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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 computationMon, 18 May 2015 19:56:44 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/May/18/t1431975457tyfcrw8b4mip14r.htm/, Retrieved Thu, 02 May 2024 05:18:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279114, Retrieved Thu, 02 May 2024 05:18:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2015-05-18 18:56:44] [006461bb825a57cb671d1f8ff85b37cb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
299,81
299,01
296,82
296,67
296,95
296,80
296,80
295,93
293,77
291,02
288,61
284,55
284,55
278,14
273,28
270,14
268,36
267,15
267,15
265,47
261,75
256,51
252,98
251,17
251,17
244,27
240,54
238,92
237,47
235,91
235,91
231,41
224,94
222,19
219,06
217,83
217,83
216,89
213,84
212,90
213,98
215,31
215,31
214,09
213,71
211,54
209,40
207,33
207,33
202,75
200,26
198,99
198,82
198,43
198,43
195,68
195,45
193,65
191,38
189,71
189,71
185,49
183,01
182,38
181,60
182,13
182,13
180,81
180,25
179,84
178,50
178,11
178,11
178,10
177,52
177,34
175,53
176,01
175,94
175,47
175,48
173,76
173,74
173,65
172,00
171,50
170,41
171,50
171,43
170,69
170,40
169,90
170,21
170,55
169,98
169,34

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279114&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279114&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279114&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'George Udny Yule' @ yule.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1299.81NANA0.863309NA
2299.01NANA-0.999846NA
3296.82NANA-2.12562NA
4296.67NANA-1.62877NA
5296.95NANA-0.916989NA
6296.8NANA0.252059NA
7296.8296.073294.0921.980150.727346
8295.93294.257292.5871.669921.673
9293.77291.988290.7371.251341.78199
10291.02288.994288.650.343132.02645
11288.61286.069286.354-0.2846682.54092
12284.55283.523283.927-0.4040131.02693
13284.55282.32281.4560.8633092.23044
14278.14277.952278.952-0.9998460.18818
15273.28274.223276.348-2.12562-0.942713
16270.14271.947273.576-1.62877-1.80748
17268.36269.737270.654-0.916989-1.37676
18267.15268.03267.7780.252059-0.880392
19267.15266.977264.9971.980150.17318
20265.47263.864262.1951.669921.6055
21261.75260.671259.4191.251341.07949
22256.51257.097256.7540.34313-0.587297
23252.98253.882254.166-0.284668-0.901582
24251.17251.173251.577-0.404013-0.0034871
25251.17249.837248.9740.8633091.33252
26244.27245.253246.253-0.999846-0.983487
27240.54241.175243.3-2.12562-0.634797
28238.92238.708240.337-1.628770.212108
29237.47236.576237.493-0.9169890.893656
30235.91234.943234.6910.2520590.967108
31235.91233.893231.9121.980152.01735
32231.41231.052229.3821.669920.357584
33224.94228.381227.1291.25134-3.44051
34222.19225.276224.9320.34313-3.08563
35219.06222.585222.87-0.284668-3.52492
36217.83220.628221.033-0.404013-2.79849
37217.83220.179219.3160.863309-2.34914
38216.89216.736217.736-0.9998460.154013
39213.84214.421216.546-2.12562-0.58063
40212.9214.006215.635-1.62877-1.10581
41213.98213.871214.788-0.9169890.108656
42215.31214.2213.9480.2520591.10961
