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R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationMon, 09 Dec 2013 11:32:50 -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/t1386606816nqxc7ezfjyxf5fw.htm/, Retrieved Fri, 29 Mar 2024 15:33:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231684, Retrieved Fri, 29 Mar 2024 15:33:31 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-09 16:32:50] [d5e0951e56f9204e3d256e2fd8efefc4] [Current]
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Dataseries X:
104,4
104,4
104,4
104,4
104,4
104,41
104,42
104,68
106,02
106,35
106,38
106,47
106,5
106,56
113,07
116,26
118
118,02
118,04
118,12
118,12
118,17
118,22
118,22
118,23
118,23
118,23
119,94
120,88
121,14
121,16
121,2
121,2
121,2
121,2
121,2
121,22
121,22
121,95
123,05
123,44
123,65
123,79
123,87
123,91
123,94
124,28
126,28
126,68
126,69
126,69
126,99
128,79
128,84
128,95
128,97
128,97
128,97
128,97
128,97
128,97
128,98
128,99
129,07
129,76
130,47
130,76
130,88
131,04
131,06
131,13
131,15
131,16
131,33
131,42
131,86
134,39
135,59
136,01
136,14
136,74
136,89
136,82
136,82




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231684&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231684&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231684&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 time6 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1104.4NANA-0.863657NA
2104.4NANA-1.25984NA
3104.4NANA-0.46831NA
4104.4NANA0.24294NA
5104.4NANA1.1678NA
6104.41NANA1.15398NA
7104.42105.73105.1480.581829-1.31016
8104.68105.635105.3260.308981-0.954815
9106.02105.968105.7770.1909950.0519213
10106.35106.517106.632-0.115671-0.166829
11106.38107.26107.693-0.432963-0.88037
12106.47108.321108.827-0.506088-1.851
13106.5109.098109.962-0.863657-2.59801
14106.56109.829111.089-1.25984-3.26933
15113.07111.685112.153-0.468311.38498
16116.26113.393113.150.242942.86706
17118115.304114.1361.16782.69637
18118.02116.273115.1191.153981.74727
19118.04116.679116.0970.5818291.36109
20118.12117.381117.0720.3089810.738935
21118.12117.964117.7730.1909950.155671
22118.17118.026118.142-0.1156710.144005
23118.22117.982118.415-0.4329630.237963
24118.22118.159118.665-0.5060880.061088
25118.23118.061118.925-0.8636570.168657
26118.23117.923119.183-1.259840.306505
27118.23118.972119.44-0.46831-0.74169
28119.94119.938119.6950.242940.00247685
29120.88121.113119.9451.1678-0.232801
30121.14121.347120.1931.15398-0.207315
31121.16121.024120.4420.5818290.136088
32121.2121120.6910.3089810.199769
33121.2121.162120.9710.1909950.0381713
34121.2121.14121.255-0.1156710.0602546
35121.2121.059121.492-0.4329630.141296
36121.2121.197121.703-0.5060880.0031713
37121.22121.053121.917-0.8636570.166574
38121.22120.878122.138-1.259840.341921
39121.95121.894122.362-0.468310.0562269
40123.05122.832122.5890.242940.217894
41123.44123.999122.8321.1678-0.559468
42123.65124.326123.1721.15398-0.675648
43123.79124.193123.6110.581829-0.402662
44123.87124.375124.0660.308981-0.505231
45123.91124.683124.4920.190995-0.772662
