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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 27 Nov 2014 21:26:36 +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/Nov/27/t1417123824mime2cpwnqu12t3.htm/, Retrieved Fri, 17 May 2024 04:45:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=260693, Retrieved Fri, 17 May 2024 04:45:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2014-11-27 21:26:36] [bdd4dd5e616b71837cf1c04213e8fe07] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
204,12
203,27
203,73
203,7
203,44
203,34
203,34
203,05
202,71
202,51
203,45
203,04
203,04
202,87
202,92
202,87
203,17
203,88
203,88
203,45
203,22
202,11
202,5
202,86
202,86
203,8
203,78
204,53
204,44
204,14
204,14
204,04
204,68
205,01
204,93
204,34
204,34
203,87
202,47
201,95
201,86
200,33
200,33
200,33
200,75
201,86
202,77
202,85
202,85
202,84
202,94
203,05
203,45
204,19
204,18
204,47
204,78
206,05
206,32
206,36
205,21
205,35
205,94
204,57
204,27
204,86
204,66
204,79
205,58
205,63
205,12
204,96

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260693&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260693&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260693&T=0

As an alternative you can also use a QR Code:  
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'Gertrude Mary Cox' @ cox.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1204.12NANA0.149931NA
2203.27NANA0.210431NA
3203.73NANA0.0360139NA
4203.7NANA-0.229903NA
5203.44NANA-0.225819NA
6203.34NANA-0.213736NA
7203.34203.073203.263-0.1908190.267486
8203.05202.878203.202-0.3232360.171569
9202.71202.952203.151-0.198986-0.242264
10202.51203.138203.0830.0553472-0.628264
11203.45203.564203.0370.527181-0.114264
12203.04203.452203.0480.403597-0.411931
13203.04203.243203.0930.149931-0.203264
14202.87203.343203.1320.210431-0.472931
15202.92203.206203.170.0360139-0.286431
16202.87202.945203.175-0.229903-0.0750972
17203.17202.893203.119-0.2258190.277069
18203.88202.858203.072-0.2137361.02207
19203.88202.866203.057-0.1908191.01415
20203.45202.765203.088-0.3232360.685319
21203.22202.964203.163-0.1989860.256486
22202.11203.323203.2680.0553472-1.21285
23202.5203.917203.390.527181-1.41676
24202.86203.857203.4530.403597-0.996931
25202.86203.625203.4750.149931-0.764931
26203.8203.721203.510.2104310.0791528
27203.78203.632203.5960.03601390.148153
28204.53203.548203.777-0.2299030.982403
29204.44203.774204-0.2258190.666236
30204.14203.949204.162-0.2137360.191236
31204.14204.095204.286-0.1908190.0449861
32204.04204.027204.35-0.3232360.0128194
33204.68204.1204.299-0.1989860.580236
34205.01204.192204.1370.05534720.817986
35204.93204.449203.9220.5271810.481153
36204.34204.059203.6550.4035970.280986
37204.34203.488203.3380.1499310.852153
38203.87203.235203.0250.2104310.634986
39202.47202.742202.7060.0360139-0.272264
40201.95202.181202.411-0.229903-0.231347
41201.86201.964202.19-0.225819-0.104181
42200.33201.824202.038-0.213736-1.49418
43200.33201.723201.914-0.190819-1.39293
44200.33201.486201.809-0.323236-1.15551
45200.75201.586201.785-0.198986-0.836431
46201.86201.906201.8510.0553472-0.0461806