43215.31215.053213.0731.980150.256513
44214.09213.717212.0471.669920.373418
45213.71212.143210.8921.251341.56699
46211.54210.089209.7460.343131.45062
47209.4208.25208.535-0.2846681.14967
48207.33206.796207.2-0.4040130.534013
49207.33206.657205.7930.8633090.673358
50202.75203.323204.323-0.999846-0.57307
51200.26200.669202.795-2.12562-0.40938
52198.99199.66201.289-1.62877-0.669975
53198.82198.876199.792-0.916989-0.0555109
54198.43198.56198.3070.252059-0.129559
55198.43198.819196.8391.98015-0.38932
56195.68197.056195.3861.66992-1.37575
57195.45195.199193.9481.251340.250739
58193.65192.88192.5370.343130.769787
59191.38190.843191.128-0.2846680.537168
60189.71189.327189.731-0.4040130.38318
61189.71189.236188.3720.8633090.474191
62185.49186.074187.074-0.999846-0.583904
63183.01183.695185.821-2.12562-0.685213
64182.38182.983184.612-1.62877-0.603309
65181.6182.583183.5-0.916989-0.983011
66182.13182.732182.480.252059-0.602059
67182.13183.493181.5131.98015-1.36349
68180.81182.392180.7221.66992-1.582
69180.25181.437180.1851.25134-1.18676
70179.84180.09179.7470.34313-0.249797
71178.5178.999179.284-0.284668-0.499082
72178.11178.372178.776-0.404013-0.26182
73178.11179.126178.2630.863309-1.01623
74178.1176.783177.782-0.9998461.31735
75177.52175.236177.361-2.125622.28437
76177.34175.28176.909-1.628772.05961
77175.53175.541176.458-0.916989-0.0105109
78176.01176.325176.0730.252059-0.315392
79175.94177.613175.6331.98015-1.67307
80175.47176.773175.1031.66992-1.30325
81175.48175.783174.5321.25134-0.303428
82173.76174.336173.9920.34313-0.57563
83173.74173.294173.578-0.2846680.446334
84173.65172.782173.186-0.4040130.86818
85172173.597172.7330.863309-1.59664
86171.5171.271172.27-0.9998460.22943
87170.41169.693171.819-2.125620.71687
88171.5169.837171.465-1.628771.66336
89171.43170.258171.175-0.9169891.17199
90170.69171.091170.8390.252059-0.400809
91170.4NANA1.98015NA
92169.9NANA1.66992NA
93170.21NANA1.25134NA
94170.55NANA0.34313NA
95169.98NANA-0.284668NA
96169.34NANA-0.404013NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 299.81 & NA & NA & 0.863309 & NA \tabularnewline
2 & 299.01 & NA & NA & -0.999846 & NA \tabularnewline
3 & 296.82 & NA & NA & -2.12562 & NA \tabularnewline
4 & 296.67 & NA & NA & -1.62877 & NA \tabularnewline
5 & 296.95 & NA & NA & -0.916989 & NA \tabularnewline
6 & 296.8 & NA & NA & 0.252059 & NA \tabularnewline
7 & 296.8 & 296.073 & 294.092 & 1.98015 & 0.727346 \tabularnewline
8 & 295.93 & 294.257 & 292.587 & 1.66992 & 1.673 \tabularnewline
9 & 293.77 & 291.988 & 290.737 & 1.25134 & 1.78199 \tabularnewline
10 & 291.02 & 288.994 & 288.65 & 0.34313 & 2.02645 \tabularnewline
11 & 288.61 & 286.069 & 286.354 & -0.284668 & 2.54092 \tabularnewline
12 & 284.55 & 283.523 & 283.927 & -0.404013 & 1.02693 \tabularnewline
13 & 284.55 & 282.32 & 281.456 & 0.863309 & 2.23044 \tabularnewline
14 & 278.14 & 277.952 & 278.952 & -0.999846 & 0.18818 \tabularnewline
15 & 273.28 & 274.223 & 276.348 & -2.12562 & -0.942713 \tabularnewline
16 & 270.14 & 271.947 & 273.576 & -1.62877 & -1.80748 \tabularnewline