46123.94124.738124.853-0.115671-0.797662
47124.28124.807125.24-0.432963-0.527454
48126.28125.173125.68-0.5060881.1065
49126.68125.247126.111-0.8636571.43282
50126.69125.278126.538-1.259841.4115
51126.69126.493126.962-0.468310.196644
52126.99127.625127.3820.24294-0.635023
53128.79128.955127.7871.1678-0.164884
54128.84129.249128.0951.15398-0.408565
55128.95128.884128.3020.5818290.066088
56128.97128.802128.4930.3089810.168102
57128.97128.875128.6840.1909950.094838
58128.97128.751128.867-0.1156710.219005
59128.97128.561128.994-0.4329630.409213
60128.97128.596129.102-0.5060880.374005
61128.97128.382129.245-0.8636570.588241
62128.98128.141129.4-1.259840.839421
63128.99129.098129.566-0.46831-0.10794
64129.07129.983129.740.24294-0.912523
65129.76131.084129.9171.1678-1.32447
66130.47131.251130.0981.15398-0.781481
67130.76130.861130.280.581829-0.101412
68130.88130.778130.4690.3089810.102269
69131.04130.859130.6680.1909950.181088
70131.06130.77130.885-0.1156710.290255
71131.13130.762131.195-0.4329630.36838
72131.15131.095131.601-0.5060880.0552546
73131.16131.169132.033-0.863657-0.00925926
74131.33131.211132.471-1.259840.119005
75131.42132.459132.927-0.46831-1.03919
76131.86133.651133.4080.24294-1.79086
77134.39135.056133.8881.1678-0.665718
78135.59135.515134.3611.153980.0747685
79136.01NANA0.581829NA
80136.14NANA0.308981NA
81136.74NANA0.190995NA
82136.89NANA-0.115671NA
83136.82NANA-0.432963NA
84136.82NANA-0.506088NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 104.4 & NA & NA & -0.863657 & NA \tabularnewline
2 & 104.4 & NA & NA & -1.25984 & NA \tabularnewline
3 & 104.4 & NA & NA & -0.46831 & NA \tabularnewline
4 & 104.4 & NA & NA & 0.24294 & NA \tabularnewline
5 & 104.4 & NA & NA & 1.1678 & NA \tabularnewline
6 & 104.41 & NA & NA & 1.15398 & NA \tabularnewline
7 & 104.42 & 105.73 & 105.148 & 0.581829 & -1.31016 \tabularnewline
8 & 104.68 & 105.635 & 105.326 & 0.308981 & -0.954815 \tabularnewline
9 & 106.02 & 105.968 & 105.777 & 0.190995 & 0.0519213 \tabularnewline
10 & 106.35 & 106.517 & 106.632 & -0.115671 & -0.166829 \tabularnewline
11 & 106.38 & 107.26 & 107.693 & -0.432963 & -0.88037 \tabularnewline
12 & 106.47 & 108.321 & 108.827 & -0.506088 & -1.851 \tabularnewline
13 & 106.5 & 109.098 & 109.962 & -0.863657 & -2.59801 \tabularnewline
14 & 106.56 & 109.829 & 111.089 & -1.25984 & -3.26933 \tabularnewline
15 & 113.07 & 111.685 & 112.153 & -0.46831 & 1.38498 \tabularnewline
16 & 116.26 & 113.393 & 113.15 & 0.24294 & 2.86706 \tabularnewline
17 & 118 & 115.304 & 114.136 & 1.1678 & 2.69637 \tabularnewline
18 & 118.02 & 116.273 & 115.119 & 1.15398 & 1.74727 \tabularnewline
19 & 118.04 & 116.679 & 116.097 & 0.581829 & 1.36109 \tabularnewline
20 & 118.12 & 117.381 & 117.072 & 0.308981 & 0.738935 \tabularnewline
21 & 118.12 & 117.964 & 117.773 & 0.190995 & 0.155671 \tabularnewline
22 & 118.17 & 118.026 & 118.142 & -0.115671 & 0.144005 \tabularnewline
23 & 118.22 & 117.982 & 118.415 & -0.432963 & 0.237963 \tabularnewline
24 & 118.22 & 118.159 & 118.665 & -0.506088 & 0.061088 \tabularnewline
