FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationMon, 09 Dec 2013 03:32:52 -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/09/t13865779977ulxdi5cdbyrwi7.htm/, Retrieved Wed, 24 Apr 2024 22:18:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231559, Retrieved Wed, 24 Apr 2024 22:18:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-09 08:32:52] [c1a61ab38fcc49939d713dd54579d7ce] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
107,2
107,56
107,72
108,14
108,16
108,16
108,16
108,1
108,95
110,49
110,72
110,82
110,82
110,75
110,71
110,86
110,84
110,84
110,84
110,92
111,46
112,46
113,04
113,15
113,15
113,21
113,37
113,47
113,71
113,71
113,71
113,8
115,46
117
117,94
118,08
118,08
118,47
118,49
118,45
118,54
118,55
118,55
118,55
119,04
121,37
122
122,14
122,14
122,03
121,91
122,23
121,73
121,83
121,83
122,49
123,02
125,98
126,13
126,39
126,39
126,57
126,87
127,26
126,82
126,7
126,7
126,7
128,53
130,37
130,39
130,65
130,65
130,65
130,85
130,89
130,85
131,6
131,6
131,6
132,53
133,05
133,49
133,46

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231559&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]6 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=231559&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231559&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 time6 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1107.2NANA0.603796NA
2107.56NANA0.352824NA
3107.72NANA0.112546NA
4108.14NANA-0.0478704NA
5108.16NANA-0.474329NA
6108.16NANA-0.666343NA
7108.16107.787108.832-1.04530.372801
8108.1107.876109.116-1.240160.223912
9108.95108.796109.374-0.5778010.154051
10110.49110.584109.6120.971921-0.093588
11110.72110.918109.8371.08137-0.198032
12110.82110.989110.060.929352-0.169352
13110.82110.887110.2830.603796-0.0671296
14110.75110.865110.5120.352824-0.115324
15110.71110.847110.7350.112546-0.13713
16110.86110.873110.921-0.0478704-0.0133796
17110.84110.626111.1-0.4743290.214329
18110.84110.627111.294-0.6663430.212593
19110.84110.443111.488-1.04530.397384
20110.92110.447111.687-1.240160.472662
21111.46111.323111.901-0.5778010.136968
22112.46113.092112.120.971921-0.632338
23113.04113.43112.3491.08137-0.390116
24113.15113.517112.5880.929352-0.367269
25113.15113.431112.8270.603796-0.28088
26113.21113.419113.0670.352824-0.209491
27113.37113.466113.3530.112546-0.0958796
28113.47113.661113.709-0.0478704-0.191296
29113.71113.628114.102-0.4743290.0818287
30113.71113.846114.512-0.666343-0.135741
31113.71113.878114.923-1.0453-0.167616
32113.8114.107115.347-1.24016-0.307338
33115.46115.202115.78-0.5778010.257801
34117117.173116.2010.971921-0.172755
35117.94117.691116.611.081370.249051
36118.08117.942117.0120.9293520.138148