47202.77202.49201.9630.5271810.279903
48202.85202.594202.190.4035970.256403
49202.85202.661202.5110.1499310.188819
50202.84203.055202.8440.210431-0.214597
51202.94203.221203.1850.0360139-0.280597
52203.05203.297203.527-0.229903-0.247181
53203.45203.624203.85-0.225819-0.173764
54204.19203.93204.144-0.2137360.259986
55204.18204.198204.388-0.190819-0.0175139
56204.47204.268204.591-0.3232360.201986
57204.78204.622204.821-0.1989860.158153
58206.05205.065205.0090.05534720.985486
59206.32205.634205.1070.5271810.686153
60206.36205.572205.1690.4035970.787653
61205.21205.367205.2170.149931-0.156597
62205.35205.46205.250.210431-0.110431
63205.94205.333205.2970.03601390.607319
64204.57205.083205.312-0.229903-0.512597
65204.27205.019205.245-0.225819-0.749181
66204.86204.923205.137-0.213736-0.0629306
67204.66NANA-0.190819NA
68204.79NANA-0.323236NA
69205.58NANA-0.198986NA
70205.63NANA0.0553472NA
71205.12NANA0.527181NA
72204.96NANA0.403597NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 204.12 & NA & NA & 0.149931 & NA \tabularnewline
2 & 203.27 & NA & NA & 0.210431 & NA \tabularnewline
3 & 203.73 & NA & NA & 0.0360139 & NA \tabularnewline
4 & 203.7 & NA & NA & -0.229903 & NA \tabularnewline
5 & 203.44 & NA & NA & -0.225819 & NA \tabularnewline
6 & 203.34 & NA & NA & -0.213736 & NA \tabularnewline
7 & 203.34 & 203.073 & 203.263 & -0.190819 & 0.267486 \tabularnewline
8 & 203.05 & 202.878 & 203.202 & -0.323236 & 0.171569 \tabularnewline
9 & 202.71 & 202.952 & 203.151 & -0.198986 & -0.242264 \tabularnewline
10 & 202.51 & 203.138 & 203.083 & 0.0553472 & -0.628264 \tabularnewline
11 & 203.45 & 203.564 & 203.037 & 0.527181 & -0.114264 \tabularnewline
12 & 203.04 & 203.452 & 203.048 & 0.403597 & -0.411931 \tabularnewline
13 & 203.04 & 203.243 & 203.093 & 0.149931 & -0.203264 \tabularnewline
14 & 202.87 & 203.343 & 203.132 & 0.210431 & -0.472931 \tabularnewline
15 & 202.92 & 203.206 & 203.17 & 0.0360139 & -0.286431 \tabularnewline
16 & 202.87 & 202.945 & 203.175 & -0.229903 & -0.0750972 \tabularnewline
17 & 203.17 & 202.893 & 203.119 & -0.225819 & 0.277069 \tabularnewline
18 & 203.88 & 202.858 & 203.072 & -0.213736 & 1.02207 \tabularnewline
19 & 203.88 & 202.866 & 203.057 & -0.190819 & 1.01415 \tabularnewline
20 & 203.45 & 202.765 & 203.088 & -0.323236 & 0.685319 \tabularnewline
21 & 203.22 & 202.964 & 203.163 & -0.198986 & 0.256486 \tabularnewline
22 & 202.11 & 203.323 & 203.268 & 0.0553472 & -1.21285 \tabularnewline
23 & 202.5 & 203.917 & 203.39 & 0.527181 & -1.41676 \tabularnewline
24 & 202.86 & 203.857 & 203.453 & 0.403597 & -0.996931 \tabularnewline
25 & 202.86 & 203.625 & 203.475 & 0.149931 & -0.764931 \tabularnewline
26 & 203.8 & 203.721 & 203.51 & 0.210431 & 0.0791528 \tabularnewline
27 & 203.78 & 203.632 & 203.596 & 0.0360139 & 0.148153 \tabularnewline
28 & 204.53 & 203.548 & 203.777 & -0.229903 & 0.982403 \tabularnewline
29 & 204.44 & 203.774 & 204 & -0.225819 & 0.666236 \tabularnewline
30 & 204.14 & 203.949 & 204.162 & -0.213736 & 0.191236 \tabularnewline
31 & 204.14 & 204.095 & 204.286 & -0.190819 & 0.0449861 \tabularnewline
32 & 204.04 & 204.027 & 204.35 & -0.323236 & 0.0128194 \tabularnewline
