Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 01 Dec 2011 09:47:37 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/01/t1322751049y9tmkb66wwuwh4f.htm/, Retrieved Sat, 27 Apr 2024 00:37:02 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=149753, Retrieved Sat, 27 Apr 2024 00:37:02 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

108

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Univariate Data Series] [web server] [2010-10-19 15:51:23] [b98453cac15ba1066b407e146608df68]
- RMPD    [Classical Decomposition] [Classical Decompo...] [2011-12-01 14:47:37] [614dd89c388120cee0dd25886939832b] [Current]
- RMPD      [Univariate Explorative Data Analysis] [Sequence plot Wer...] [2011-12-01 15:29:03] [15a5dd358825f04074b70fc847ec6454] 
- RMPD      [Exponential Smoothing] [Exponential smoot...] [2011-12-01 19:00:51] [15a5dd358825f04074b70fc847ec6454] 
- RMPD      [Decomposition by Loess] [Decomposition by ...] [2011-12-01 19:34:10] [15a5dd358825f04074b70fc847ec6454] 

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149753&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]1 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=149753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149753&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	79717000	NA	NA	0.94850203730037	NA
2	82855667	NA	NA	0.989446704791798	NA
3	79346667	NA	NA	0.996972141895198	NA
4	76270333	NA	NA	1.00241126950128	NA
5	89532667	NA	NA	0.985955261922536	NA
6	83541333	NA	NA	0.984963621039131	NA
7	82456000	84526002.651883	86433875	0.977926798398001	0.975510463207302
8	85818333	86945467.1435982	87134666.6666667	0.997828653849193	0.987036309302513
9	92106667	91789769.711529	88033763.875	1.04266551458441	1.00345242492128
10	96873333	94373518.1195754	89503791.6666667	1.05440804643277	1.02648852061716
11	96580000	93243666.9929224	91090847.25	1.02363376571758	1.03578080007654
12	87769000	92169569.1996613	92606097.25	0.995286184567737	0.952255725638376
13	88396000	89540344.4415433	94401847.25	0.94850203730037	0.98721978959674
14	90995667	95152162.5278859	96167041.7083333	0.989446704791798	0.95631738241716
15	92785000	97319200.2625932	97614763.9166667	0.996972141895198	0.953408985581892
16	98112667	99397221.9626167	99158125	1.00241126950128	0.987076550659536
17	105779667	99766772.5606083	101187930.541667	0.985955261922536	1.06026950942749
18	103660333	102329334.327776	103891486.083333	0.984963621039131	1.0130070099739
19	105435000	104490459.694331	106848958.291667	0.977926798398001	1.00903948847035
20	105204000	109650476.012069	109889083.25	0.997828653849193	0.9594486392236
21	107466333	118310343.477234	113469124.875	1.04266551458441	0.908342667610286
22	118554333	123297570.877075	116935347.083333	1.05440804643277	0.961530159569778
23	123614333	121977393.591695	119161166.5	1.02363376571758	1.0134200228428
24	125620000	120368653.036944	120938735.916667	0.995286184567737	1.04362719720261
25	121524333	116586932.518943	122916902.583333	0.94850203730037	1.04234951871862
26	130830333	123711400.82965	125030888.708333	0.989446704791798	1.05754467351115
27	138871333	127182115.895678	127568374.833333	0.996972141895198	1.09190928317241
28	135215667	129818941.975144	129506666.5	1.00241126950128	1.04157116783381
29	122096333	128271478.525991	130098680.416667	0.985955261922536	0.951858779543579
30	130005333	127724281.92559	129674111	0.984963621039131	1.01785918104232
31	126566000	125591294.813986	128426069.333333	0.977926798398001	1.00776092950915
32	134808667	126185231.291392	126459819.333333	0.997828653849193	1.06833950075104
33	138761333	129170197.21042	123884597.125	1.04266551458441	1.07425192495414
34	133778333	127613014.082958	121028111	1.05440804643277	1.04831261890761
35	122598667	121635997.570561	118827652.666667	1.02363376571758	1.00791434648185
36	116446000	116188741.477974	116739027.708333	0.995286184567737	1.00221414328749
37	100745333	108731649.569162	114635124.958333	0.94850203730037	0.926550212373245
38	104419333	111477881.895286	112666888.833333	0.989446704791798	0.936682068449095
39	103477000	110294778.731749	110629749.916667	0.996972141895198	0.938185843335967
40	102054333	109166568.99332	108903972.166667	1.00241126950128	0.934849688334936
41	102446667	106034120.386345	107544555.5	0.985955261922536	0.966166990650991
42	99528000	105327207.854192	106935124.916667	0.984963621039131	0.94494102737234
43	106549667	105086886.369238	107458847.166667	0.977926798398001	1.0139197256794
44	107587333	108519936.230411	108756083.333333	0.997828653849193	0.991406157589048
45	117091333	114774766.246833	110078222.25	1.04266551458441	1.02018358938048
46	114029667	117568562.103611	111501958.375	1.05440804643277	0.969899307771642
47	109721333	115603780.814118	112934708.375	1.02363376571758	0.949115437465003
48	114697000	113771633.781839	114310472.25	0.995286184567737	1.00813354073772