37118.08118.02117.4160.6037960.0603704
38118.47118.168117.8150.3528240.301759
39118.49118.275118.1620.1125460.214954
40118.45118.446118.494-0.04787040.00412037
41118.54118.371118.845-0.4743290.169329
42118.55118.517119.183-0.6663430.0330093
43118.55118.476119.522-1.04530.0736343
44118.55118.599119.839-1.24016-0.0490046
45119.04119.552120.13-0.577801-0.512199
46121.37121.402120.430.971921-0.0319213
47122121.802120.721.081370.198218
48122.14121.919120.990.9293520.220648
49122.14121.867121.2630.6037960.27287
50122.03121.917121.5640.3528240.113009
51121.91122.007121.8940.112546-0.096713
52122.23122.204122.252-0.04787040.025787
53121.73122.142122.616-0.474329-0.411921
54121.83122.299122.965-0.666343-0.469074
55121.83122.274123.32-1.0453-0.444282
56122.49122.446123.686-1.240160.0443287
57123.02123.504124.082-0.577801-0.483866
58125.98125.47124.4980.9719210.510162
59126.13126.001124.921.081370.129051
60126.39126.264125.3350.9293520.126065
61126.39126.344125.740.6037960.045787
62126.57126.472126.1190.3528240.0984259
63126.87126.636126.5240.1125460.233704
64127.26126.888126.936-0.04787040.37162
65126.82126.822127.297-0.474329-0.00233796
66126.7126.985127.652-0.666343-0.285324
67126.7126.961128.007-1.0453-0.261366
68126.7127.114128.354-1.24016-0.414005
69128.53128.112128.69-0.5778010.417801
70130.37129.979129.0070.9719210.390995
71130.39130.408129.3261.08137-0.0176157
72130.65130.628129.6980.9293520.0223148
73130.65130.71130.1070.603796-0.060463
74130.65130.868130.5150.352824-0.217824
75130.85130.998130.8860.112546-0.14838
76130.89131.116131.164-0.0478704-0.226296
77130.85130.931131.405-0.474329-0.0806713
78131.6130.985131.651-0.6663430.615093
79131.6NANA-1.0453NA
80131.6NANA-1.24016NA
81132.53NANA-0.577801NA
82133.05NANA0.971921NA
83133.49NANA1.08137NA
84133.46NANA0.929352NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 107.2 & NA & NA & 0.603796 & NA \tabularnewline
2 & 107.56 & NA & NA & 0.352824 & NA \tabularnewline
3 & 107.72 & NA & NA & 0.112546 & NA \tabularnewline
4 & 108.14 & NA & NA & -0.0478704 & NA \tabularnewline
5 & 108.16 & NA & NA & -0.474329 & NA \tabularnewline
6 & 108.16 & NA & NA & -0.666343 & NA \tabularnewline
7 & 108.16 & 107.787 & 108.832 & -1.0453 & 0.372801 \tabularnewline
8 & 108.1 & 107.876 & 109.116 & -1.24016 & 0.223912 \tabularnewline
9 & 108.95 & 108.796 & 109.374 & -0.577801 & 0.154051 \tabularnewline
10 & 110.49 & 110.584 & 109.612 & 0.971921 & -0.093588 \tabularnewline
11 & 110.72 & 110.918 & 109.837 & 1.08137 & -0.198032 \tabularnewline
12 & 110.82 & 110.989 & 110.06 & 0.929352 & -0.169352 \tabularnewline
13 & 110.82 & 110.887 & 110.283 & 0.603796 & -0.0671296 \tabularnewline
