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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 12:09:21 -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/12/t138686823357s7nxhcmw6tik5.htm/, Retrieved Tue, 07 Dec 2021 11:25:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232261, Retrieved Tue, 07 Dec 2021 11:25:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact45
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 17:09:21] [4b42de28d069c82084b3ad7a06d83fce] [Current]
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Dataseries X:
41086
39690
43129
37863
35953
29133
24693
22205
21725
27192
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232261&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232261&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232261&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 time5 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
141086NANA1.32719NA
239690NANA1.20085NA
343129NANA1.32843NA
437863NANA1.22345NA
535953NANA1.01798NA
629133NANA1.0534NA
72469326076.929668.30.8789480.946929
82220522272.229138.70.764350.996983
92172523606.128311.80.8337890.920313
102719228306.427554.71.027280.96063
112179021346.126986.40.7909961.02079
121325314776.626704.40.553340.896891
133770235460.526718.51.327191.06321
143036432151.4267741.200850.944405
153260935511.526731.91.328430.918265
163021232725.326748.31.223450.923201
172996527316.426833.81.017981.09696
182835228317.4268821.05341.00122
192581423622.826876.20.8789481.09276
202241420673.927047.80.764351.08417
212050622808.827355.50.8337890.899041
222880628400.527646.31.027281.01428
232222821917.127708.20.7909961.01418
241397115160.127397.40.553340.921565
253684535951.427088.41.327191.02486
263533832123.9267511.200851.10005
273502235305.226576.61.328430.991977
283477732343.426436.21.223451.07524
292688726527.126058.51.017981.01357
302397027130.625755.41.05340.883504
312278022352.425430.90.8789481.01913
32173511900524864.30.764350.912969
332138220251.224288.20.8337891.05584
342456124341.623695.21.027281.00901
35174091830923146.80.7909960.950845
361151412701.622954.40.553340.906502
373151430398.222904.31.327191.0367
382707127487.722890.21.200850.98484
392946230414.822895.21.328430.968672
402610528018.2229011.223450.931716
412239723357.322944.71.017980.958886
422384324359.923125.11.05340.978782
432170520345.9231480.8789481.0668
441808917655.823099.10.764351.02454
452076419582.423486.10.8337891.06034
462531624679.224023.81.027281.0258
471770419207.424282.60.7909960.921727
48155481345424314.20.553341.15564
492802932091.124179.81.327190.87342
502938328823.424002.61.200851.01941
513643831833.3239631.328431.14465
523203429168.123840.81.223451.09825
532267924224.223796.31.017980.936212
542431925054.823784.81.05340.970633
551800420904.623783.70.8789480.861245
561753718112.923697.10.764350.968207
572036619371.623233.20.8337891.05133