17 & 268.36 & 269.737 & 270.654 & -0.916989 & -1.37676 \tabularnewline
18 & 267.15 & 268.03 & 267.778 & 0.252059 & -0.880392 \tabularnewline
19 & 267.15 & 266.977 & 264.997 & 1.98015 & 0.17318 \tabularnewline
20 & 265.47 & 263.864 & 262.195 & 1.66992 & 1.6055 \tabularnewline
21 & 261.75 & 260.671 & 259.419 & 1.25134 & 1.07949 \tabularnewline
22 & 256.51 & 257.097 & 256.754 & 0.34313 & -0.587297 \tabularnewline
23 & 252.98 & 253.882 & 254.166 & -0.284668 & -0.901582 \tabularnewline
24 & 251.17 & 251.173 & 251.577 & -0.404013 & -0.0034871 \tabularnewline
25 & 251.17 & 249.837 & 248.974 & 0.863309 & 1.33252 \tabularnewline
26 & 244.27 & 245.253 & 246.253 & -0.999846 & -0.983487 \tabularnewline
27 & 240.54 & 241.175 & 243.3 & -2.12562 & -0.634797 \tabularnewline
28 & 238.92 & 238.708 & 240.337 & -1.62877 & 0.212108 \tabularnewline
29 & 237.47 & 236.576 & 237.493 & -0.916989 & 0.893656 \tabularnewline
30 & 235.91 & 234.943 & 234.691 & 0.252059 & 0.967108 \tabularnewline
31 & 235.91 & 233.893 & 231.912 & 1.98015 & 2.01735 \tabularnewline
32 & 231.41 & 231.052 & 229.382 & 1.66992 & 0.357584 \tabularnewline
33 & 224.94 & 228.381 & 227.129 & 1.25134 & -3.44051 \tabularnewline
34 & 222.19 & 225.276 & 224.932 & 0.34313 & -3.08563 \tabularnewline
35 & 219.06 & 222.585 & 222.87 & -0.284668 & -3.52492 \tabularnewline
36 & 217.83 & 220.628 & 221.033 & -0.404013 & -2.79849 \tabularnewline
37 & 217.83 & 220.179 & 219.316 & 0.863309 & -2.34914 \tabularnewline
38 & 216.89 & 216.736 & 217.736 & -0.999846 & 0.154013 \tabularnewline
39 & 213.84 & 214.421 & 216.546 & -2.12562 & -0.58063 \tabularnewline
40 & 212.9 & 214.006 & 215.635 & -1.62877 & -1.10581 \tabularnewline
41 & 213.98 & 213.871 & 214.788 & -0.916989 & 0.108656 \tabularnewline
42 & 215.31 & 214.2 & 213.948 & 0.252059 & 1.10961 \tabularnewline
43 & 215.31 & 215.053 & 213.073 & 1.98015 & 0.256513 \tabularnewline
44 & 214.09 & 213.717 & 212.047 & 1.66992 & 0.373418 \tabularnewline
45 & 213.71 & 212.143 & 210.892 & 1.25134 & 1.56699 \tabularnewline
46 & 211.54 & 210.089 & 209.746 & 0.34313 & 1.45062 \tabularnewline
47 & 209.4 & 208.25 & 208.535 & -0.284668 & 1.14967 \tabularnewline
48 & 207.33 & 206.796 & 207.2 & -0.404013 & 0.534013 \tabularnewline
49 & 207.33 & 206.657 & 205.793 & 0.863309 & 0.673358 \tabularnewline
50 & 202.75 & 203.323 & 204.323 & -0.999846 & -0.57307 \tabularnewline
51 & 200.26 & 200.669 & 202.795 & -2.12562 & -0.40938 \tabularnewline
52 & 198.99 & 199.66 & 201.289 & -1.62877 & -0.669975 \tabularnewline
53 & 198.82 & 198.876 & 199.792 & -0.916989 & -0.0555109 \tabularnewline
54 & 198.43 & 198.56 & 198.307 & 0.252059 & -0.129559 \tabularnewline
55 & 198.43 & 198.819 & 196.839 & 1.98015 & -0.38932 \tabularnewline
56 & 195.68 & 197.056 & 195.386 & 1.66992 & -1.37575 \tabularnewline
57 & 195.45 & 195.199 & 193.948 & 1.25134 & 0.250739 \tabularnewline
58 & 193.65 & 192.88 & 192.537 & 0.34313 & 0.769787 \tabularnewline
59 & 191.38 & 190.843 & 191.128 & -0.284668 & 0.537168 \tabularnewline
