2722.2922.189922.2346-0.04472220.100139
2822.2422.184922.2396-0.05472220.0551389
2922.2622.173522.2562-0.08272220.0864722
3022.2922.227322.2754-0.04813890.0627222
3122.2922.288722.2996-0.01088890.00130556
3222.2922.369722.30830.0613611-0.0796944
3322.2922.381322.29790.0833611-0.0912778
3422.3522.307422.28290.02444440.0426389
3522.3922.327722.26630.06144440.0623056
3622.4322.310422.24880.06169440.119556
3722.4322.247422.23130.01619440.182556
3822.1122.146922.2142-0.0673056-0.0368611
3922.1222.152822.1975-0.0447222-0.0327778
4022.0522.129922.1846-0.0547222-0.0798611
4122.0522.091422.1742-0.0827222-0.0414444
4222.0822.112322.1604-0.0481389-0.0322778
4322.0822.133722.1446-0.0108889-0.0536944
4422.0922.203922.14250.0613611-0.113861
4522.0922.238422.1550.0833611-0.148361
4622.2422.193622.16920.02444440.0463889
4722.2522.248122.18670.06144440.00188889
4822.2422.267922.20620.0616944-0.0279444
4922.2422.241622.22540.0161944-0.00161111
5022.2522.176922.2442-0.06730560.0731389
5122.2822.221122.2658-0.04472220.0588889
5222.2322.231122.2858-0.0547222-0.00111111
5322.2922.217722.3004-0.08272220.0723056
5422.3122.266922.315-0.04813890.0431389
5522.3122.307922.3187-0.01088890.00213889
5622.3122.363922.30250.0613611-0.0538611
5722.3922.3622.27670.08336110.0299722
5822.4222.276922.25250.02444440.143056
5922.4222.276922.21540.06144440.143139
6022.4222.223822.16210.06169440.196222
6122.1522.124922.10880.01619440.0250556
6221.9521.991922.0592-0.0673056-0.0418611
6321.9621.956122.0008-0.04472220.00388889
6421.9721.876521.9312-0.05472220.0934722
6521.6621.777321.86-0.0827222-0.117278
6621.6621.738521.7867-0.0481389-0.0785278
6721.68NANA-0.0108889NA
6821.75NANA0.0613611NA
6921.55NANA0.0833611NA
7021.59NANA0.0244444NA
7121.54NANA0.0614444NA
7221.54NANA0.0616944NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 21.94 & NA & NA & 0.0161944 & NA \tabularnewline
2 & 21.95 & NA & NA & -0.0673056 & NA \tabularnewline
3 & 21.96 & NA & NA & -0.0447222 & NA \tabularnewline
4 & 22.1 & NA & NA & -0.0547222 & NA \tabularnewline
5 & 22.13 & NA & NA & -0.0827222 & NA \tabularnewline
6 & 22.18 & NA & NA & -0.0481389 & NA \tabularnewline
7 & 22.18 & 22.0908 & 22.1017 & -0.0108889 & 0.0892222 \tabularnewline
8 & 22.27 & 22.1726 & 22.1112 & 0.0613611 & 0.0973889 \tabularnewline
9 & 22.3 & 22.1996 & 22.1162 & 0.0833611 & 0.100389 \tabularnewline
10 & 22.04 & 22.1382 & 22.1138 & 0.0244444 & -0.0981944 \tabularnewline
11 & 22.05 & 22.1702 & 22.1087 & 0.0614444 & -0.120194 \tabularnewline
12 & 22.06 & 22.1663 & 22.1046 & 0.0616944 & -0.106278 \tabularnewline
13 & 22.06 & 22.1166 & 22.1004 & 0.0161944 & -0.0566111 \tabularnewline
14 & 22.06 & 22.0364 & 22.1037 & -0.0673056 & 0.0235556 \tabularnewline
15 & 21.97 & 22.0686 & 22.1133 & -0.0447222 & -0.0986111 \tabularnewline