33 & 204.68 & 204.1 & 204.299 & -0.198986 & 0.580236 \tabularnewline
34 & 205.01 & 204.192 & 204.137 & 0.0553472 & 0.817986 \tabularnewline
35 & 204.93 & 204.449 & 203.922 & 0.527181 & 0.481153 \tabularnewline
36 & 204.34 & 204.059 & 203.655 & 0.403597 & 0.280986 \tabularnewline
37 & 204.34 & 203.488 & 203.338 & 0.149931 & 0.852153 \tabularnewline
38 & 203.87 & 203.235 & 203.025 & 0.210431 & 0.634986 \tabularnewline
39 & 202.47 & 202.742 & 202.706 & 0.0360139 & -0.272264 \tabularnewline
40 & 201.95 & 202.181 & 202.411 & -0.229903 & -0.231347 \tabularnewline
41 & 201.86 & 201.964 & 202.19 & -0.225819 & -0.104181 \tabularnewline
42 & 200.33 & 201.824 & 202.038 & -0.213736 & -1.49418 \tabularnewline
43 & 200.33 & 201.723 & 201.914 & -0.190819 & -1.39293 \tabularnewline
44 & 200.33 & 201.486 & 201.809 & -0.323236 & -1.15551 \tabularnewline
45 & 200.75 & 201.586 & 201.785 & -0.198986 & -0.836431 \tabularnewline
46 & 201.86 & 201.906 & 201.851 & 0.0553472 & -0.0461806 \tabularnewline
47 & 202.77 & 202.49 & 201.963 & 0.527181 & 0.279903 \tabularnewline
48 & 202.85 & 202.594 & 202.19 & 0.403597 & 0.256403 \tabularnewline
49 & 202.85 & 202.661 & 202.511 & 0.149931 & 0.188819 \tabularnewline
50 & 202.84 & 203.055 & 202.844 & 0.210431 & -0.214597 \tabularnewline
51 & 202.94 & 203.221 & 203.185 & 0.0360139 & -0.280597 \tabularnewline
52 & 203.05 & 203.297 & 203.527 & -0.229903 & -0.247181 \tabularnewline
53 & 203.45 & 203.624 & 203.85 & -0.225819 & -0.173764 \tabularnewline
54 & 204.19 & 203.93 & 204.144 & -0.213736 & 0.259986 \tabularnewline
55 & 204.18 & 204.198 & 204.388 & -0.190819 & -0.0175139 \tabularnewline
56 & 204.47 & 204.268 & 204.591 & -0.323236 & 0.201986 \tabularnewline
57 & 204.78 & 204.622 & 204.821 & -0.198986 & 0.158153 \tabularnewline
58 & 206.05 & 205.065 & 205.009 & 0.0553472 & 0.985486 \tabularnewline
59 & 206.32 & 205.634 & 205.107 & 0.527181 & 0.686153 \tabularnewline
60 & 206.36 & 205.572 & 205.169 & 0.403597 & 0.787653 \tabularnewline
61 & 205.21 & 205.367 & 205.217 & 0.149931 & -0.156597 \tabularnewline
62 & 205.35 & 205.46 & 205.25 & 0.210431 & -0.110431 \tabularnewline
63 & 205.94 & 205.333 & 205.297 & 0.0360139 & 0.607319 \tabularnewline
64 & 204.57 & 205.083 & 205.312 & -0.229903 & -0.512597 \tabularnewline
65 & 204.27 & 205.019 & 205.245 & -0.225819 & -0.749181 \tabularnewline
66 & 204.86 & 204.923 & 205.137 & -0.213736 & -0.0629306 \tabularnewline
67 & 204.66 & NA & NA & -0.190819 & NA \tabularnewline
68 & 204.79 & NA & NA & -0.323236 & NA \tabularnewline
69 & 205.58 & NA & NA & -0.198986 & NA \tabularnewline
70 & 205.63 & NA & NA & 0.0553472 & NA \tabularnewline
71 & 205.12 & NA & NA & 0.527181 & NA \tabularnewline
72 & 204.96 & NA & NA & 0.403597 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260693&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]204.12[/C][C]NA[/C][C]NA[/C][C]0.149931[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]203.27[/C][C]NA[/C][C]NA[/C][C]0.210431[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]203.73[/C][C]NA[/C][C]NA[/C][C]0.0360139[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]203.7[/C][C]NA[/C][C]NA[/C][C]-0.229903[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]203.44[/C][C]NA[/C][C]NA[/C][C]-0.225819[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]203.34[/C][C]NA[/C][C]NA[/C][C]-0.213736[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]203.34[/C][C]203.073[/C][C]203.263[/C][C]-0.190819[/C][C]0.267486[/C][/ROW]