582278223315.122695.91.027280.977136
591916917760.422453.20.7909961.07931
601380712480.722555.30.553341.10626
612974330083.922667.41.327190.988669
622559127278.122715.71.200850.938152
632909630204.6227371.328430.963297
642648227630.122583.71.223450.958449
652240522833.422430.11.017980.981237
66270442346122271.81.05341.15272
6717970NANA0.878948NA
6818730NANA0.76435NA
6919684NANA0.833789NA
7019785NANA1.02728NA
7118479NANA0.790996NA
7210698NANA0.55334NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 41086 & NA & NA & 1.32719 & NA \tabularnewline
2 & 39690 & NA & NA & 1.20085 & NA \tabularnewline
3 & 43129 & NA & NA & 1.32843 & NA \tabularnewline
4 & 37863 & NA & NA & 1.22345 & NA \tabularnewline
5 & 35953 & NA & NA & 1.01798 & NA \tabularnewline
6 & 29133 & NA & NA & 1.0534 & NA \tabularnewline
7 & 24693 & 26076.9 & 29668.3 & 0.878948 & 0.946929 \tabularnewline
8 & 22205 & 22272.2 & 29138.7 & 0.76435 & 0.996983 \tabularnewline
9 & 21725 & 23606.1 & 28311.8 & 0.833789 & 0.920313 \tabularnewline
10 & 27192 & 28306.4 & 27554.7 & 1.02728 & 0.96063 \tabularnewline
11 & 21790 & 21346.1 & 26986.4 & 0.790996 & 1.02079 \tabularnewline
12 & 13253 & 14776.6 & 26704.4 & 0.55334 & 0.896891 \tabularnewline
13 & 37702 & 35460.5 & 26718.5 & 1.32719 & 1.06321 \tabularnewline
14 & 30364 & 32151.4 & 26774 & 1.20085 & 0.944405 \tabularnewline
15 & 32609 & 35511.5 & 26731.9 & 1.32843 & 0.918265 \tabularnewline
16 & 30212 & 32725.3 & 26748.3 & 1.22345 & 0.923201 \tabularnewline
17 & 29965 & 27316.4 & 26833.8 & 1.01798 & 1.09696 \tabularnewline
18 & 28352 & 28317.4 & 26882 & 1.0534 & 1.00122 \tabularnewline
19 & 25814 & 23622.8 & 26876.2 & 0.878948 & 1.09276 \tabularnewline
20 & 22414 & 20673.9 & 27047.8 & 0.76435 & 1.08417 \tabularnewline
21 & 20506 & 22808.8 & 27355.5 & 0.833789 & 0.899041 \tabularnewline
22 & 28806 & 28400.5 & 27646.3 & 1.02728 & 1.01428 \tabularnewline
23 & 22228 & 21917.1 & 27708.2 & 0.790996 & 1.01418 \tabularnewline
24 & 13971 & 15160.1 & 27397.4 & 0.55334 & 0.921565 \tabularnewline
25 & 36845 & 35951.4 & 27088.4 & 1.32719 & 1.02486 \tabularnewline
26 & 35338 & 32123.9 & 26751 & 1.20085 & 1.10005 \tabularnewline
27 & 35022 & 35305.2 & 26576.6 & 1.32843 & 0.991977 \tabularnewline
28 & 34777 & 32343.4 & 26436.2 & 1.22345 & 1.07524 \tabularnewline
29 & 26887 & 26527.1 & 26058.5 & 1.01798 & 1.01357 \tabularnewline
30 & 23970 & 27130.6 & 25755.4 & 1.0534 & 0.883504 \tabularnewline
31 & 22780 & 22352.4 & 25430.9 & 0.878948 & 1.01913 \tabularnewline
32 & 17351 & 19005 & 24864.3 & 0.76435 & 0.912969 \tabularnewline
33 & 21382 & 20251.2 & 24288.2 & 0.833789 & 1.05584 \tabularnewline
34 & 24561 & 24341.6 & 23695.2 & 1.02728 & 1.00901 \tabularnewline
35 & 17409 & 18309 & 23146.8 & 0.790996 & 0.950845 \tabularnewline
36 & 11514 & 12701.6 & 22954.4 & 0.55334 & 0.906502 \tabularnewline
37 & 31514 & 30398.2 & 22904.3 & 1.32719 & 1.0367 \tabularnewline