16 & 22.03 & 22.0661 & 22.1208 & -0.0547222 & -0.0361111 \tabularnewline
17 & 22.08 & 22.0485 & 22.1312 & -0.0827222 & 0.0314722 \tabularnewline
18 & 22.13 & 22.0935 & 22.1417 & -0.0481389 & 0.0364722 \tabularnewline
19 & 22.13 & 22.1374 & 22.1483 & -0.0108889 & -0.00744444 \tabularnewline
20 & 22.4 & 22.2184 & 22.1571 & 0.0613611 & 0.181556 \tabularnewline
21 & 22.4 & 22.2592 & 22.1758 & 0.0833611 & 0.140806 \tabularnewline
22 & 22.12 & 22.2224 & 22.1979 & 0.0244444 & -0.102361 \tabularnewline
23 & 22.22 & 22.2756 & 22.2142 & 0.0614444 & -0.0556111 \tabularnewline
24 & 22.14 & 22.29 & 22.2283 & 0.0616944 & -0.150028 \tabularnewline
25 & 22.14 & 22.2579 & 22.2417 & 0.0161944 & -0.117861 \tabularnewline
26 & 22.19 & 22.1764 & 22.2438 & -0.0673056 & 0.0135556 \tabularnewline
27 & 22.29 & 22.1899 & 22.2346 & -0.0447222 & 0.100139 \tabularnewline
28 & 22.24 & 22.1849 & 22.2396 & -0.0547222 & 0.0551389 \tabularnewline
29 & 22.26 & 22.1735 & 22.2562 & -0.0827222 & 0.0864722 \tabularnewline
30 & 22.29 & 22.2273 & 22.2754 & -0.0481389 & 0.0627222 \tabularnewline
31 & 22.29 & 22.2887 & 22.2996 & -0.0108889 & 0.00130556 \tabularnewline
32 & 22.29 & 22.3697 & 22.3083 & 0.0613611 & -0.0796944 \tabularnewline
33 & 22.29 & 22.3813 & 22.2979 & 0.0833611 & -0.0912778 \tabularnewline
34 & 22.35 & 22.3074 & 22.2829 & 0.0244444 & 0.0426389 \tabularnewline
35 & 22.39 & 22.3277 & 22.2663 & 0.0614444 & 0.0623056 \tabularnewline
36 & 22.43 & 22.3104 & 22.2488 & 0.0616944 & 0.119556 \tabularnewline
37 & 22.43 & 22.2474 & 22.2313 & 0.0161944 & 0.182556 \tabularnewline
38 & 22.11 & 22.1469 & 22.2142 & -0.0673056 & -0.0368611 \tabularnewline
39 & 22.12 & 22.1528 & 22.1975 & -0.0447222 & -0.0327778 \tabularnewline
40 & 22.05 & 22.1299 & 22.1846 & -0.0547222 & -0.0798611 \tabularnewline
41 & 22.05 & 22.0914 & 22.1742 & -0.0827222 & -0.0414444 \tabularnewline
42 & 22.08 & 22.1123 & 22.1604 & -0.0481389 & -0.0322778 \tabularnewline
43 & 22.08 & 22.1337 & 22.1446 & -0.0108889 & -0.0536944 \tabularnewline
44 & 22.09 & 22.2039 & 22.1425 & 0.0613611 & -0.113861 \tabularnewline
45 & 22.09 & 22.2384 & 22.155 & 0.0833611 & -0.148361 \tabularnewline
46 & 22.24 & 22.1936 & 22.1692 & 0.0244444 & 0.0463889 \tabularnewline
47 & 22.25 & 22.2481 & 22.1867 & 0.0614444 & 0.00188889 \tabularnewline
48 & 22.24 & 22.2679 & 22.2062 & 0.0616944 & -0.0279444 \tabularnewline
49 & 22.24 & 22.2416 & 22.2254 & 0.0161944 & -0.00161111 \tabularnewline
50 & 22.25 & 22.1769 & 22.2442 & -0.0673056 & 0.0731389 \tabularnewline
51 & 22.28 & 22.2211 & 22.2658 & -0.0447222 & 0.0588889 \tabularnewline
52 & 22.23 & 22.2311 & 22.2858 & -0.0547222 & -0.00111111 \tabularnewline
53 & 22.29 & 22.2177 & 22.3004 & -0.0827222 & 0.0723056 \tabularnewline