[ROW][C]8[/C][C]203.05[/C][C]202.878[/C][C]203.202[/C][C]-0.323236[/C][C]0.171569[/C][/ROW]
[ROW][C]9[/C][C]202.71[/C][C]202.952[/C][C]203.151[/C][C]-0.198986[/C][C]-0.242264[/C][/ROW]
[ROW][C]10[/C][C]202.51[/C][C]203.138[/C][C]203.083[/C][C]0.0553472[/C][C]-0.628264[/C][/ROW]
[ROW][C]11[/C][C]203.45[/C][C]203.564[/C][C]203.037[/C][C]0.527181[/C][C]-0.114264[/C][/ROW]
[ROW][C]12[/C][C]203.04[/C][C]203.452[/C][C]203.048[/C][C]0.403597[/C][C]-0.411931[/C][/ROW]
[ROW][C]13[/C][C]203.04[/C][C]203.243[/C][C]203.093[/C][C]0.149931[/C][C]-0.203264[/C][/ROW]
[ROW][C]14[/C][C]202.87[/C][C]203.343[/C][C]203.132[/C][C]0.210431[/C][C]-0.472931[/C][/ROW]
[ROW][C]15[/C][C]202.92[/C][C]203.206[/C][C]203.17[/C][C]0.0360139[/C][C]-0.286431[/C][/ROW]
[ROW][C]16[/C][C]202.87[/C][C]202.945[/C][C]203.175[/C][C]-0.229903[/C][C]-0.0750972[/C][/ROW]
[ROW][C]17[/C][C]203.17[/C][C]202.893[/C][C]203.119[/C][C]-0.225819[/C][C]0.277069[/C][/ROW]
[ROW][C]18[/C][C]203.88[/C][C]202.858[/C][C]203.072[/C][C]-0.213736[/C][C]1.02207[/C][/ROW]
[ROW][C]19[/C][C]203.88[/C][C]202.866[/C][C]203.057[/C][C]-0.190819[/C][C]1.01415[/C][/ROW]
[ROW][C]20[/C][C]203.45[/C][C]202.765[/C][C]203.088[/C][C]-0.323236[/C][C]0.685319[/C][/ROW]
[ROW][C]21[/C][C]203.22[/C][C]202.964[/C][C]203.163[/C][C]-0.198986[/C][C]0.256486[/C][/ROW]
[ROW][C]22[/C][C]202.11[/C][C]203.323[/C][C]203.268[/C][C]0.0553472[/C][C]-1.21285[/C][/ROW]
[ROW][C]23[/C][C]202.5[/C][C]203.917[/C][C]203.39[/C][C]0.527181[/C][C]-1.41676[/C][/ROW]
[ROW][C]24[/C][C]202.86[/C][C]203.857[/C][C]203.453[/C][C]0.403597[/C][C]-0.996931[/C][/ROW]
[ROW][C]25[/C][C]202.86[/C][C]203.625[/C][C]203.475[/C][C]0.149931[/C][C]-0.764931[/C][/ROW]
[ROW][C]26[/C][C]203.8[/C][C]203.721[/C][C]203.51[/C][C]0.210431[/C][C]0.0791528[/C][/ROW]
[ROW][C]27[/C][C]203.78[/C][C]203.632[/C][C]203.596[/C][C]0.0360139[/C][C]0.148153[/C][/ROW]
[ROW][C]28[/C][C]204.53[/C][C]203.548[/C][C]203.777[/C][C]-0.229903[/C][C]0.982403[/C][/ROW]
[ROW][C]29[/C][C]204.44[/C][C]203.774[/C][C]204[/C][C]-0.225819[/C][C]0.666236[/C][/ROW]
[ROW][C]30[/C][C]204.14[/C][C]203.949[/C][C]204.162[/C][C]-0.213736[/C][C]0.191236[/C][/ROW]
[ROW][C]31[/C][C]204.14[/C][C]204.095[/C][C]204.286[/C][C]-0.190819[/C][C]0.0449861[/C][/ROW]
[ROW][C]32[/C][C]204.04[/C][C]204.027[/C][C]204.35[/C][C]-0.323236[/C][C]0.0128194[/C][/ROW]
[ROW][C]33[/C][C]204.68[/C][C]204.1[/C][C]204.299[/C][C]-0.198986[/C][C]0.580236[/C][/ROW]
[ROW][C]34[/C][C]205.01[/C][C]204.192[/C][C]204.137[/C][C]0.0553472[/C][C]0.817986[/C][/ROW]
[ROW][C]35[/C][C]204.93[/C][C]204.449[/C][C]203.922[/C][C]0.527181[/C][C]0.481153[/C][/ROW]
[ROW][C]36[/C][C]204.34[/C][C]204.059[/C][C]203.655[/C][C]0.403597[/C][C]0.280986[/C][/ROW]
[ROW][C]37[/C][C]204.34[/C][C]203.488[/C][C]203.338[/C][C]0.149931[/C][C]0.852153[/C][/ROW]