38 & 27071 & 27487.7 & 22890.2 & 1.20085 & 0.98484 \tabularnewline
39 & 29462 & 30414.8 & 22895.2 & 1.32843 & 0.968672 \tabularnewline
40 & 26105 & 28018.2 & 22901 & 1.22345 & 0.931716 \tabularnewline
41 & 22397 & 23357.3 & 22944.7 & 1.01798 & 0.958886 \tabularnewline
42 & 23843 & 24359.9 & 23125.1 & 1.0534 & 0.978782 \tabularnewline
43 & 21705 & 20345.9 & 23148 & 0.878948 & 1.0668 \tabularnewline
44 & 18089 & 17655.8 & 23099.1 & 0.76435 & 1.02454 \tabularnewline
45 & 20764 & 19582.4 & 23486.1 & 0.833789 & 1.06034 \tabularnewline
46 & 25316 & 24679.2 & 24023.8 & 1.02728 & 1.0258 \tabularnewline
47 & 17704 & 19207.4 & 24282.6 & 0.790996 & 0.921727 \tabularnewline
48 & 15548 & 13454 & 24314.2 & 0.55334 & 1.15564 \tabularnewline
49 & 28029 & 32091.1 & 24179.8 & 1.32719 & 0.87342 \tabularnewline
50 & 29383 & 28823.4 & 24002.6 & 1.20085 & 1.01941 \tabularnewline
51 & 36438 & 31833.3 & 23963 & 1.32843 & 1.14465 \tabularnewline
52 & 32034 & 29168.1 & 23840.8 & 1.22345 & 1.09825 \tabularnewline
53 & 22679 & 24224.2 & 23796.3 & 1.01798 & 0.936212 \tabularnewline
54 & 24319 & 25054.8 & 23784.8 & 1.0534 & 0.970633 \tabularnewline
55 & 18004 & 20904.6 & 23783.7 & 0.878948 & 0.861245 \tabularnewline
56 & 17537 & 18112.9 & 23697.1 & 0.76435 & 0.968207 \tabularnewline
57 & 20366 & 19371.6 & 23233.2 & 0.833789 & 1.05133 \tabularnewline
58 & 22782 & 23315.1 & 22695.9 & 1.02728 & 0.977136 \tabularnewline
59 & 19169 & 17760.4 & 22453.2 & 0.790996 & 1.07931 \tabularnewline
60 & 13807 & 12480.7 & 22555.3 & 0.55334 & 1.10626 \tabularnewline
61 & 29743 & 30083.9 & 22667.4 & 1.32719 & 0.988669 \tabularnewline
62 & 25591 & 27278.1 & 22715.7 & 1.20085 & 0.938152 \tabularnewline
63 & 29096 & 30204.6 & 22737 & 1.32843 & 0.963297 \tabularnewline
64 & 26482 & 27630.1 & 22583.7 & 1.22345 & 0.958449 \tabularnewline
65 & 22405 & 22833.4 & 22430.1 & 1.01798 & 0.981237 \tabularnewline
66 & 27044 & 23461 & 22271.8 & 1.0534 & 1.15272 \tabularnewline
67 & 17970 & NA & NA & 0.878948 & NA \tabularnewline
68 & 18730 & NA & NA & 0.76435 & NA \tabularnewline
69 & 19684 & NA & NA & 0.833789 & NA \tabularnewline
70 & 19785 & NA & NA & 1.02728 & NA \tabularnewline
71 & 18479 & NA & NA & 0.790996 & NA \tabularnewline
72 & 10698 & NA & NA & 0.55334 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232261&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]41086[/C][C]NA[/C][C]NA[/C][C]1.32719[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]39690[/C][C]NA[/C][C]NA[/C][C]1.20085[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]43129[/C][C]NA[/C][C]NA[/C][C]1.32843[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]37863[/C][C]NA[/C][C]NA[/C][C]1.22345[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]35953[/C][C]NA[/C][C]NA[/C][C]1.01798[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]29133[/C][C]NA[/C][C]NA[/C][C]1.0534[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]24693[/C][C]26076.9[/C][C]29668.3[/C][C]0.878948[/C][C]0.946929[/C][/ROW]