54 & 22.31 & 22.2669 & 22.315 & -0.0481389 & 0.0431389 \tabularnewline
55 & 22.31 & 22.3079 & 22.3187 & -0.0108889 & 0.00213889 \tabularnewline
56 & 22.31 & 22.3639 & 22.3025 & 0.0613611 & -0.0538611 \tabularnewline
57 & 22.39 & 22.36 & 22.2767 & 0.0833611 & 0.0299722 \tabularnewline
58 & 22.42 & 22.2769 & 22.2525 & 0.0244444 & 0.143056 \tabularnewline
59 & 22.42 & 22.2769 & 22.2154 & 0.0614444 & 0.143139 \tabularnewline
60 & 22.42 & 22.2238 & 22.1621 & 0.0616944 & 0.196222 \tabularnewline
61 & 22.15 & 22.1249 & 22.1088 & 0.0161944 & 0.0250556 \tabularnewline
62 & 21.95 & 21.9919 & 22.0592 & -0.0673056 & -0.0418611 \tabularnewline
63 & 21.96 & 21.9561 & 22.0008 & -0.0447222 & 0.00388889 \tabularnewline
64 & 21.97 & 21.8765 & 21.9312 & -0.0547222 & 0.0934722 \tabularnewline
65 & 21.66 & 21.7773 & 21.86 & -0.0827222 & -0.117278 \tabularnewline
66 & 21.66 & 21.7385 & 21.7867 & -0.0481389 & -0.0785278 \tabularnewline
67 & 21.68 & NA & NA & -0.0108889 & NA \tabularnewline
68 & 21.75 & NA & NA & 0.0613611 & NA \tabularnewline
69 & 21.55 & NA & NA & 0.0833611 & NA \tabularnewline
70 & 21.59 & NA & NA & 0.0244444 & NA \tabularnewline
71 & 21.54 & NA & NA & 0.0614444 & NA \tabularnewline
72 & 21.54 & NA & NA & 0.0616944 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269942&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]21.94[/C][C]NA[/C][C]NA[/C][C]0.0161944[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]21.95[/C][C]NA[/C][C]NA[/C][C]-0.0673056[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]21.96[/C][C]NA[/C][C]NA[/C][C]-0.0447222[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]22.1[/C][C]NA[/C][C]NA[/C][C]-0.0547222[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]22.13[/C][C]NA[/C][C]NA[/C][C]-0.0827222[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]22.18[/C][C]NA[/C][C]NA[/C][C]-0.0481389[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]22.18[/C][C]22.0908[/C][C]22.1017[/C][C]-0.0108889[/C][C]0.0892222[/C][/ROW]
[ROW][C]8[/C][C]22.27[/C][C]22.1726[/C][C]22.1112[/C][C]0.0613611[/C][C]0.0973889[/C][/ROW]
[ROW][C]9[/C][C]22.3[/C][C]22.1996[/C][C]22.1162[/C][C]0.0833611[/C][C]0.100389[/C][/ROW]
[ROW][C]10[/C][C]22.04[/C][C]22.1382[/C][C]22.1138[/C][C]0.0244444[/C][C]-0.0981944[/C][/ROW]
[ROW][C]11[/C][C]22.05[/C][C]22.1702[/C][C]22.1087[/C][C]0.0614444[/C][C]-0.120194[/C][/ROW]
[ROW][C]12[/C][C]22.06[/C][C]22.1663[/C][C]22.1046[/C][C]0.0616944[/C][C]-0.106278[/C][/ROW]
[ROW][C]13[/C][C]22.06[/C][C]22.1166[/C][C]22.1004[/C][C]0.0161944[/C][C]-0.0566111[/C][/ROW]
[ROW][C]14[/C][C]22.06[/C][C]22.0364[/C][C]22.1037[/C][C]-0.0673056[/C][C]0.0235556[/C][/ROW]
[ROW][C]15[/C][C]21.97[/C][C]22.0686[/C][C]22.1133[/C][C]-0.0447222[/C][C]-0.0986111[/C][/ROW]