25 & 118.23 & 118.061 & 118.925 & -0.863657 & 0.168657 \tabularnewline
26 & 118.23 & 117.923 & 119.183 & -1.25984 & 0.306505 \tabularnewline
27 & 118.23 & 118.972 & 119.44 & -0.46831 & -0.74169 \tabularnewline
28 & 119.94 & 119.938 & 119.695 & 0.24294 & 0.00247685 \tabularnewline
29 & 120.88 & 121.113 & 119.945 & 1.1678 & -0.232801 \tabularnewline
30 & 121.14 & 121.347 & 120.193 & 1.15398 & -0.207315 \tabularnewline
31 & 121.16 & 121.024 & 120.442 & 0.581829 & 0.136088 \tabularnewline
32 & 121.2 & 121 & 120.691 & 0.308981 & 0.199769 \tabularnewline
33 & 121.2 & 121.162 & 120.971 & 0.190995 & 0.0381713 \tabularnewline
34 & 121.2 & 121.14 & 121.255 & -0.115671 & 0.0602546 \tabularnewline
35 & 121.2 & 121.059 & 121.492 & -0.432963 & 0.141296 \tabularnewline
36 & 121.2 & 121.197 & 121.703 & -0.506088 & 0.0031713 \tabularnewline
37 & 121.22 & 121.053 & 121.917 & -0.863657 & 0.166574 \tabularnewline
38 & 121.22 & 120.878 & 122.138 & -1.25984 & 0.341921 \tabularnewline
39 & 121.95 & 121.894 & 122.362 & -0.46831 & 0.0562269 \tabularnewline
40 & 123.05 & 122.832 & 122.589 & 0.24294 & 0.217894 \tabularnewline
41 & 123.44 & 123.999 & 122.832 & 1.1678 & -0.559468 \tabularnewline
42 & 123.65 & 124.326 & 123.172 & 1.15398 & -0.675648 \tabularnewline
43 & 123.79 & 124.193 & 123.611 & 0.581829 & -0.402662 \tabularnewline
44 & 123.87 & 124.375 & 124.066 & 0.308981 & -0.505231 \tabularnewline
45 & 123.91 & 124.683 & 124.492 & 0.190995 & -0.772662 \tabularnewline
46 & 123.94 & 124.738 & 124.853 & -0.115671 & -0.797662 \tabularnewline
47 & 124.28 & 124.807 & 125.24 & -0.432963 & -0.527454 \tabularnewline
48 & 126.28 & 125.173 & 125.68 & -0.506088 & 1.1065 \tabularnewline
49 & 126.68 & 125.247 & 126.111 & -0.863657 & 1.43282 \tabularnewline
50 & 126.69 & 125.278 & 126.538 & -1.25984 & 1.4115 \tabularnewline
51 & 126.69 & 126.493 & 126.962 & -0.46831 & 0.196644 \tabularnewline
52 & 126.99 & 127.625 & 127.382 & 0.24294 & -0.635023 \tabularnewline
53 & 128.79 & 128.955 & 127.787 & 1.1678 & -0.164884 \tabularnewline
54 & 128.84 & 129.249 & 128.095 & 1.15398 & -0.408565 \tabularnewline
55 & 128.95 & 128.884 & 128.302 & 0.581829 & 0.066088 \tabularnewline
56 & 128.97 & 128.802 & 128.493 & 0.308981 & 0.168102 \tabularnewline
57 & 128.97 & 128.875 & 128.684 & 0.190995 & 0.094838 \tabularnewline
58 & 128.97 & 128.751 & 128.867 & -0.115671 & 0.219005 \tabularnewline
59 & 128.97 & 128.561 & 128.994 & -0.432963 & 0.409213 \tabularnewline
60 & 128.97 & 128.596 & 129.102 & -0.506088 & 0.374005 \tabularnewline
61 & 128.97 & 128.382 & 129.245 & -0.863657 & 0.588241 \tabularnewline
62 & 128.98 & 128.141 & 129.4 & -1.25984 & 0.839421 \tabularnewline
63 & 128.99 & 129.098 & 129.566 & -0.46831 & -0.10794 \tabularnewline
64 & 129.07 & 129.983 & 129.74 & 0.24294 & -0.912523 \tabularnewline
65 & 129.76 & 131.084 & 129.917 & 1.1678 & -1.32447 \tabularnewline
66 & 130.47 & 131.251 & 130.098 & 1.15398 & -0.781481 \tabularnewline
67 & 130.76 & 130.861 & 130.28 & 0.581829 & -0.101412 \tabularnewline