60 & 189.71 & 189.327 & 189.731 & -0.404013 & 0.38318 \tabularnewline
61 & 189.71 & 189.236 & 188.372 & 0.863309 & 0.474191 \tabularnewline
62 & 185.49 & 186.074 & 187.074 & -0.999846 & -0.583904 \tabularnewline
63 & 183.01 & 183.695 & 185.821 & -2.12562 & -0.685213 \tabularnewline
64 & 182.38 & 182.983 & 184.612 & -1.62877 & -0.603309 \tabularnewline
65 & 181.6 & 182.583 & 183.5 & -0.916989 & -0.983011 \tabularnewline
66 & 182.13 & 182.732 & 182.48 & 0.252059 & -0.602059 \tabularnewline
67 & 182.13 & 183.493 & 181.513 & 1.98015 & -1.36349 \tabularnewline
68 & 180.81 & 182.392 & 180.722 & 1.66992 & -1.582 \tabularnewline
69 & 180.25 & 181.437 & 180.185 & 1.25134 & -1.18676 \tabularnewline
70 & 179.84 & 180.09 & 179.747 & 0.34313 & -0.249797 \tabularnewline
71 & 178.5 & 178.999 & 179.284 & -0.284668 & -0.499082 \tabularnewline
72 & 178.11 & 178.372 & 178.776 & -0.404013 & -0.26182 \tabularnewline
73 & 178.11 & 179.126 & 178.263 & 0.863309 & -1.01623 \tabularnewline
74 & 178.1 & 176.783 & 177.782 & -0.999846 & 1.31735 \tabularnewline
75 & 177.52 & 175.236 & 177.361 & -2.12562 & 2.28437 \tabularnewline
76 & 177.34 & 175.28 & 176.909 & -1.62877 & 2.05961 \tabularnewline
77 & 175.53 & 175.541 & 176.458 & -0.916989 & -0.0105109 \tabularnewline
78 & 176.01 & 176.325 & 176.073 & 0.252059 & -0.315392 \tabularnewline
79 & 175.94 & 177.613 & 175.633 & 1.98015 & -1.67307 \tabularnewline
80 & 175.47 & 176.773 & 175.103 & 1.66992 & -1.30325 \tabularnewline
81 & 175.48 & 175.783 & 174.532 & 1.25134 & -0.303428 \tabularnewline
82 & 173.76 & 174.336 & 173.992 & 0.34313 & -0.57563 \tabularnewline
83 & 173.74 & 173.294 & 173.578 & -0.284668 & 0.446334 \tabularnewline
84 & 173.65 & 172.782 & 173.186 & -0.404013 & 0.86818 \tabularnewline
85 & 172 & 173.597 & 172.733 & 0.863309 & -1.59664 \tabularnewline
86 & 171.5 & 171.271 & 172.27 & -0.999846 & 0.22943 \tabularnewline
87 & 170.41 & 169.693 & 171.819 & -2.12562 & 0.71687 \tabularnewline
88 & 171.5 & 169.837 & 171.465 & -1.62877 & 1.66336 \tabularnewline
89 & 171.43 & 170.258 & 171.175 & -0.916989 & 1.17199 \tabularnewline
90 & 170.69 & 171.091 & 170.839 & 0.252059 & -0.400809 \tabularnewline
91 & 170.4 & NA & NA & 1.98015 & NA \tabularnewline
92 & 169.9 & NA & NA & 1.66992 & NA \tabularnewline
93 & 170.21 & NA & NA & 1.25134 & NA \tabularnewline
94 & 170.55 & NA & NA & 0.34313 & NA \tabularnewline
95 & 169.98 & NA & NA & -0.284668 & NA \tabularnewline
96 & 169.34 & NA & NA & -0.404013 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279114&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]299.81[/C][C]NA[/C][C]NA[/C][C]0.863309[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]299.01[/C][C]NA[/C][C]NA[/C][C]-0.999846[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]296.82[/C][C]NA[/C][C]NA[/C][C]-2.12562[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]296.67[/C][C]NA[/C][C]NA[/C][C]-1.62877[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]296.95[/C][C]NA[/C][C]NA[/C][C]-0.916989[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]296.8[/C][C]NA[/C][C]NA[/C][C]0.252059[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]296.8[/C][C]296.073[/C][C]294.092[/C][C]1.98015[/C][C]0.727346[/C][/ROW]