[ROW][C]8[/C][C]22205[/C][C]22272.2[/C][C]29138.7[/C][C]0.76435[/C][C]0.996983[/C][/ROW]
[ROW][C]9[/C][C]21725[/C][C]23606.1[/C][C]28311.8[/C][C]0.833789[/C][C]0.920313[/C][/ROW]
[ROW][C]10[/C][C]27192[/C][C]28306.4[/C][C]27554.7[/C][C]1.02728[/C][C]0.96063[/C][/ROW]
[ROW][C]11[/C][C]21790[/C][C]21346.1[/C][C]26986.4[/C][C]0.790996[/C][C]1.02079[/C][/ROW]
[ROW][C]12[/C][C]13253[/C][C]14776.6[/C][C]26704.4[/C][C]0.55334[/C][C]0.896891[/C][/ROW]
[ROW][C]13[/C][C]37702[/C][C]35460.5[/C][C]26718.5[/C][C]1.32719[/C][C]1.06321[/C][/ROW]
[ROW][C]14[/C][C]30364[/C][C]32151.4[/C][C]26774[/C][C]1.20085[/C][C]0.944405[/C][/ROW]
[ROW][C]15[/C][C]32609[/C][C]35511.5[/C][C]26731.9[/C][C]1.32843[/C][C]0.918265[/C][/ROW]
[ROW][C]16[/C][C]30212[/C][C]32725.3[/C][C]26748.3[/C][C]1.22345[/C][C]0.923201[/C][/ROW]
[ROW][C]17[/C][C]29965[/C][C]27316.4[/C][C]26833.8[/C][C]1.01798[/C][C]1.09696[/C][/ROW]
[ROW][C]18[/C][C]28352[/C][C]28317.4[/C][C]26882[/C][C]1.0534[/C][C]1.00122[/C][/ROW]
[ROW][C]19[/C][C]25814[/C][C]23622.8[/C][C]26876.2[/C][C]0.878948[/C][C]1.09276[/C][/ROW]
[ROW][C]20[/C][C]22414[/C][C]20673.9[/C][C]27047.8[/C][C]0.76435[/C][C]1.08417[/C][/ROW]
[ROW][C]21[/C][C]20506[/C][C]22808.8[/C][C]27355.5[/C][C]0.833789[/C][C]0.899041[/C][/ROW]
[ROW][C]22[/C][C]28806[/C][C]28400.5[/C][C]27646.3[/C][C]1.02728[/C][C]1.01428[/C][/ROW]
[ROW][C]23[/C][C]22228[/C][C]21917.1[/C][C]27708.2[/C][C]0.790996[/C][C]1.01418[/C][/ROW]
[ROW][C]24[/C][C]13971[/C][C]15160.1[/C][C]27397.4[/C][C]0.55334[/C][C]0.921565[/C][/ROW]
[ROW][C]25[/C][C]36845[/C][C]35951.4[/C][C]27088.4[/C][C]1.32719[/C][C]1.02486[/C][/ROW]
[ROW][C]26[/C][C]35338[/C][C]32123.9[/C][C]26751[/C][C]1.20085[/C][C]1.10005[/C][/ROW]
[ROW][C]27[/C][C]35022[/C][C]35305.2[/C][C]26576.6[/C][C]1.32843[/C][C]0.991977[/C][/ROW]
[ROW][C]28[/C][C]34777[/C][C]32343.4[/C][C]26436.2[/C][C]1.22345[/C][C]1.07524[/C][/ROW]
[ROW][C]29[/C][C]26887[/C][C]26527.1[/C][C]26058.5[/C][C]1.01798[/C][C]1.01357[/C][/ROW]
[ROW][C]30[/C][C]23970[/C][C]27130.6[/C][C]25755.4[/C][C]1.0534[/C][C]0.883504[/C][/ROW]
[ROW][C]31[/C][C]22780[/C][C]22352.4[/C][C]25430.9[/C][C]0.878948[/C][C]1.01913[/C][/ROW]
[ROW][C]32[/C][C]17351[/C][C]19005[/C][C]24864.3[/C][C]0.76435[/C][C]0.912969[/C][/ROW]
[ROW][C]33[/C][C]21382[/C][C]20251.2[/C][C]24288.2[/C][C]0.833789[/C][C]1.05584[/C][/ROW]
[ROW][C]34[/C][C]24561[/C][C]24341.6[/C][C]23695.2[/C][C]1.02728[/C][C]1.00901[/C][/ROW]
[ROW][C]35[/C][C]17409[/C][C]18309[/C][C]23146.8[/C][C]0.790996[/C][C]0.950845[/C][/ROW]
[ROW][C]36[/C][C]11514[/C][C]12701.6[/C][C]22954.4[/C][C]0.55334[/C][C]0.906502[/C][/ROW]
[ROW][C]37[/C][C]31514[/C][C]30398.2[/C][C]22904.3[/C][C]1.32719[/C][C]1.0367[/C][/ROW]
[ROW][C]38[/C][C]27071[/C][C]27487.7[/C][C]22890.2[/C][C]1.20085[/C][C]0.98484[/C][/ROW]