68 & 130.88 & 130.778 & 130.469 & 0.308981 & 0.102269 \tabularnewline
69 & 131.04 & 130.859 & 130.668 & 0.190995 & 0.181088 \tabularnewline
70 & 131.06 & 130.77 & 130.885 & -0.115671 & 0.290255 \tabularnewline
71 & 131.13 & 130.762 & 131.195 & -0.432963 & 0.36838 \tabularnewline
72 & 131.15 & 131.095 & 131.601 & -0.506088 & 0.0552546 \tabularnewline
73 & 131.16 & 131.169 & 132.033 & -0.863657 & -0.00925926 \tabularnewline
74 & 131.33 & 131.211 & 132.471 & -1.25984 & 0.119005 \tabularnewline
75 & 131.42 & 132.459 & 132.927 & -0.46831 & -1.03919 \tabularnewline
76 & 131.86 & 133.651 & 133.408 & 0.24294 & -1.79086 \tabularnewline
77 & 134.39 & 135.056 & 133.888 & 1.1678 & -0.665718 \tabularnewline
78 & 135.59 & 135.515 & 134.361 & 1.15398 & 0.0747685 \tabularnewline
79 & 136.01 & NA & NA & 0.581829 & NA \tabularnewline
80 & 136.14 & NA & NA & 0.308981 & NA \tabularnewline
81 & 136.74 & NA & NA & 0.190995 & NA \tabularnewline
82 & 136.89 & NA & NA & -0.115671 & NA \tabularnewline
83 & 136.82 & NA & NA & -0.432963 & NA \tabularnewline
84 & 136.82 & NA & NA & -0.506088 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231684&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]104.4[/C][C]NA[/C][C]NA[/C][C]-0.863657[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]104.4[/C][C]NA[/C][C]NA[/C][C]-1.25984[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]104.4[/C][C]NA[/C][C]NA[/C][C]-0.46831[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]104.4[/C][C]NA[/C][C]NA[/C][C]0.24294[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]104.4[/C][C]NA[/C][C]NA[/C][C]1.1678[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]104.41[/C][C]NA[/C][C]NA[/C][C]1.15398[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]104.42[/C][C]105.73[/C][C]105.148[/C][C]0.581829[/C][C]-1.31016[/C][/ROW]
[ROW][C]8[/C][C]104.68[/C][C]105.635[/C][C]105.326[/C][C]0.308981[/C][C]-0.954815[/C][/ROW]
[ROW][C]9[/C][C]106.02[/C][C]105.968[/C][C]105.777[/C][C]0.190995[/C][C]0.0519213[/C][/ROW]
[ROW][C]10[/C][C]106.35[/C][C]106.517[/C][C]106.632[/C][C]-0.115671[/C][C]-0.166829[/C][/ROW]
[ROW][C]11[/C][C]106.38[/C][C]107.26[/C][C]107.693[/C][C]-0.432963[/C][C]-0.88037[/C][/ROW]
[ROW][C]12[/C][C]106.47[/C][C]108.321[/C][C]108.827[/C][C]-0.506088[/C][C]-1.851[/C][/ROW]
[ROW][C]13[/C][C]106.5[/C][C]109.098[/C][C]109.962[/C][C]-0.863657[/C][C]-2.59801[/C][/ROW]
[ROW][C]14[/C][C]106.56[/C][C]109.829[/C][C]111.089[/C][C]-1.25984[/C][C]-3.26933[/C][/ROW]
[ROW][C]15[/C][C]113.07[/C][C]111.685[/C][C]112.153[/C][C]-0.46831[/C][C]1.38498[/C][/ROW]
[ROW][C]16[/C][C]116.26[/C][C]113.393[/C][C]113.15[/C][C]0.24294[/C][C]2.86706[/C][/ROW]
[ROW][C]17[/C][C]118[/C][C]115.304[/C][C]114.136[/C][C]1.1678[/C][C]2.69637[/C][/ROW]
[ROW][C]18[/C][C]118.02[/C][C]116.273[/C][C]115.119[/C][C]1.15398[/C][C]1.74727[/C][/ROW]
[ROW][C]19[/C][C]118.04[/C][C]116.679[/C][C]116.097[/C][C]0.581829[/C][C]1.36109[/C][/ROW]
[ROW][C]20[/C][C]118.12[/C][C]117.381[/C][C]117.072[/C][C]0.308981[/C][C]0.738935[/C][/ROW]
[ROW][C]21[/C][C]118.12[/C][C]117.964[/C][C]117.773[/C][C]0.190995[/C][C]0.155671[/C][/ROW]