14 & 110.75 & 110.865 & 110.512 & 0.352824 & -0.115324 \tabularnewline
15 & 110.71 & 110.847 & 110.735 & 0.112546 & -0.13713 \tabularnewline
16 & 110.86 & 110.873 & 110.921 & -0.0478704 & -0.0133796 \tabularnewline
17 & 110.84 & 110.626 & 111.1 & -0.474329 & 0.214329 \tabularnewline
18 & 110.84 & 110.627 & 111.294 & -0.666343 & 0.212593 \tabularnewline
19 & 110.84 & 110.443 & 111.488 & -1.0453 & 0.397384 \tabularnewline
20 & 110.92 & 110.447 & 111.687 & -1.24016 & 0.472662 \tabularnewline
21 & 111.46 & 111.323 & 111.901 & -0.577801 & 0.136968 \tabularnewline
22 & 112.46 & 113.092 & 112.12 & 0.971921 & -0.632338 \tabularnewline
23 & 113.04 & 113.43 & 112.349 & 1.08137 & -0.390116 \tabularnewline
24 & 113.15 & 113.517 & 112.588 & 0.929352 & -0.367269 \tabularnewline
25 & 113.15 & 113.431 & 112.827 & 0.603796 & -0.28088 \tabularnewline
26 & 113.21 & 113.419 & 113.067 & 0.352824 & -0.209491 \tabularnewline
27 & 113.37 & 113.466 & 113.353 & 0.112546 & -0.0958796 \tabularnewline
28 & 113.47 & 113.661 & 113.709 & -0.0478704 & -0.191296 \tabularnewline
29 & 113.71 & 113.628 & 114.102 & -0.474329 & 0.0818287 \tabularnewline
30 & 113.71 & 113.846 & 114.512 & -0.666343 & -0.135741 \tabularnewline
31 & 113.71 & 113.878 & 114.923 & -1.0453 & -0.167616 \tabularnewline
32 & 113.8 & 114.107 & 115.347 & -1.24016 & -0.307338 \tabularnewline
33 & 115.46 & 115.202 & 115.78 & -0.577801 & 0.257801 \tabularnewline
34 & 117 & 117.173 & 116.201 & 0.971921 & -0.172755 \tabularnewline
35 & 117.94 & 117.691 & 116.61 & 1.08137 & 0.249051 \tabularnewline
36 & 118.08 & 117.942 & 117.012 & 0.929352 & 0.138148 \tabularnewline
37 & 118.08 & 118.02 & 117.416 & 0.603796 & 0.0603704 \tabularnewline
38 & 118.47 & 118.168 & 117.815 & 0.352824 & 0.301759 \tabularnewline
39 & 118.49 & 118.275 & 118.162 & 0.112546 & 0.214954 \tabularnewline
40 & 118.45 & 118.446 & 118.494 & -0.0478704 & 0.00412037 \tabularnewline
41 & 118.54 & 118.371 & 118.845 & -0.474329 & 0.169329 \tabularnewline
42 & 118.55 & 118.517 & 119.183 & -0.666343 & 0.0330093 \tabularnewline
43 & 118.55 & 118.476 & 119.522 & -1.0453 & 0.0736343 \tabularnewline
44 & 118.55 & 118.599 & 119.839 & -1.24016 & -0.0490046 \tabularnewline
45 & 119.04 & 119.552 & 120.13 & -0.577801 & -0.512199 \tabularnewline
46 & 121.37 & 121.402 & 120.43 & 0.971921 & -0.0319213 \tabularnewline
47 & 122 & 121.802 & 120.72 & 1.08137 & 0.198218 \tabularnewline
48 & 122.14 & 121.919 & 120.99 & 0.929352 & 0.220648 \tabularnewline
49 & 122.14 & 121.867 & 121.263 & 0.603796 & 0.27287 \tabularnewline
50 & 122.03 & 121.917 & 121.564 & 0.352824 & 0.113009 \tabularnewline
51 & 121.91 & 122.007 & 121.894 & 0.112546 & -0.096713 \tabularnewline
52 & 122.23 & 122.204 & 122.252 & -0.0478704 & 0.025787 \tabularnewline