[ROW][C]39[/C][C]29462[/C][C]30414.8[/C][C]22895.2[/C][C]1.32843[/C][C]0.968672[/C][/ROW]
[ROW][C]40[/C][C]26105[/C][C]28018.2[/C][C]22901[/C][C]1.22345[/C][C]0.931716[/C][/ROW]
[ROW][C]41[/C][C]22397[/C][C]23357.3[/C][C]22944.7[/C][C]1.01798[/C][C]0.958886[/C][/ROW]
[ROW][C]42[/C][C]23843[/C][C]24359.9[/C][C]23125.1[/C][C]1.0534[/C][C]0.978782[/C][/ROW]
[ROW][C]43[/C][C]21705[/C][C]20345.9[/C][C]23148[/C][C]0.878948[/C][C]1.0668[/C][/ROW]
[ROW][C]44[/C][C]18089[/C][C]17655.8[/C][C]23099.1[/C][C]0.76435[/C][C]1.02454[/C][/ROW]
[ROW][C]45[/C][C]20764[/C][C]19582.4[/C][C]23486.1[/C][C]0.833789[/C][C]1.06034[/C][/ROW]
[ROW][C]46[/C][C]25316[/C][C]24679.2[/C][C]24023.8[/C][C]1.02728[/C][C]1.0258[/C][/ROW]
[ROW][C]47[/C][C]17704[/C][C]19207.4[/C][C]24282.6[/C][C]0.790996[/C][C]0.921727[/C][/ROW]
[ROW][C]48[/C][C]15548[/C][C]13454[/C][C]24314.2[/C][C]0.55334[/C][C]1.15564[/C][/ROW]
[ROW][C]49[/C][C]28029[/C][C]32091.1[/C][C]24179.8[/C][C]1.32719[/C][C]0.87342[/C][/ROW]
[ROW][C]50[/C][C]29383[/C][C]28823.4[/C][C]24002.6[/C][C]1.20085[/C][C]1.01941[/C][/ROW]
[ROW][C]51[/C][C]36438[/C][C]31833.3[/C][C]23963[/C][C]1.32843[/C][C]1.14465[/C][/ROW]
[ROW][C]52[/C][C]32034[/C][C]29168.1[/C][C]23840.8[/C][C]1.22345[/C][C]1.09825[/C][/ROW]
[ROW][C]53[/C][C]22679[/C][C]24224.2[/C][C]23796.3[/C][C]1.01798[/C][C]0.936212[/C][/ROW]
[ROW][C]54[/C][C]24319[/C][C]25054.8[/C][C]23784.8[/C][C]1.0534[/C][C]0.970633[/C][/ROW]
[ROW][C]55[/C][C]18004[/C][C]20904.6[/C][C]23783.7[/C][C]0.878948[/C][C]0.861245[/C][/ROW]
[ROW][C]56[/C][C]17537[/C][C]18112.9[/C][C]23697.1[/C][C]0.76435[/C][C]0.968207[/C][/ROW]
[ROW][C]57[/C][C]20366[/C][C]19371.6[/C][C]23233.2[/C][C]0.833789[/C][C]1.05133[/C][/ROW]
[ROW][C]58[/C][C]22782[/C][C]23315.1[/C][C]22695.9[/C][C]1.02728[/C][C]0.977136[/C][/ROW]
[ROW][C]59[/C][C]19169[/C][C]17760.4[/C][C]22453.2[/C][C]0.790996[/C][C]1.07931[/C][/ROW]
[ROW][C]60[/C][C]13807[/C][C]12480.7[/C][C]22555.3[/C][C]0.55334[/C][C]1.10626[/C][/ROW]
[ROW][C]61[/C][C]29743[/C][C]30083.9[/C][C]22667.4[/C][C]1.32719[/C][C]0.988669[/C][/ROW]
[ROW][C]62[/C][C]25591[/C][C]27278.1[/C][C]22715.7[/C][C]1.20085[/C][C]0.938152[/C][/ROW]
[ROW][C]63[/C][C]29096[/C][C]30204.6[/C][C]22737[/C][C]1.32843[/C][C]0.963297[/C][/ROW]
[ROW][C]64[/C][C]26482[/C][C]27630.1[/C][C]22583.7[/C][C]1.22345[/C][C]0.958449[/C][/ROW]
[ROW][C]65[/C][C]22405[/C][C]22833.4[/C][C]22430.1[/C][C]1.01798[/C][C]0.981237[/C][/ROW]
[ROW][C]66[/C][C]27044[/C][C]23461[/C][C]22271.8[/C][C]1.0534[/C][C]1.15272[/C][/ROW]
[ROW][C]67[/C][C]17970[/C][C]NA[/C][C]NA[/C][C]0.878948[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]18730[/C][C]NA[/C][C]NA[/C][C]0.76435[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]19684[/C][C]NA[/C][C]NA[/C][C]0.833789[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]19785[/C][C]NA[/C][C]NA[/C][C]1.02728[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]18479[/C][C]NA[/C][C]NA[/C][C]0.790996[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]10698[/C][C]NA[/C][C]NA[/C][C]0.55334[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232261&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232261&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