[ROW][C]8[/C][C]295.93[/C][C]294.257[/C][C]292.587[/C][C]1.66992[/C][C]1.673[/C][/ROW]
[ROW][C]9[/C][C]293.77[/C][C]291.988[/C][C]290.737[/C][C]1.25134[/C][C]1.78199[/C][/ROW]
[ROW][C]10[/C][C]291.02[/C][C]288.994[/C][C]288.65[/C][C]0.34313[/C][C]2.02645[/C][/ROW]
[ROW][C]11[/C][C]288.61[/C][C]286.069[/C][C]286.354[/C][C]-0.284668[/C][C]2.54092[/C][/ROW]
[ROW][C]12[/C][C]284.55[/C][C]283.523[/C][C]283.927[/C][C]-0.404013[/C][C]1.02693[/C][/ROW]
[ROW][C]13[/C][C]284.55[/C][C]282.32[/C][C]281.456[/C][C]0.863309[/C][C]2.23044[/C][/ROW]
[ROW][C]14[/C][C]278.14[/C][C]277.952[/C][C]278.952[/C][C]-0.999846[/C][C]0.18818[/C][/ROW]
[ROW][C]15[/C][C]273.28[/C][C]274.223[/C][C]276.348[/C][C]-2.12562[/C][C]-0.942713[/C][/ROW]
[ROW][C]16[/C][C]270.14[/C][C]271.947[/C][C]273.576[/C][C]-1.62877[/C][C]-1.80748[/C][/ROW]
[ROW][C]17[/C][C]268.36[/C][C]269.737[/C][C]270.654[/C][C]-0.916989[/C][C]-1.37676[/C][/ROW]
[ROW][C]18[/C][C]267.15[/C][C]268.03[/C][C]267.778[/C][C]0.252059[/C][C]-0.880392[/C][/ROW]
[ROW][C]19[/C][C]267.15[/C][C]266.977[/C][C]264.997[/C][C]1.98015[/C][C]0.17318[/C][/ROW]
[ROW][C]20[/C][C]265.47[/C][C]263.864[/C][C]262.195[/C][C]1.66992[/C][C]1.6055[/C][/ROW]
[ROW][C]21[/C][C]261.75[/C][C]260.671[/C][C]259.419[/C][C]1.25134[/C][C]1.07949[/C][/ROW]
[ROW][C]22[/C][C]256.51[/C][C]257.097[/C][C]256.754[/C][C]0.34313[/C][C]-0.587297[/C][/ROW]
[ROW][C]23[/C][C]252.98[/C][C]253.882[/C][C]254.166[/C][C]-0.284668[/C][C]-0.901582[/C][/ROW]
[ROW][C]24[/C][C]251.17[/C][C]251.173[/C][C]251.577[/C][C]-0.404013[/C][C]-0.0034871[/C][/ROW]
[ROW][C]25[/C][C]251.17[/C][C]249.837[/C][C]248.974[/C][C]0.863309[/C][C]1.33252[/C][/ROW]
[ROW][C]26[/C][C]244.27[/C][C]245.253[/C][C]246.253[/C][C]-0.999846[/C][C]-0.983487[/C][/ROW]
[ROW][C]27[/C][C]240.54[/C][C]241.175[/C][C]243.3[/C][C]-2.12562[/C][C]-0.634797[/C][/ROW]
[ROW][C]28[/C][C]238.92[/C][C]238.708[/C][C]240.337[/C][C]-1.62877[/C][C]0.212108[/C][/ROW]
[ROW][C]29[/C][C]237.47[/C][C]236.576[/C][C]237.493[/C][C]-0.916989[/C][C]0.893656[/C][/ROW]
[ROW][C]30[/C][C]235.91[/C][C]234.943[/C][C]234.691[/C][C]0.252059[/C][C]0.967108[/C][/ROW]
[ROW][C]31[/C][C]235.91[/C][C]233.893[/C][C]231.912[/C][C]1.98015[/C][C]2.01735[/C][/ROW]
[ROW][C]32[/C][C]231.41[/C][C]231.052[/C][C]229.382[/C][C]1.66992[/C][C]0.357584[/C][/ROW]
[ROW][C]33[/C][C]224.94[/C][C]228.381[/C][C]227.129[/C][C]1.25134[/C][C]-3.44051[/C][/ROW]
[ROW][C]34[/C][C]222.19[/C][C]225.276[/C][C]224.932[/C][C]0.34313[/C][C]-3.08563[/C][/ROW]
[ROW][C]35[/C][C]219.06[/C][C]222.585[/C][C]222.87[/C][C]-0.284668[/C][C]-3.52492[/C][/ROW]
[ROW][C]36[/C][C]217.83[/C][C]220.628[/C][C]221.033[/C][C]-0.404013[/C][C]-2.79849[/C][/ROW]
[ROW][C]37[/C][C]217.83[/C][C]220.179[/C][C]219.316[/C][C]0.863309[/C][C]-2.34914[/C][/ROW]
[ROW][C]38[/C][C]216.89[/C][C]216.736[/C][C]217.736[/C][C]-0.999846[/C][C]0.154013[/C][/ROW]