53 & 121.73 & 122.142 & 122.616 & -0.474329 & -0.411921 \tabularnewline
54 & 121.83 & 122.299 & 122.965 & -0.666343 & -0.469074 \tabularnewline
55 & 121.83 & 122.274 & 123.32 & -1.0453 & -0.444282 \tabularnewline
56 & 122.49 & 122.446 & 123.686 & -1.24016 & 0.0443287 \tabularnewline
57 & 123.02 & 123.504 & 124.082 & -0.577801 & -0.483866 \tabularnewline
58 & 125.98 & 125.47 & 124.498 & 0.971921 & 0.510162 \tabularnewline
59 & 126.13 & 126.001 & 124.92 & 1.08137 & 0.129051 \tabularnewline
60 & 126.39 & 126.264 & 125.335 & 0.929352 & 0.126065 \tabularnewline
61 & 126.39 & 126.344 & 125.74 & 0.603796 & 0.045787 \tabularnewline
62 & 126.57 & 126.472 & 126.119 & 0.352824 & 0.0984259 \tabularnewline
63 & 126.87 & 126.636 & 126.524 & 0.112546 & 0.233704 \tabularnewline
64 & 127.26 & 126.888 & 126.936 & -0.0478704 & 0.37162 \tabularnewline
65 & 126.82 & 126.822 & 127.297 & -0.474329 & -0.00233796 \tabularnewline
66 & 126.7 & 126.985 & 127.652 & -0.666343 & -0.285324 \tabularnewline
67 & 126.7 & 126.961 & 128.007 & -1.0453 & -0.261366 \tabularnewline
68 & 126.7 & 127.114 & 128.354 & -1.24016 & -0.414005 \tabularnewline
69 & 128.53 & 128.112 & 128.69 & -0.577801 & 0.417801 \tabularnewline
70 & 130.37 & 129.979 & 129.007 & 0.971921 & 0.390995 \tabularnewline
71 & 130.39 & 130.408 & 129.326 & 1.08137 & -0.0176157 \tabularnewline
72 & 130.65 & 130.628 & 129.698 & 0.929352 & 0.0223148 \tabularnewline
73 & 130.65 & 130.71 & 130.107 & 0.603796 & -0.060463 \tabularnewline
74 & 130.65 & 130.868 & 130.515 & 0.352824 & -0.217824 \tabularnewline
75 & 130.85 & 130.998 & 130.886 & 0.112546 & -0.14838 \tabularnewline
76 & 130.89 & 131.116 & 131.164 & -0.0478704 & -0.226296 \tabularnewline
77 & 130.85 & 130.931 & 131.405 & -0.474329 & -0.0806713 \tabularnewline
78 & 131.6 & 130.985 & 131.651 & -0.666343 & 0.615093 \tabularnewline
79 & 131.6 & NA & NA & -1.0453 & NA \tabularnewline
80 & 131.6 & NA & NA & -1.24016 & NA \tabularnewline
81 & 132.53 & NA & NA & -0.577801 & NA \tabularnewline
82 & 133.05 & NA & NA & 0.971921 & NA \tabularnewline
83 & 133.49 & NA & NA & 1.08137 & NA \tabularnewline
84 & 133.46 & NA & NA & 0.929352 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231559&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]107.2[/C][C]NA[/C][C]NA[/C][C]0.603796[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]107.56[/C][C]NA[/C][C]NA[/C][C]0.352824[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]107.72[/C][C]NA[/C][C]NA[/C][C]0.112546[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]108.14[/C][C]NA[/C][C]NA[/C][C]-0.0478704[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]108.16[/C][C]NA[/C][C]NA[/C][C]-0.474329[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]108.16[/C][C]NA[/C][C]NA[/C][C]-0.666343[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]108.16[/C][C]107.787[/C][C]108.832[/C][C]-1.0453[/C][C]0.372801[/C][/ROW]