[ROW][C]22[/C][C]118.17[/C][C]118.026[/C][C]118.142[/C][C]-0.115671[/C][C]0.144005[/C][/ROW]
[ROW][C]23[/C][C]118.22[/C][C]117.982[/C][C]118.415[/C][C]-0.432963[/C][C]0.237963[/C][/ROW]
[ROW][C]24[/C][C]118.22[/C][C]118.159[/C][C]118.665[/C][C]-0.506088[/C][C]0.061088[/C][/ROW]
[ROW][C]25[/C][C]118.23[/C][C]118.061[/C][C]118.925[/C][C]-0.863657[/C][C]0.168657[/C][/ROW]
[ROW][C]26[/C][C]118.23[/C][C]117.923[/C][C]119.183[/C][C]-1.25984[/C][C]0.306505[/C][/ROW]
[ROW][C]27[/C][C]118.23[/C][C]118.972[/C][C]119.44[/C][C]-0.46831[/C][C]-0.74169[/C][/ROW]
[ROW][C]28[/C][C]119.94[/C][C]119.938[/C][C]119.695[/C][C]0.24294[/C][C]0.00247685[/C][/ROW]
[ROW][C]29[/C][C]120.88[/C][C]121.113[/C][C]119.945[/C][C]1.1678[/C][C]-0.232801[/C][/ROW]
[ROW][C]30[/C][C]121.14[/C][C]121.347[/C][C]120.193[/C][C]1.15398[/C][C]-0.207315[/C][/ROW]
[ROW][C]31[/C][C]121.16[/C][C]121.024[/C][C]120.442[/C][C]0.581829[/C][C]0.136088[/C][/ROW]
[ROW][C]32[/C][C]121.2[/C][C]121[/C][C]120.691[/C][C]0.308981[/C][C]0.199769[/C][/ROW]
[ROW][C]33[/C][C]121.2[/C][C]121.162[/C][C]120.971[/C][C]0.190995[/C][C]0.0381713[/C][/ROW]
[ROW][C]34[/C][C]121.2[/C][C]121.14[/C][C]121.255[/C][C]-0.115671[/C][C]0.0602546[/C][/ROW]
[ROW][C]35[/C][C]121.2[/C][C]121.059[/C][C]121.492[/C][C]-0.432963[/C][C]0.141296[/C][/ROW]
[ROW][C]36[/C][C]121.2[/C][C]121.197[/C][C]121.703[/C][C]-0.506088[/C][C]0.0031713[/C][/ROW]
[ROW][C]37[/C][C]121.22[/C][C]121.053[/C][C]121.917[/C][C]-0.863657[/C][C]0.166574[/C][/ROW]
[ROW][C]38[/C][C]121.22[/C][C]120.878[/C][C]122.138[/C][C]-1.25984[/C][C]0.341921[/C][/ROW]
[ROW][C]39[/C][C]121.95[/C][C]121.894[/C][C]122.362[/C][C]-0.46831[/C][C]0.0562269[/C][/ROW]
[ROW][C]40[/C][C]123.05[/C][C]122.832[/C][C]122.589[/C][C]0.24294[/C][C]0.217894[/C][/ROW]
[ROW][C]41[/C][C]123.44[/C][C]123.999[/C][C]122.832[/C][C]1.1678[/C][C]-0.559468[/C][/ROW]
[ROW][C]42[/C][C]123.65[/C][C]124.326[/C][C]123.172[/C][C]1.15398[/C][C]-0.675648[/C][/ROW]
[ROW][C]43[/C][C]123.79[/C][C]124.193[/C][C]123.611[/C][C]0.581829[/C][C]-0.402662[/C][/ROW]
[ROW][C]44[/C][C]123.87[/C][C]124.375[/C][C]124.066[/C][C]0.308981[/C][C]-0.505231[/C][/ROW]
[ROW][C]45[/C][C]123.91[/C][C]124.683[/C][C]124.492[/C][C]0.190995[/C][C]-0.772662[/C][/ROW]
[ROW][C]46[/C][C]123.94[/C][C]124.738[/C][C]124.853[/C][C]-0.115671[/C][C]-0.797662[/C][/ROW]
[ROW][C]47[/C][C]124.28[/C][C]124.807[/C][C]125.24[/C][C]-0.432963[/C][C]-0.527454[/C][/ROW]
[ROW][C]48[/C][C]126.28[/C][C]125.173[/C][C]125.68[/C][C]-0.506088[/C][C]1.1065[/C][/ROW]
[ROW][C]49[/C][C]126.68[/C][C]125.247[/C][C]126.111[/C][C]-0.863657[/C][C]1.43282[/C][/ROW]
[ROW][C]50[/C][C]126.69[/C][C]125.278[/C][C]126.538[/C][C]-1.25984[/C][C]1.4115[/C][/ROW]
[ROW][C]51[/C][C]126.69[/C][C]126.493[/C][C]126.962[/C][C]-0.46831[/C][C]0.196644[/C][/ROW]
[ROW][C]52[/C][C]126.99[/C][C]127.625[/C][C]127.382[/C][C]0.24294[/C][C]-0.635023[/C][/ROW]
[ROW][C]53[/C][C]128.79[/C][C]128.955[/C][C]127.787[/C][C]1.1678[/C][C]-0.164884[/C][/ROW]
[ROW][C]54[/C][C]128.84[/C][C]129.249[/C][C]128.095[/C][C]1.15398[/C][C]-0.408565[/C][/ROW]