[ROW][C]39[/C][C]213.84[/C][C]214.421[/C][C]216.546[/C][C]-2.12562[/C][C]-0.58063[/C][/ROW]
[ROW][C]40[/C][C]212.9[/C][C]214.006[/C][C]215.635[/C][C]-1.62877[/C][C]-1.10581[/C][/ROW]
[ROW][C]41[/C][C]213.98[/C][C]213.871[/C][C]214.788[/C][C]-0.916989[/C][C]0.108656[/C][/ROW]
[ROW][C]42[/C][C]215.31[/C][C]214.2[/C][C]213.948[/C][C]0.252059[/C][C]1.10961[/C][/ROW]
[ROW][C]43[/C][C]215.31[/C][C]215.053[/C][C]213.073[/C][C]1.98015[/C][C]0.256513[/C][/ROW]
[ROW][C]44[/C][C]214.09[/C][C]213.717[/C][C]212.047[/C][C]1.66992[/C][C]0.373418[/C][/ROW]
[ROW][C]45[/C][C]213.71[/C][C]212.143[/C][C]210.892[/C][C]1.25134[/C][C]1.56699[/C][/ROW]
[ROW][C]46[/C][C]211.54[/C][C]210.089[/C][C]209.746[/C][C]0.34313[/C][C]1.45062[/C][/ROW]
[ROW][C]47[/C][C]209.4[/C][C]208.25[/C][C]208.535[/C][C]-0.284668[/C][C]1.14967[/C][/ROW]
[ROW][C]48[/C][C]207.33[/C][C]206.796[/C][C]207.2[/C][C]-0.404013[/C][C]0.534013[/C][/ROW]
[ROW][C]49[/C][C]207.33[/C][C]206.657[/C][C]205.793[/C][C]0.863309[/C][C]0.673358[/C][/ROW]
[ROW][C]50[/C][C]202.75[/C][C]203.323[/C][C]204.323[/C][C]-0.999846[/C][C]-0.57307[/C][/ROW]
[ROW][C]51[/C][C]200.26[/C][C]200.669[/C][C]202.795[/C][C]-2.12562[/C][C]-0.40938[/C][/ROW]
[ROW][C]52[/C][C]198.99[/C][C]199.66[/C][C]201.289[/C][C]-1.62877[/C][C]-0.669975[/C][/ROW]
[ROW][C]53[/C][C]198.82[/C][C]198.876[/C][C]199.792[/C][C]-0.916989[/C][C]-0.0555109[/C][/ROW]
[ROW][C]54[/C][C]198.43[/C][C]198.56[/C][C]198.307[/C][C]0.252059[/C][C]-0.129559[/C][/ROW]
[ROW][C]55[/C][C]198.43[/C][C]198.819[/C][C]196.839[/C][C]1.98015[/C][C]-0.38932[/C][/ROW]
[ROW][C]56[/C][C]195.68[/C][C]197.056[/C][C]195.386[/C][C]1.66992[/C][C]-1.37575[/C][/ROW]
[ROW][C]57[/C][C]195.45[/C][C]195.199[/C][C]193.948[/C][C]1.25134[/C][C]0.250739[/C][/ROW]
[ROW][C]58[/C][C]193.65[/C][C]192.88[/C][C]192.537[/C][C]0.34313[/C][C]0.769787[/C][/ROW]
[ROW][C]59[/C][C]191.38[/C][C]190.843[/C][C]191.128[/C][C]-0.284668[/C][C]0.537168[/C][/ROW]
[ROW][C]60[/C][C]189.71[/C][C]189.327[/C][C]189.731[/C][C]-0.404013[/C][C]0.38318[/C][/ROW]
[ROW][C]61[/C][C]189.71[/C][C]189.236[/C][C]188.372[/C][C]0.863309[/C][C]0.474191[/C][/ROW]
[ROW][C]62[/C][C]185.49[/C][C]186.074[/C][C]187.074[/C][C]-0.999846[/C][C]-0.583904[/C][/ROW]
[ROW][C]63[/C][C]183.01[/C][C]183.695[/C][C]185.821[/C][C]-2.12562[/C][C]-0.685213[/C][/ROW]
[ROW][C]64[/C][C]182.38[/C][C]182.983[/C][C]184.612[/C][C]-1.62877[/C][C]-0.603309[/C][/ROW]
[ROW][C]65[/C][C]181.6[/C][C]182.583[/C][C]183.5[/C][C]-0.916989[/C][C]-0.983011[/C][/ROW]
[ROW][C]66[/C][C]182.13[/C][C]182.732[/C][C]182.48[/C][C]0.252059[/C][C]-0.602059[/C][/ROW]
[ROW][C]67[/C][C]182.13[/C][C]183.493[/C][C]181.513[/C][C]1.98015[/C][C]-1.36349[/C][/ROW]
[ROW][C]68[/C][C]180.81[/C][C]182.392[/C][C]180.722[/C][C]1.66992[/C][C]-1.582[/C][/ROW]
[ROW][C]69[/C][C]180.25[/C][C]181.437[/C][C]180.185[/C][C]1.25134[/C][C]-1.18676[/C][/ROW]
[ROW][C]70[/C][C]179.84[/C][C]180.09[/C][C]179.747[/C][C]0.34313[/C][C]-0.249797[/C][/ROW]
[ROW][C]71[/C][C]178.5[/C][C]178.999[/C][C]179.284[/C][C]-0.284668[/C][C]-0.499082[/C][/ROW]