[ROW][C]8[/C][C]108.1[/C][C]107.876[/C][C]109.116[/C][C]-1.24016[/C][C]0.223912[/C][/ROW]
[ROW][C]9[/C][C]108.95[/C][C]108.796[/C][C]109.374[/C][C]-0.577801[/C][C]0.154051[/C][/ROW]
[ROW][C]10[/C][C]110.49[/C][C]110.584[/C][C]109.612[/C][C]0.971921[/C][C]-0.093588[/C][/ROW]
[ROW][C]11[/C][C]110.72[/C][C]110.918[/C][C]109.837[/C][C]1.08137[/C][C]-0.198032[/C][/ROW]
[ROW][C]12[/C][C]110.82[/C][C]110.989[/C][C]110.06[/C][C]0.929352[/C][C]-0.169352[/C][/ROW]
[ROW][C]13[/C][C]110.82[/C][C]110.887[/C][C]110.283[/C][C]0.603796[/C][C]-0.0671296[/C][/ROW]
[ROW][C]14[/C][C]110.75[/C][C]110.865[/C][C]110.512[/C][C]0.352824[/C][C]-0.115324[/C][/ROW]
[ROW][C]15[/C][C]110.71[/C][C]110.847[/C][C]110.735[/C][C]0.112546[/C][C]-0.13713[/C][/ROW]
[ROW][C]16[/C][C]110.86[/C][C]110.873[/C][C]110.921[/C][C]-0.0478704[/C][C]-0.0133796[/C][/ROW]
[ROW][C]17[/C][C]110.84[/C][C]110.626[/C][C]111.1[/C][C]-0.474329[/C][C]0.214329[/C][/ROW]
[ROW][C]18[/C][C]110.84[/C][C]110.627[/C][C]111.294[/C][C]-0.666343[/C][C]0.212593[/C][/ROW]
[ROW][C]19[/C][C]110.84[/C][C]110.443[/C][C]111.488[/C][C]-1.0453[/C][C]0.397384[/C][/ROW]
[ROW][C]20[/C][C]110.92[/C][C]110.447[/C][C]111.687[/C][C]-1.24016[/C][C]0.472662[/C][/ROW]
[ROW][C]21[/C][C]111.46[/C][C]111.323[/C][C]111.901[/C][C]-0.577801[/C][C]0.136968[/C][/ROW]
[ROW][C]22[/C][C]112.46[/C][C]113.092[/C][C]112.12[/C][C]0.971921[/C][C]-0.632338[/C][/ROW]
[ROW][C]23[/C][C]113.04[/C][C]113.43[/C][C]112.349[/C][C]1.08137[/C][C]-0.390116[/C][/ROW]
[ROW][C]24[/C][C]113.15[/C][C]113.517[/C][C]112.588[/C][C]0.929352[/C][C]-0.367269[/C][/ROW]
[ROW][C]25[/C][C]113.15[/C][C]113.431[/C][C]112.827[/C][C]0.603796[/C][C]-0.28088[/C][/ROW]
[ROW][C]26[/C][C]113.21[/C][C]113.419[/C][C]113.067[/C][C]0.352824[/C][C]-0.209491[/C][/ROW]
[ROW][C]27[/C][C]113.37[/C][C]113.466[/C][C]113.353[/C][C]0.112546[/C][C]-0.0958796[/C][/ROW]
[ROW][C]28[/C][C]113.47[/C][C]113.661[/C][C]113.709[/C][C]-0.0478704[/C][C]-0.191296[/C][/ROW]
[ROW][C]29[/C][C]113.71[/C][C]113.628[/C][C]114.102[/C][C]-0.474329[/C][C]0.0818287[/C][/ROW]
[ROW][C]30[/C][C]113.71[/C][C]113.846[/C][C]114.512[/C][C]-0.666343[/C][C]-0.135741[/C][/ROW]
[ROW][C]31[/C][C]113.71[/C][C]113.878[/C][C]114.923[/C][C]-1.0453[/C][C]-0.167616[/C][/ROW]
[ROW][C]32[/C][C]113.8[/C][C]114.107[/C][C]115.347[/C][C]-1.24016[/C][C]-0.307338[/C][/ROW]
[ROW][C]33[/C][C]115.46[/C][C]115.202[/C][C]115.78[/C][C]-0.577801[/C][C]0.257801[/C][/ROW]