141086NANA1.32719NA
239690NANA1.20085NA
343129NANA1.32843NA
437863NANA1.22345NA
535953NANA1.01798NA
629133NANA1.0534NA
72469326076.929668.30.8789480.946929
82220522272.229138.70.764350.996983
92172523606.128311.80.8337890.920313
102719228306.427554.71.027280.96063
112179021346.126986.40.7909961.02079
121325314776.626704.40.553340.896891
133770235460.526718.51.327191.06321
143036432151.4267741.200850.944405
153260935511.526731.91.328430.918265
163021232725.326748.31.223450.923201
172996527316.426833.81.017981.09696
182835228317.4268821.05341.00122
192581423622.826876.20.8789481.09276
202241420673.927047.80.764351.08417
212050622808.827355.50.8337890.899041
222880628400.527646.31.027281.01428
232222821917.127708.20.7909961.01418
241397115160.127397.40.553340.921565
253684535951.427088.41.327191.02486
263533832123.9267511.200851.10005
273502235305.226576.61.328430.991977
283477732343.426436.21.223451.07524
292688726527.126058.51.017981.01357
302397027130.625755.41.05340.883504
312278022352.425430.90.8789481.01913
32173511900524864.30.764350.912969
332138220251.224288.20.8337891.05584
342456124341.623695.21.027281.00901
35174091830923146.80.7909960.950845
361151412701.622954.40.553340.906502
373151430398.222904.31.327191.0367
382707127487.722890.21.200850.98484
392946230414.822895.21.328430.968672
402610528018.2229011.223450.931716
412239723357.322944.71.017980.958886
422384324359.923125.11.05340.978782
432170520345.9231480.8789481.0668
441808917655.823099.10.764351.02454
452076419582.423486.10.8337891.06034
462531624679.224023.81.027281.0258
471770419207.424282.60.7909960.921727
48155481345424314.20.553341.15564
492802932091.124179.81.327190.87342
502938328823.424002.61.200851.01941
513643831833.3239631.328431.14465
523203429168.123840.81.223451.09825
532267924224.223796.31.017980.936212
542431925054.823784.81.05340.970633
551800420904.623783.70.8789480.861245
561753718112.923697.10.764350.968207
572036619371.623233.20.8337891.05133
582278223315.122695.91.027280.977136
591916917760.422453.20.7909961.07931
601380712480.722555.30.553341.10626
612974330083.922667.41.327190.988669
622559127278.122715.71.200850.938152
632909630204.6227371.328430.963297
642648227630.122583.71.223450.958449
652240522833.422430.11.017980.981237
66270442346122271.81.05341.15272
6717970NANA0.878948NA
6818730NANA0.76435NA
6919684NANA0.833789NA
7019785NANA1.02728NA
7118479NANA0.790996NA
7210698NANA0.55334NA



Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
Parameters (R input):
par1 = multiplicative ; 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')