[ROW][C]38[/C][C]203.87[/C][C]203.235[/C][C]203.025[/C][C]0.210431[/C][C]0.634986[/C][/ROW]
[ROW][C]39[/C][C]202.47[/C][C]202.742[/C][C]202.706[/C][C]0.0360139[/C][C]-0.272264[/C][/ROW]
[ROW][C]40[/C][C]201.95[/C][C]202.181[/C][C]202.411[/C][C]-0.229903[/C][C]-0.231347[/C][/ROW]
[ROW][C]41[/C][C]201.86[/C][C]201.964[/C][C]202.19[/C][C]-0.225819[/C][C]-0.104181[/C][/ROW]
[ROW][C]42[/C][C]200.33[/C][C]201.824[/C][C]202.038[/C][C]-0.213736[/C][C]-1.49418[/C][/ROW]
[ROW][C]43[/C][C]200.33[/C][C]201.723[/C][C]201.914[/C][C]-0.190819[/C][C]-1.39293[/C][/ROW]
[ROW][C]44[/C][C]200.33[/C][C]201.486[/C][C]201.809[/C][C]-0.323236[/C][C]-1.15551[/C][/ROW]
[ROW][C]45[/C][C]200.75[/C][C]201.586[/C][C]201.785[/C][C]-0.198986[/C][C]-0.836431[/C][/ROW]
[ROW][C]46[/C][C]201.86[/C][C]201.906[/C][C]201.851[/C][C]0.0553472[/C][C]-0.0461806[/C][/ROW]
[ROW][C]47[/C][C]202.77[/C][C]202.49[/C][C]201.963[/C][C]0.527181[/C][C]0.279903[/C][/ROW]
[ROW][C]48[/C][C]202.85[/C][C]202.594[/C][C]202.19[/C][C]0.403597[/C][C]0.256403[/C][/ROW]
[ROW][C]49[/C][C]202.85[/C][C]202.661[/C][C]202.511[/C][C]0.149931[/C][C]0.188819[/C][/ROW]
[ROW][C]50[/C][C]202.84[/C][C]203.055[/C][C]202.844[/C][C]0.210431[/C][C]-0.214597[/C][/ROW]
[ROW][C]51[/C][C]202.94[/C][C]203.221[/C][C]203.185[/C][C]0.0360139[/C][C]-0.280597[/C][/ROW]
[ROW][C]52[/C][C]203.05[/C][C]203.297[/C][C]203.527[/C][C]-0.229903[/C][C]-0.247181[/C][/ROW]
[ROW][C]53[/C][C]203.45[/C][C]203.624[/C][C]203.85[/C][C]-0.225819[/C][C]-0.173764[/C][/ROW]
[ROW][C]54[/C][C]204.19[/C][C]203.93[/C][C]204.144[/C][C]-0.213736[/C][C]0.259986[/C][/ROW]
[ROW][C]55[/C][C]204.18[/C][C]204.198[/C][C]204.388[/C][C]-0.190819[/C][C]-0.0175139[/C][/ROW]
[ROW][C]56[/C][C]204.47[/C][C]204.268[/C][C]204.591[/C][C]-0.323236[/C][C]0.201986[/C][/ROW]
[ROW][C]57[/C][C]204.78[/C][C]204.622[/C][C]204.821[/C][C]-0.198986[/C][C]0.158153[/C][/ROW]
[ROW][C]58[/C][C]206.05[/C][C]205.065[/C][C]205.009[/C][C]0.0553472[/C][C]0.985486[/C][/ROW]
[ROW][C]59[/C][C]206.32[/C][C]205.634[/C][C]205.107[/C][C]0.527181[/C][C]0.686153[/C][/ROW]
[ROW][C]60[/C][C]206.36[/C][C]205.572[/C][C]205.169[/C][C]0.403597[/C][C]0.787653[/C][/ROW]
[ROW][C]61[/C][C]205.21[/C][C]205.367[/C][C]205.217[/C][C]0.149931[/C][C]-0.156597[/C][/ROW]
[ROW][C]62[/C][C]205.35[/C][C]205.46[/C][C]205.25[/C][C]0.210431[/C][C]-0.110431[/C][/ROW]
[ROW][C]63[/C][C]205.94[/C][C]205.333[/C][C]205.297[/C][C]0.0360139[/C][C]0.607319[/C][/ROW]
[ROW][C]64[/C][C]204.57[/C][C]205.083[/C][C]205.312[/C][C]-0.229903[/C][C]-0.512597[/C][/ROW]
[ROW][C]65[/C][C]204.27[/C][C]205.019[/C][C]205.245[/C][C]-0.225819[/C][C]-0.749181[/C][/ROW]
[ROW][C]66[/C][C]204.86[/C][C]204.923[/C][C]205.137[/C][C]-0.213736[/C][C]-0.0629306[/C][/ROW]
[ROW][C]67[/C][C]204.66[/C][C]NA[/C][C]NA[/C][C]-0.190819[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]204.79[/C][C]NA[/C][C]NA[/C][C]-0.323236[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]205.58[/C][C]NA[/C][C]NA[/C][C]-0.198986[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]205.63[/C][C]NA[/C][C]NA[/C][C]0.0553472[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]205.12[/C][C]NA[/C][C]NA[/C][C]0.527181[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]204.96[/C][C]NA[/C][C]NA[/C][C]0.403597[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260693&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260693&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1204.12NANA0.149931NA