[ROW][C]34[/C][C]117[/C][C]117.173[/C][C]116.201[/C][C]0.971921[/C][C]-0.172755[/C][/ROW]
[ROW][C]35[/C][C]117.94[/C][C]117.691[/C][C]116.61[/C][C]1.08137[/C][C]0.249051[/C][/ROW]
[ROW][C]36[/C][C]118.08[/C][C]117.942[/C][C]117.012[/C][C]0.929352[/C][C]0.138148[/C][/ROW]
[ROW][C]37[/C][C]118.08[/C][C]118.02[/C][C]117.416[/C][C]0.603796[/C][C]0.0603704[/C][/ROW]
[ROW][C]38[/C][C]118.47[/C][C]118.168[/C][C]117.815[/C][C]0.352824[/C][C]0.301759[/C][/ROW]
[ROW][C]39[/C][C]118.49[/C][C]118.275[/C][C]118.162[/C][C]0.112546[/C][C]0.214954[/C][/ROW]
[ROW][C]40[/C][C]118.45[/C][C]118.446[/C][C]118.494[/C][C]-0.0478704[/C][C]0.00412037[/C][/ROW]
[ROW][C]41[/C][C]118.54[/C][C]118.371[/C][C]118.845[/C][C]-0.474329[/C][C]0.169329[/C][/ROW]
[ROW][C]42[/C][C]118.55[/C][C]118.517[/C][C]119.183[/C][C]-0.666343[/C][C]0.0330093[/C][/ROW]
[ROW][C]43[/C][C]118.55[/C][C]118.476[/C][C]119.522[/C][C]-1.0453[/C][C]0.0736343[/C][/ROW]
[ROW][C]44[/C][C]118.55[/C][C]118.599[/C][C]119.839[/C][C]-1.24016[/C][C]-0.0490046[/C][/ROW]
[ROW][C]45[/C][C]119.04[/C][C]119.552[/C][C]120.13[/C][C]-0.577801[/C][C]-0.512199[/C][/ROW]
[ROW][C]46[/C][C]121.37[/C][C]121.402[/C][C]120.43[/C][C]0.971921[/C][C]-0.0319213[/C][/ROW]
[ROW][C]47[/C][C]122[/C][C]121.802[/C][C]120.72[/C][C]1.08137[/C][C]0.198218[/C][/ROW]
[ROW][C]48[/C][C]122.14[/C][C]121.919[/C][C]120.99[/C][C]0.929352[/C][C]0.220648[/C][/ROW]
[ROW][C]49[/C][C]122.14[/C][C]121.867[/C][C]121.263[/C][C]0.603796[/C][C]0.27287[/C][/ROW]
[ROW][C]50[/C][C]122.03[/C][C]121.917[/C][C]121.564[/C][C]0.352824[/C][C]0.113009[/C][/ROW]
[ROW][C]51[/C][C]121.91[/C][C]122.007[/C][C]121.894[/C][C]0.112546[/C][C]-0.096713[/C][/ROW]
[ROW][C]52[/C][C]122.23[/C][C]122.204[/C][C]122.252[/C][C]-0.0478704[/C][C]0.025787[/C][/ROW]
[ROW][C]53[/C][C]121.73[/C][C]122.142[/C][C]122.616[/C][C]-0.474329[/C][C]-0.411921[/C][/ROW]
[ROW][C]54[/C][C]121.83[/C][C]122.299[/C][C]122.965[/C][C]-0.666343[/C][C]-0.469074[/C][/ROW]
[ROW][C]55[/C][C]121.83[/C][C]122.274[/C][C]123.32[/C][C]-1.0453[/C][C]-0.444282[/C][/ROW]
[ROW][C]56[/C][C]122.49[/C][C]122.446[/C][C]123.686[/C][C]-1.24016[/C][C]0.0443287[/C][/ROW]
[ROW][C]57[/C][C]123.02[/C][C]123.504[/C][C]124.082[/C][C]-0.577801[/C][C]-0.483866[/C][/ROW]
[ROW][C]58[/C][C]125.98[/C][C]125.47[/C][C]124.498[/C][C]0.971921[/C][C]0.510162[/C][/ROW]
[ROW][C]59[/C][C]126.13[/C][C]126.001[/C][C]124.92[/C][C]1.08137[/C][C]0.129051[/C][/ROW]
[ROW][C]60[/C][C]126.39[/C][C]126.264[/C][C]125.335[/C][C]0.929352[/C][C]0.126065[/C][/ROW]
[ROW][C]61[/C][C]126.39[/C][C]126.344[/C][C]125.74[/C][C]0.603796[/C][C]0.045787[/C][/ROW]
[ROW][C]62[/C][C]126.57[/C][C]126.472[/C][C]126.119[/C][C]0.352824[/C][C]0.0984259[/C][/ROW]
[ROW][C]63[/C][C]126.87[/C][C]126.636[/C][C]126.524[/C][C]0.112546[/C][C]0.233704[/C][/ROW]