[ROW][C]55[/C][C]128.95[/C][C]128.884[/C][C]128.302[/C][C]0.581829[/C][C]0.066088[/C][/ROW]
[ROW][C]56[/C][C]128.97[/C][C]128.802[/C][C]128.493[/C][C]0.308981[/C][C]0.168102[/C][/ROW]
[ROW][C]57[/C][C]128.97[/C][C]128.875[/C][C]128.684[/C][C]0.190995[/C][C]0.094838[/C][/ROW]
[ROW][C]58[/C][C]128.97[/C][C]128.751[/C][C]128.867[/C][C]-0.115671[/C][C]0.219005[/C][/ROW]
[ROW][C]59[/C][C]128.97[/C][C]128.561[/C][C]128.994[/C][C]-0.432963[/C][C]0.409213[/C][/ROW]
[ROW][C]60[/C][C]128.97[/C][C]128.596[/C][C]129.102[/C][C]-0.506088[/C][C]0.374005[/C][/ROW]
[ROW][C]61[/C][C]128.97[/C][C]128.382[/C][C]129.245[/C][C]-0.863657[/C][C]0.588241[/C][/ROW]
[ROW][C]62[/C][C]128.98[/C][C]128.141[/C][C]129.4[/C][C]-1.25984[/C][C]0.839421[/C][/ROW]
[ROW][C]63[/C][C]128.99[/C][C]129.098[/C][C]129.566[/C][C]-0.46831[/C][C]-0.10794[/C][/ROW]
[ROW][C]64[/C][C]129.07[/C][C]129.983[/C][C]129.74[/C][C]0.24294[/C][C]-0.912523[/C][/ROW]
[ROW][C]65[/C][C]129.76[/C][C]131.084[/C][C]129.917[/C][C]1.1678[/C][C]-1.32447[/C][/ROW]
[ROW][C]66[/C][C]130.47[/C][C]131.251[/C][C]130.098[/C][C]1.15398[/C][C]-0.781481[/C][/ROW]
[ROW][C]67[/C][C]130.76[/C][C]130.861[/C][C]130.28[/C][C]0.581829[/C][C]-0.101412[/C][/ROW]
[ROW][C]68[/C][C]130.88[/C][C]130.778[/C][C]130.469[/C][C]0.308981[/C][C]0.102269[/C][/ROW]
[ROW][C]69[/C][C]131.04[/C][C]130.859[/C][C]130.668[/C][C]0.190995[/C][C]0.181088[/C][/ROW]
[ROW][C]70[/C][C]131.06[/C][C]130.77[/C][C]130.885[/C][C]-0.115671[/C][C]0.290255[/C][/ROW]
[ROW][C]71[/C][C]131.13[/C][C]130.762[/C][C]131.195[/C][C]-0.432963[/C][C]0.36838[/C][/ROW]
[ROW][C]72[/C][C]131.15[/C][C]131.095[/C][C]131.601[/C][C]-0.506088[/C][C]0.0552546[/C][/ROW]
[ROW][C]73[/C][C]131.16[/C][C]131.169[/C][C]132.033[/C][C]-0.863657[/C][C]-0.00925926[/C][/ROW]
[ROW][C]74[/C][C]131.33[/C][C]131.211[/C][C]132.471[/C][C]-1.25984[/C][C]0.119005[/C][/ROW]
[ROW][C]75[/C][C]131.42[/C][C]132.459[/C][C]132.927[/C][C]-0.46831[/C][C]-1.03919[/C][/ROW]
[ROW][C]76[/C][C]131.86[/C][C]133.651[/C][C]133.408[/C][C]0.24294[/C][C]-1.79086[/C][/ROW]
[ROW][C]77[/C][C]134.39[/C][C]135.056[/C][C]133.888[/C][C]1.1678[/C][C]-0.665718[/C][/ROW]
[ROW][C]78[/C][C]135.59[/C][C]135.515[/C][C]134.361[/C][C]1.15398[/C][C]0.0747685[/C][/ROW]
[ROW][C]79[/C][C]136.01[/C][C]NA[/C][C]NA[/C][C]0.581829[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]136.14[/C][C]NA[/C][C]NA[/C][C]0.308981[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]136.74[/C][C]NA[/C][C]NA[/C][C]0.190995[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]136.89[/C][C]NA[/C][C]NA[/C][C]-0.115671[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]136.82[/C][C]NA[/C][C]NA[/C][C]-0.432963[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]136.82[/C][C]NA[/C][C]NA[/C][C]-0.506088[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231684&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231684&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
1104.4NANA-0.863657NA
2104.4NANA-1.25984NA
3104.4NANA-0.46831NA
4104.4NANA0.24294NA