[ROW][C]16[/C][C]22.03[/C][C]22.0661[/C][C]22.1208[/C][C]-0.0547222[/C][C]-0.0361111[/C][/ROW]
[ROW][C]17[/C][C]22.08[/C][C]22.0485[/C][C]22.1312[/C][C]-0.0827222[/C][C]0.0314722[/C][/ROW]
[ROW][C]18[/C][C]22.13[/C][C]22.0935[/C][C]22.1417[/C][C]-0.0481389[/C][C]0.0364722[/C][/ROW]
[ROW][C]19[/C][C]22.13[/C][C]22.1374[/C][C]22.1483[/C][C]-0.0108889[/C][C]-0.00744444[/C][/ROW]
[ROW][C]20[/C][C]22.4[/C][C]22.2184[/C][C]22.1571[/C][C]0.0613611[/C][C]0.181556[/C][/ROW]
[ROW][C]21[/C][C]22.4[/C][C]22.2592[/C][C]22.1758[/C][C]0.0833611[/C][C]0.140806[/C][/ROW]
[ROW][C]22[/C][C]22.12[/C][C]22.2224[/C][C]22.1979[/C][C]0.0244444[/C][C]-0.102361[/C][/ROW]
[ROW][C]23[/C][C]22.22[/C][C]22.2756[/C][C]22.2142[/C][C]0.0614444[/C][C]-0.0556111[/C][/ROW]
[ROW][C]24[/C][C]22.14[/C][C]22.29[/C][C]22.2283[/C][C]0.0616944[/C][C]-0.150028[/C][/ROW]
[ROW][C]25[/C][C]22.14[/C][C]22.2579[/C][C]22.2417[/C][C]0.0161944[/C][C]-0.117861[/C][/ROW]
[ROW][C]26[/C][C]22.19[/C][C]22.1764[/C][C]22.2438[/C][C]-0.0673056[/C][C]0.0135556[/C][/ROW]
[ROW][C]27[/C][C]22.29[/C][C]22.1899[/C][C]22.2346[/C][C]-0.0447222[/C][C]0.100139[/C][/ROW]
[ROW][C]28[/C][C]22.24[/C][C]22.1849[/C][C]22.2396[/C][C]-0.0547222[/C][C]0.0551389[/C][/ROW]
[ROW][C]29[/C][C]22.26[/C][C]22.1735[/C][C]22.2562[/C][C]-0.0827222[/C][C]0.0864722[/C][/ROW]
[ROW][C]30[/C][C]22.29[/C][C]22.2273[/C][C]22.2754[/C][C]-0.0481389[/C][C]0.0627222[/C][/ROW]
[ROW][C]31[/C][C]22.29[/C][C]22.2887[/C][C]22.2996[/C][C]-0.0108889[/C][C]0.00130556[/C][/ROW]
[ROW][C]32[/C][C]22.29[/C][C]22.3697[/C][C]22.3083[/C][C]0.0613611[/C][C]-0.0796944[/C][/ROW]
[ROW][C]33[/C][C]22.29[/C][C]22.3813[/C][C]22.2979[/C][C]0.0833611[/C][C]-0.0912778[/C][/ROW]
[ROW][C]34[/C][C]22.35[/C][C]22.3074[/C][C]22.2829[/C][C]0.0244444[/C][C]0.0426389[/C][/ROW]
[ROW][C]35[/C][C]22.39[/C][C]22.3277[/C][C]22.2663[/C][C]0.0614444[/C][C]0.0623056[/C][/ROW]
[ROW][C]36[/C][C]22.43[/C][C]22.3104[/C][C]22.2488[/C][C]0.0616944[/C][C]0.119556[/C][/ROW]
[ROW][C]37[/C][C]22.43[/C][C]22.2474[/C][C]22.2313[/C][C]0.0161944[/C][C]0.182556[/C][/ROW]
[ROW][C]38[/C][C]22.11[/C][C]22.1469[/C][C]22.2142[/C][C]-0.0673056[/C][C]-0.0368611[/C][/ROW]
[ROW][C]39[/C][C]22.12[/C][C]22.1528[/C][C]22.1975[/C][C]-0.0447222[/C][C]-0.0327778[/C][/ROW]
[ROW][C]40[/C][C]22.05[/C][C]22.1299[/C][C]22.1846[/C][C]-0.0547222[/C][C]-0.0798611[/C][/ROW]
[ROW][C]41[/C][C]22.05[/C][C]22.0914[/C][C]22.1742[/C][C]-0.0827222[/C][C]-0.0414444[/C][/ROW]
[ROW][C]42[/C][C]22.08[/C][C]22.1123[/C][C]22.1604[/C][C]-0.0481389[/C][C]-0.0322778[/C][/ROW]
[ROW][C]43[/C][C]22.08[/C][C]22.1337[/C][C]22.1446[/C][C]-0.0108889[/C][C]-0.0536944[/C][/ROW]
[ROW][C]44[/C][C]22.09[/C][C]22.2039[/C][C]22.1425[/C][C]0.0613611[/C][C]-0.113861[/C][/ROW]