[ROW][C]64[/C][C]127.26[/C][C]126.888[/C][C]126.936[/C][C]-0.0478704[/C][C]0.37162[/C][/ROW]
[ROW][C]65[/C][C]126.82[/C][C]126.822[/C][C]127.297[/C][C]-0.474329[/C][C]-0.00233796[/C][/ROW]
[ROW][C]66[/C][C]126.7[/C][C]126.985[/C][C]127.652[/C][C]-0.666343[/C][C]-0.285324[/C][/ROW]
[ROW][C]67[/C][C]126.7[/C][C]126.961[/C][C]128.007[/C][C]-1.0453[/C][C]-0.261366[/C][/ROW]
[ROW][C]68[/C][C]126.7[/C][C]127.114[/C][C]128.354[/C][C]-1.24016[/C][C]-0.414005[/C][/ROW]
[ROW][C]69[/C][C]128.53[/C][C]128.112[/C][C]128.69[/C][C]-0.577801[/C][C]0.417801[/C][/ROW]
[ROW][C]70[/C][C]130.37[/C][C]129.979[/C][C]129.007[/C][C]0.971921[/C][C]0.390995[/C][/ROW]
[ROW][C]71[/C][C]130.39[/C][C]130.408[/C][C]129.326[/C][C]1.08137[/C][C]-0.0176157[/C][/ROW]
[ROW][C]72[/C][C]130.65[/C][C]130.628[/C][C]129.698[/C][C]0.929352[/C][C]0.0223148[/C][/ROW]
[ROW][C]73[/C][C]130.65[/C][C]130.71[/C][C]130.107[/C][C]0.603796[/C][C]-0.060463[/C][/ROW]
[ROW][C]74[/C][C]130.65[/C][C]130.868[/C][C]130.515[/C][C]0.352824[/C][C]-0.217824[/C][/ROW]
[ROW][C]75[/C][C]130.85[/C][C]130.998[/C][C]130.886[/C][C]0.112546[/C][C]-0.14838[/C][/ROW]
[ROW][C]76[/C][C]130.89[/C][C]131.116[/C][C]131.164[/C][C]-0.0478704[/C][C]-0.226296[/C][/ROW]
[ROW][C]77[/C][C]130.85[/C][C]130.931[/C][C]131.405[/C][C]-0.474329[/C][C]-0.0806713[/C][/ROW]
[ROW][C]78[/C][C]131.6[/C][C]130.985[/C][C]131.651[/C][C]-0.666343[/C][C]0.615093[/C][/ROW]
[ROW][C]79[/C][C]131.6[/C][C]NA[/C][C]NA[/C][C]-1.0453[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]131.6[/C][C]NA[/C][C]NA[/C][C]-1.24016[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]132.53[/C][C]NA[/C][C]NA[/C][C]-0.577801[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]133.05[/C][C]NA[/C][C]NA[/C][C]0.971921[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]133.49[/C][C]NA[/C][C]NA[/C][C]1.08137[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]133.46[/C][C]NA[/C][C]NA[/C][C]0.929352[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231559&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231559&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
1107.2NANA0.603796NA
2107.56NANA0.352824NA
3107.72NANA0.112546NA
4108.14NANA-0.0478704NA
5108.16NANA-0.474329NA
6108.16NANA-0.666343NA
7108.16107.787108.832-1.04530.372801
8108.1107.876109.116-1.240160.223912
9108.95108.796109.374-0.5778010.154051
10110.49110.584109.6120.971921-0.093588
11110.72110.918109.8371.08137-0.198032
12110.82110.989110.060.929352-0.169352
13110.82110.887110.2830.603796-0.0671296
14110.75110.865110.5120.352824-0.115324
15110.71110.847110.7350.112546-0.13713
16110.86110.873110.921-0.0478704-0.0133796
17110.84110.626111.1-0.4743290.214329