[ROW][C]72[/C][C]178.11[/C][C]178.372[/C][C]178.776[/C][C]-0.404013[/C][C]-0.26182[/C][/ROW]
[ROW][C]73[/C][C]178.11[/C][C]179.126[/C][C]178.263[/C][C]0.863309[/C][C]-1.01623[/C][/ROW]
[ROW][C]74[/C][C]178.1[/C][C]176.783[/C][C]177.782[/C][C]-0.999846[/C][C]1.31735[/C][/ROW]
[ROW][C]75[/C][C]177.52[/C][C]175.236[/C][C]177.361[/C][C]-2.12562[/C][C]2.28437[/C][/ROW]
[ROW][C]76[/C][C]177.34[/C][C]175.28[/C][C]176.909[/C][C]-1.62877[/C][C]2.05961[/C][/ROW]
[ROW][C]77[/C][C]175.53[/C][C]175.541[/C][C]176.458[/C][C]-0.916989[/C][C]-0.0105109[/C][/ROW]
[ROW][C]78[/C][C]176.01[/C][C]176.325[/C][C]176.073[/C][C]0.252059[/C][C]-0.315392[/C][/ROW]
[ROW][C]79[/C][C]175.94[/C][C]177.613[/C][C]175.633[/C][C]1.98015[/C][C]-1.67307[/C][/ROW]
[ROW][C]80[/C][C]175.47[/C][C]176.773[/C][C]175.103[/C][C]1.66992[/C][C]-1.30325[/C][/ROW]
[ROW][C]81[/C][C]175.48[/C][C]175.783[/C][C]174.532[/C][C]1.25134[/C][C]-0.303428[/C][/ROW]
[ROW][C]82[/C][C]173.76[/C][C]174.336[/C][C]173.992[/C][C]0.34313[/C][C]-0.57563[/C][/ROW]
[ROW][C]83[/C][C]173.74[/C][C]173.294[/C][C]173.578[/C][C]-0.284668[/C][C]0.446334[/C][/ROW]
[ROW][C]84[/C][C]173.65[/C][C]172.782[/C][C]173.186[/C][C]-0.404013[/C][C]0.86818[/C][/ROW]
[ROW][C]85[/C][C]172[/C][C]173.597[/C][C]172.733[/C][C]0.863309[/C][C]-1.59664[/C][/ROW]
[ROW][C]86[/C][C]171.5[/C][C]171.271[/C][C]172.27[/C][C]-0.999846[/C][C]0.22943[/C][/ROW]
[ROW][C]87[/C][C]170.41[/C][C]169.693[/C][C]171.819[/C][C]-2.12562[/C][C]0.71687[/C][/ROW]
[ROW][C]88[/C][C]171.5[/C][C]169.837[/C][C]171.465[/C][C]-1.62877[/C][C]1.66336[/C][/ROW]
[ROW][C]89[/C][C]171.43[/C][C]170.258[/C][C]171.175[/C][C]-0.916989[/C][C]1.17199[/C][/ROW]
[ROW][C]90[/C][C]170.69[/C][C]171.091[/C][C]170.839[/C][C]0.252059[/C][C]-0.400809[/C][/ROW]
[ROW][C]91[/C][C]170.4[/C][C]NA[/C][C]NA[/C][C]1.98015[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]169.9[/C][C]NA[/C][C]NA[/C][C]1.66992[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]170.21[/C][C]NA[/C][C]NA[/C][C]1.25134[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]170.55[/C][C]NA[/C][C]NA[/C][C]0.34313[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]169.98[/C][C]NA[/C][C]NA[/C][C]-0.284668[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]169.34[/C][C]NA[/C][C]NA[/C][C]-0.404013[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279114&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279114&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
1299.81NANA0.863309NA
2299.01NANA-0.999846NA
3296.82NANA-2.12562NA
4296.67NANA-1.62877NA
5296.95NANA-0.916989NA
6296.8NANA0.252059NA
7296.8296.073294.0921.980150.727346
8295.93294.257292.5871.669921.673
9293.77291.988290.7371.251341.78199
10291.02288.994288.650.343132.02645
11288.61286.069286.354-0.2846682.54092
12284.55283.523283.927-0.4040131.02693
13284.55282.32281.4560.8633092.23044
14278.14277.952278.952-0.9998460.18818
15273.28274.223276.348-2.12562-0.942713
16270.14271.947273.576-1.62877-1.80748
17268.36269.737270.654-0.916989-1.37676