2203.27NANA0.210431NA
3203.73NANA0.0360139NA
4203.7NANA-0.229903NA
5203.44NANA-0.225819NA
6203.34NANA-0.213736NA
7203.34203.073203.263-0.1908190.267486
8203.05202.878203.202-0.3232360.171569
9202.71202.952203.151-0.198986-0.242264
10202.51203.138203.0830.0553472-0.628264
11203.45203.564203.0370.527181-0.114264
12203.04203.452203.0480.403597-0.411931
13203.04203.243203.0930.149931-0.203264
14202.87203.343203.1320.210431-0.472931
15202.92203.206203.170.0360139-0.286431
16202.87202.945203.175-0.229903-0.0750972
17203.17202.893203.119-0.2258190.277069
18203.88202.858203.072-0.2137361.02207
19203.88202.866203.057-0.1908191.01415
20203.45202.765203.088-0.3232360.685319
21203.22202.964203.163-0.1989860.256486
22202.11203.323203.2680.0553472-1.21285
23202.5203.917203.390.527181-1.41676
24202.86203.857203.4530.403597-0.996931
25202.86203.625203.4750.149931-0.764931
26203.8203.721203.510.2104310.0791528
27203.78203.632203.5960.03601390.148153
28204.53203.548203.777-0.2299030.982403
29204.44203.774204-0.2258190.666236
30204.14203.949204.162-0.2137360.191236
31204.14204.095204.286-0.1908190.0449861
32204.04204.027204.35-0.3232360.0128194
33204.68204.1204.299-0.1989860.580236
34205.01204.192204.1370.05534720.817986
35204.93204.449203.9220.5271810.481153
36204.34204.059203.6550.4035970.280986
37204.34203.488203.3380.1499310.852153
38203.87203.235203.0250.2104310.634986
39202.47202.742202.7060.0360139-0.272264
40201.95202.181202.411-0.229903-0.231347
41201.86201.964202.19-0.225819-0.104181
42200.33201.824202.038-0.213736-1.49418
43200.33201.723201.914-0.190819-1.39293
44200.33201.486201.809-0.323236-1.15551
45200.75201.586201.785-0.198986-0.836431
46201.86201.906201.8510.0553472-0.0461806
47202.77202.49201.9630.5271810.279903
48202.85202.594202.190.4035970.256403
49202.85202.661202.5110.1499310.188819
50202.84203.055202.8440.210431-0.214597
51202.94203.221203.1850.0360139-0.280597
52203.05203.297203.527-0.229903-0.247181
53203.45203.624203.85-0.225819-0.173764
54204.19203.93204.144-0.2137360.259986
55204.18204.198204.388-0.190819-0.0175139
56204.47204.268204.591-0.3232360.201986
57204.78204.622204.821-0.1989860.158153
58206.05205.065205.0090.05534720.985486
59206.32205.634205.1070.5271810.686153
60206.36205.572205.1690.4035970.787653
61205.21205.367205.2170.149931-0.156597
62205.35205.46205.250.210431-0.110431
63205.94205.333205.2970.03601390.607319
64204.57205.083205.312-0.229903-0.512597
65204.27205.019205.245-0.225819-0.749181
66204.86204.923205.137-0.213736-0.0629306
67204.66NANA-0.190819NA
68204.79NANA-0.323236NA
69205.58NANA-0.198986NA
70205.63NANA0.0553472NA
71205.12NANA0.527181NA
72204.96NANA0.403597NA


Figures (Output of Computation)

Input Parameters & R Code

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')