18110.84110.627111.294-0.6663430.212593
19110.84110.443111.488-1.04530.397384
20110.92110.447111.687-1.240160.472662
21111.46111.323111.901-0.5778010.136968
22112.46113.092112.120.971921-0.632338
23113.04113.43112.3491.08137-0.390116
24113.15113.517112.5880.929352-0.367269
25113.15113.431112.8270.603796-0.28088
26113.21113.419113.0670.352824-0.209491
27113.37113.466113.3530.112546-0.0958796
28113.47113.661113.709-0.0478704-0.191296
29113.71113.628114.102-0.4743290.0818287
30113.71113.846114.512-0.666343-0.135741
31113.71113.878114.923-1.0453-0.167616
32113.8114.107115.347-1.24016-0.307338
33115.46115.202115.78-0.5778010.257801
34117117.173116.2010.971921-0.172755
35117.94117.691116.611.081370.249051
36118.08117.942117.0120.9293520.138148
37118.08118.02117.4160.6037960.0603704
38118.47118.168117.8150.3528240.301759
39118.49118.275118.1620.1125460.214954
40118.45118.446118.494-0.04787040.00412037
41118.54118.371118.845-0.4743290.169329
42118.55118.517119.183-0.6663430.0330093
43118.55118.476119.522-1.04530.0736343
44118.55118.599119.839-1.24016-0.0490046
45119.04119.552120.13-0.577801-0.512199
46121.37121.402120.430.971921-0.0319213
47122121.802120.721.081370.198218
48122.14121.919120.990.9293520.220648
49122.14121.867121.2630.6037960.27287
50122.03121.917121.5640.3528240.113009
51121.91122.007121.8940.112546-0.096713
52122.23122.204122.252-0.04787040.025787
53121.73122.142122.616-0.474329-0.411921
54121.83122.299122.965-0.666343-0.469074
55121.83122.274123.32-1.0453-0.444282
56122.49122.446123.686-1.240160.0443287
57123.02123.504124.082-0.577801-0.483866
58125.98125.47124.4980.9719210.510162
59126.13126.001124.921.081370.129051
60126.39126.264125.3350.9293520.126065
61126.39126.344125.740.6037960.045787
62126.57126.472126.1190.3528240.0984259
63126.87126.636126.5240.1125460.233704
64127.26126.888126.936-0.04787040.37162
65126.82126.822127.297-0.474329-0.00233796
66126.7126.985127.652-0.666343-0.285324
67126.7126.961128.007-1.0453-0.261366
68126.7127.114128.354-1.24016-0.414005
69128.53128.112128.69-0.5778010.417801
70130.37129.979129.0070.9719210.390995
71130.39130.408129.3261.08137-0.0176157
72130.65130.628129.6980.9293520.0223148
73130.65130.71130.1070.603796-0.060463
74130.65130.868130.5150.352824-0.217824
75130.85130.998130.8860.112546-0.14838
76130.89131.116131.164-0.0478704-0.226296
77130.85130.931131.405-0.474329-0.0806713
78131.6130.985131.651-0.6663430.615093
79131.6NANA-1.0453NA
80131.6NANA-1.24016NA
81132.53NANA-0.577801NA
82133.05NANA0.971921NA
83133.49NANA1.08137NA
84133.46NANA0.929352NA


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 <- '12'
par1 <- 'additive'
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')