[ROW][C]45[/C][C]22.09[/C][C]22.2384[/C][C]22.155[/C][C]0.0833611[/C][C]-0.148361[/C][/ROW]
[ROW][C]46[/C][C]22.24[/C][C]22.1936[/C][C]22.1692[/C][C]0.0244444[/C][C]0.0463889[/C][/ROW]
[ROW][C]47[/C][C]22.25[/C][C]22.2481[/C][C]22.1867[/C][C]0.0614444[/C][C]0.00188889[/C][/ROW]
[ROW][C]48[/C][C]22.24[/C][C]22.2679[/C][C]22.2062[/C][C]0.0616944[/C][C]-0.0279444[/C][/ROW]
[ROW][C]49[/C][C]22.24[/C][C]22.2416[/C][C]22.2254[/C][C]0.0161944[/C][C]-0.00161111[/C][/ROW]
[ROW][C]50[/C][C]22.25[/C][C]22.1769[/C][C]22.2442[/C][C]-0.0673056[/C][C]0.0731389[/C][/ROW]
[ROW][C]51[/C][C]22.28[/C][C]22.2211[/C][C]22.2658[/C][C]-0.0447222[/C][C]0.0588889[/C][/ROW]
[ROW][C]52[/C][C]22.23[/C][C]22.2311[/C][C]22.2858[/C][C]-0.0547222[/C][C]-0.00111111[/C][/ROW]
[ROW][C]53[/C][C]22.29[/C][C]22.2177[/C][C]22.3004[/C][C]-0.0827222[/C][C]0.0723056[/C][/ROW]
[ROW][C]54[/C][C]22.31[/C][C]22.2669[/C][C]22.315[/C][C]-0.0481389[/C][C]0.0431389[/C][/ROW]
[ROW][C]55[/C][C]22.31[/C][C]22.3079[/C][C]22.3187[/C][C]-0.0108889[/C][C]0.00213889[/C][/ROW]
[ROW][C]56[/C][C]22.31[/C][C]22.3639[/C][C]22.3025[/C][C]0.0613611[/C][C]-0.0538611[/C][/ROW]
[ROW][C]57[/C][C]22.39[/C][C]22.36[/C][C]22.2767[/C][C]0.0833611[/C][C]0.0299722[/C][/ROW]
[ROW][C]58[/C][C]22.42[/C][C]22.2769[/C][C]22.2525[/C][C]0.0244444[/C][C]0.143056[/C][/ROW]
[ROW][C]59[/C][C]22.42[/C][C]22.2769[/C][C]22.2154[/C][C]0.0614444[/C][C]0.143139[/C][/ROW]
[ROW][C]60[/C][C]22.42[/C][C]22.2238[/C][C]22.1621[/C][C]0.0616944[/C][C]0.196222[/C][/ROW]
[ROW][C]61[/C][C]22.15[/C][C]22.1249[/C][C]22.1088[/C][C]0.0161944[/C][C]0.0250556[/C][/ROW]
[ROW][C]62[/C][C]21.95[/C][C]21.9919[/C][C]22.0592[/C][C]-0.0673056[/C][C]-0.0418611[/C][/ROW]
[ROW][C]63[/C][C]21.96[/C][C]21.9561[/C][C]22.0008[/C][C]-0.0447222[/C][C]0.00388889[/C][/ROW]
[ROW][C]64[/C][C]21.97[/C][C]21.8765[/C][C]21.9312[/C][C]-0.0547222[/C][C]0.0934722[/C][/ROW]
[ROW][C]65[/C][C]21.66[/C][C]21.7773[/C][C]21.86[/C][C]-0.0827222[/C][C]-0.117278[/C][/ROW]
[ROW][C]66[/C][C]21.66[/C][C]21.7385[/C][C]21.7867[/C][C]-0.0481389[/C][C]-0.0785278[/C][/ROW]
[ROW][C]67[/C][C]21.68[/C][C]NA[/C][C]NA[/C][C]-0.0108889[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]21.75[/C][C]NA[/C][C]NA[/C][C]0.0613611[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]21.55[/C][C]NA[/C][C]NA[/C][C]0.0833611[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]21.59[/C][C]NA[/C][C]NA[/C][C]0.0244444[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]21.54[/C][C]NA[/C][C]NA[/C][C]0.0614444[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]21.54[/C][C]NA[/C][C]NA[/C][C]0.0616944[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269942&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269942&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
121.94NANA0.0161944NA