5104.4NANA1.1678NA
6104.41NANA1.15398NA
7104.42105.73105.1480.581829-1.31016
8104.68105.635105.3260.308981-0.954815
9106.02105.968105.7770.1909950.0519213
10106.35106.517106.632-0.115671-0.166829
11106.38107.26107.693-0.432963-0.88037
12106.47108.321108.827-0.506088-1.851
13106.5109.098109.962-0.863657-2.59801
14106.56109.829111.089-1.25984-3.26933
15113.07111.685112.153-0.468311.38498
16116.26113.393113.150.242942.86706
17118115.304114.1361.16782.69637
18118.02116.273115.1191.153981.74727
19118.04116.679116.0970.5818291.36109
20118.12117.381117.0720.3089810.738935
21118.12117.964117.7730.1909950.155671
22118.17118.026118.142-0.1156710.144005
23118.22117.982118.415-0.4329630.237963
24118.22118.159118.665-0.5060880.061088
25118.23118.061118.925-0.8636570.168657
26118.23117.923119.183-1.259840.306505
27118.23118.972119.44-0.46831-0.74169
28119.94119.938119.6950.242940.00247685
29120.88121.113119.9451.1678-0.232801
30121.14121.347120.1931.15398-0.207315
31121.16121.024120.4420.5818290.136088
32121.2121120.6910.3089810.199769
33121.2121.162120.9710.1909950.0381713
34121.2121.14121.255-0.1156710.0602546
35121.2121.059121.492-0.4329630.141296
36121.2121.197121.703-0.5060880.0031713
37121.22121.053121.917-0.8636570.166574
38121.22120.878122.138-1.259840.341921
39121.95121.894122.362-0.468310.0562269
40123.05122.832122.5890.242940.217894
41123.44123.999122.8321.1678-0.559468
42123.65124.326123.1721.15398-0.675648
43123.79124.193123.6110.581829-0.402662
44123.87124.375124.0660.308981-0.505231
45123.91124.683124.4920.190995-0.772662
46123.94124.738124.853-0.115671-0.797662
47124.28124.807125.24-0.432963-0.527454
48126.28125.173125.68-0.5060881.1065
49126.68125.247126.111-0.8636571.43282
50126.69125.278126.538-1.259841.4115
51126.69126.493126.962-0.468310.196644
52126.99127.625127.3820.24294-0.635023
53128.79128.955127.7871.1678-0.164884
54128.84129.249128.0951.15398-0.408565
55128.95128.884128.3020.5818290.066088
56128.97128.802128.4930.3089810.168102
57128.97128.875128.6840.1909950.094838
58128.97128.751128.867-0.1156710.219005
59128.97128.561128.994-0.4329630.409213
60128.97128.596129.102-0.5060880.374005
61128.97128.382129.245-0.8636570.588241
62128.98128.141129.4-1.259840.839421
63128.99129.098129.566-0.46831-0.10794
64129.07129.983129.740.24294-0.912523
65129.76131.084129.9171.1678-1.32447
66130.47131.251130.0981.15398-0.781481
67130.76130.861130.280.581829-0.101412
68130.88130.778130.4690.3089810.102269
69131.04130.859130.6680.1909950.181088
70131.06130.77130.885-0.1156710.290255
71131.13130.762131.195-0.4329630.36838
72131.15131.095131.601-0.5060880.0552546
73131.16131.169132.033-0.863657-0.00925926
74131.33131.211132.471-1.259840.119005
75131.42132.459132.927-0.46831-1.03919
76131.86133.651133.4080.24294-1.79086
77134.39135.056133.8881.1678-0.665718
78135.59135.515134.3611.153980.0747685
79136.01NANA0.581829NA
80136.14NANA0.308981NA
81136.74NANA0.190995NA
82136.89NANA-0.115671NA
83136.82NANA-0.432963NA
84136.82NANA-0.506088NA



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')