18267.15268.03267.7780.252059-0.880392
19267.15266.977264.9971.980150.17318
20265.47263.864262.1951.669921.6055
21261.75260.671259.4191.251341.07949
22256.51257.097256.7540.34313-0.587297
23252.98253.882254.166-0.284668-0.901582
24251.17251.173251.577-0.404013-0.0034871
25251.17249.837248.9740.8633091.33252
26244.27245.253246.253-0.999846-0.983487
27240.54241.175243.3-2.12562-0.634797
28238.92238.708240.337-1.628770.212108
29237.47236.576237.493-0.9169890.893656
30235.91234.943234.6910.2520590.967108
31235.91233.893231.9121.980152.01735
32231.41231.052229.3821.669920.357584
33224.94228.381227.1291.25134-3.44051
34222.19225.276224.9320.34313-3.08563
35219.06222.585222.87-0.284668-3.52492
36217.83220.628221.033-0.404013-2.79849
37217.83220.179219.3160.863309-2.34914
38216.89216.736217.736-0.9998460.154013
39213.84214.421216.546-2.12562-0.58063
40212.9214.006215.635-1.62877-1.10581
41213.98213.871214.788-0.9169890.108656
42215.31214.2213.9480.2520591.10961
43215.31215.053213.0731.980150.256513
44214.09213.717212.0471.669920.373418
45213.71212.143210.8921.251341.56699
46211.54210.089209.7460.343131.45062
47209.4208.25208.535-0.2846681.14967
48207.33206.796207.2-0.4040130.534013
49207.33206.657205.7930.8633090.673358
50202.75203.323204.323-0.999846-0.57307
51200.26200.669202.795-2.12562-0.40938
52198.99199.66201.289-1.62877-0.669975
53198.82198.876199.792-0.916989-0.0555109
54198.43198.56198.3070.252059-0.129559
55198.43198.819196.8391.98015-0.38932
56195.68197.056195.3861.66992-1.37575
57195.45195.199193.9481.251340.250739
58193.65192.88192.5370.343130.769787
59191.38190.843191.128-0.2846680.537168
60189.71189.327189.731-0.4040130.38318
61189.71189.236188.3720.8633090.474191
62185.49186.074187.074-0.999846-0.583904
63183.01183.695185.821-2.12562-0.685213
64182.38182.983184.612-1.62877-0.603309
65181.6182.583183.5-0.916989-0.983011
66182.13182.732182.480.252059-0.602059
67182.13183.493181.5131.98015-1.36349
68180.81182.392180.7221.66992-1.582
69180.25181.437180.1851.25134-1.18676
70179.84180.09179.7470.34313-0.249797
71178.5178.999179.284-0.284668-0.499082
72178.11178.372178.776-0.404013-0.26182
73178.11179.126178.2630.863309-1.01623
74178.1176.783177.782-0.9998461.31735
75177.52175.236177.361-2.125622.28437
76177.34175.28176.909-1.628772.05961
77175.53175.541176.458-0.916989-0.0105109
78176.01176.325176.0730.252059-0.315392
79175.94177.613175.6331.98015-1.67307
80175.47176.773175.1031.66992-1.30325
81175.48175.783174.5321.25134-0.303428
82173.76174.336173.9920.34313-0.57563
83173.74173.294173.578-0.2846680.446334
84173.65172.782173.186-0.4040130.86818
85172173.597172.7330.863309-1.59664
86171.5171.271172.27-0.9998460.22943
87170.41169.693171.819-2.125620.71687
88171.5169.837171.465-1.628771.66336
89171.43170.258171.175-0.9169891.17199
90170.69171.091170.8390.252059-0.400809
91170.4NANA1.98015NA
92169.9NANA1.66992NA
93170.21NANA1.25134NA
94170.55NANA0.34313NA
95169.98NANA-0.284668NA
96169.34NANA-0.404013NA


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')