221.95NANA-0.0673056NA
321.96NANA-0.0447222NA
422.1NANA-0.0547222NA
522.13NANA-0.0827222NA
622.18NANA-0.0481389NA
722.1822.090822.1017-0.01088890.0892222
822.2722.172622.11120.06136110.0973889
922.322.199622.11620.08336110.100389
1022.0422.138222.11380.0244444-0.0981944
1122.0522.170222.10870.0614444-0.120194
1222.0622.166322.10460.0616944-0.106278
1322.0622.116622.10040.0161944-0.0566111
1422.0622.036422.1037-0.06730560.0235556
1521.9722.068622.1133-0.0447222-0.0986111
1622.0322.066122.1208-0.0547222-0.0361111
1722.0822.048522.1312-0.08272220.0314722
1822.1322.093522.1417-0.04813890.0364722
1922.1322.137422.1483-0.0108889-0.00744444
2022.422.218422.15710.06136110.181556
2122.422.259222.17580.08336110.140806
2222.1222.222422.19790.0244444-0.102361
2322.2222.275622.21420.0614444-0.0556111
2422.1422.2922.22830.0616944-0.150028
2522.1422.257922.24170.0161944-0.117861
2622.1922.176422.2438-0.06730560.0135556
2722.2922.189922.2346-0.04472220.100139
2822.2422.184922.2396-0.05472220.0551389
2922.2622.173522.2562-0.08272220.0864722
3022.2922.227322.2754-0.04813890.0627222
3122.2922.288722.2996-0.01088890.00130556
3222.2922.369722.30830.0613611-0.0796944
3322.2922.381322.29790.0833611-0.0912778
3422.3522.307422.28290.02444440.0426389
3522.3922.327722.26630.06144440.0623056
3622.4322.310422.24880.06169440.119556
3722.4322.247422.23130.01619440.182556
3822.1122.146922.2142-0.0673056-0.0368611
3922.1222.152822.1975-0.0447222-0.0327778
4022.0522.129922.1846-0.0547222-0.0798611
4122.0522.091422.1742-0.0827222-0.0414444
4222.0822.112322.1604-0.0481389-0.0322778
4322.0822.133722.1446-0.0108889-0.0536944
4422.0922.203922.14250.0613611-0.113861
4522.0922.238422.1550.0833611-0.148361
4622.2422.193622.16920.02444440.0463889
4722.2522.248122.18670.06144440.00188889
4822.2422.267922.20620.0616944-0.0279444
4922.2422.241622.22540.0161944-0.00161111
5022.2522.176922.2442-0.06730560.0731389
5122.2822.221122.2658-0.04472220.0588889
5222.2322.231122.2858-0.0547222-0.00111111
5322.2922.217722.3004-0.08272220.0723056
5422.3122.266922.315-0.04813890.0431389
5522.3122.307922.3187-0.01088890.00213889
5622.3122.363922.30250.0613611-0.0538611
5722.3922.3622.27670.08336110.0299722
5822.4222.276922.25250.02444440.143056
5922.4222.276922.21540.06144440.143139
6022.4222.223822.16210.06169440.196222
6122.1522.124922.10880.01619440.0250556
6221.9521.991922.0592-0.0673056-0.0418611
6321.9621.956122.0008-0.04472220.00388889
6421.9721.876521.9312-0.05472220.0934722
6521.6621.777321.86-0.0827222-0.117278
6621.6621.738521.7867-0.0481389-0.0785278
6721.68NANA-0.0108889NA
6821.75NANA0.0613611NA
6921.55NANA0.0833611NA
7021.59NANA0.0244444NA
7121.54NANA0.0614444NA
7221.54NANA0.0616944NA



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')