49	115063667	109572852.353013	115522000	0.94850203730037	1.05011108617759
50	121234667	114839650.796881	116064513.875	0.989446704791798	1.05568648248879
51	118393000	115762132.500478	116113708.333333	0.996972141895198	1.02272649477593
52	121308000	116336566.243013	116056722.208333	1.00241126950128	1.04273320003792
53	117579000	114383655.161678	116013027.75	0.985955261922536	1.02793532724414
54	117414000	113947335.932921	115686847.208333	0.984963621039131	1.03042338847764
55	117740333	NA	NA	0.977926798398001	NA
56	109417000	NA	NA	0.997828653849193	NA
57	116442333	NA	NA	1.04266551458441	NA
58	113311000	NA	NA	1.05440804643277	NA
59	109391333	NA	NA	1.02363376571758	NA
60	107198667	NA	NA	0.995286184567737	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 79717000 & NA & NA & 0.94850203730037 & NA \tabularnewline
2 & 82855667 & NA & NA & 0.989446704791798 & NA \tabularnewline
3 & 79346667 & NA & NA & 0.996972141895198 & NA \tabularnewline
4 & 76270333 & NA & NA & 1.00241126950128 & NA \tabularnewline
5 & 89532667 & NA & NA & 0.985955261922536 & NA \tabularnewline
6 & 83541333 & NA & NA & 0.984963621039131 & NA \tabularnewline
7 & 82456000 & 84526002.651883 & 86433875 & 0.977926798398001 & 0.975510463207302 \tabularnewline
8 & 85818333 & 86945467.1435982 & 87134666.6666667 & 0.997828653849193 & 0.987036309302513 \tabularnewline
9 & 92106667 & 91789769.711529 & 88033763.875 & 1.04266551458441 & 1.00345242492128 \tabularnewline
10 & 96873333 & 94373518.1195754 & 89503791.6666667 & 1.05440804643277 & 1.02648852061716 \tabularnewline
11 & 96580000 & 93243666.9929224 & 91090847.25 & 1.02363376571758 & 1.03578080007654 \tabularnewline
12 & 87769000 & 92169569.1996613 & 92606097.25 & 0.995286184567737 & 0.952255725638376 \tabularnewline
13 & 88396000 & 89540344.4415433 & 94401847.25 & 0.94850203730037 & 0.98721978959674 \tabularnewline
14 & 90995667 & 95152162.5278859 & 96167041.7083333 & 0.989446704791798 & 0.95631738241716 \tabularnewline
15 & 92785000 & 97319200.2625932 & 97614763.9166667 & 0.996972141895198 & 0.953408985581892 \tabularnewline
16 & 98112667 & 99397221.9626167 & 99158125 & 1.00241126950128 & 0.987076550659536 \tabularnewline
17 & 105779667 & 99766772.5606083 & 101187930.541667 & 0.985955261922536 & 1.06026950942749 \tabularnewline
18 & 103660333 & 102329334.327776 & 103891486.083333 & 0.984963621039131 & 1.0130070099739 \tabularnewline
19 & 105435000 & 104490459.694331 & 106848958.291667 & 0.977926798398001 & 1.00903948847035 \tabularnewline
20 & 105204000 & 109650476.012069 & 109889083.25 & 0.997828653849193 & 0.9594486392236 \tabularnewline
21 & 107466333 & 118310343.477234 & 113469124.875 & 1.04266551458441 & 0.908342667610286 \tabularnewline
22 & 118554333 & 123297570.877075 & 116935347.083333 & 1.05440804643277 & 0.961530159569778 \tabularnewline
23 & 123614333 & 121977393.591695 & 119161166.5 & 1.02363376571758 & 1.0134200228428 \tabularnewline
24 & 125620000 & 120368653.036944 & 120938735.916667 & 0.995286184567737 & 1.04362719720261 \tabularnewline
25 & 121524333 & 116586932.518943 & 122916902.583333 & 0.94850203730037 & 1.04234951871862 \tabularnewline
26 & 130830333 & 123711400.82965 & 125030888.708333 & 0.989446704791798 & 1.05754467351115 \tabularnewline
27 & 138871333 & 127182115.895678 & 127568374.833333 & 0.996972141895198 & 1.09190928317241 \tabularnewline
28 & 135215667 & 129818941.975144 & 129506666.5 & 1.00241126950128 & 1.04157116783381 \tabularnewline
29 & 122096333 & 128271478.525991 & 130098680.416667 & 0.985955261922536 & 0.951858779543579 \tabularnewline
30 & 130005333 & 127724281.92559 & 129674111 & 0.984963621039131 & 1.01785918104232 \tabularnewline
31 & 126566000 & 125591294.813986 & 128426069.333333 & 0.977926798398001 & 1.00776092950915 \tabularnewline
32 & 134808667 & 126185231.291392 & 126459819.333333 & 0.997828653849193 & 1.06833950075104 \tabularnewline
33 & 138761333 & 129170197.21042 & 123884597.125 & 1.04266551458441 & 1.07425192495414 \tabularnewline
34 & 133778333 & 127613014.082958 & 121028111 & 1.05440804643277 & 1.04831261890761 \tabularnewline
35 & 122598667 & 121635997.570561 & 118827652.666667 & 1.02363376571758 & 1.00791434648185 \tabularnewline
36 & 116446000 & 116188741.477974 & 116739027.708333 & 0.995286184567737 & 1.00221414328749 \tabularnewline
37 & 100745333 & 108731649.569162 & 114635124.958333 & 0.94850203730037 & 0.926550212373245 \tabularnewline
38 & 104419333 & 111477881.895286 & 112666888.833333 & 0.989446704791798 & 0.936682068449095 \tabularnewline
39 & 103477000 & 110294778.731749 & 110629749.916667 & 0.996972141895198 & 0.938185843335967 \tabularnewline
40 & 102054333 & 109166568.99332 & 108903972.166667 & 1.00241126950128 & 0.934849688334936 \tabularnewline
41 & 102446667 & 106034120.386345 & 107544555.5 & 0.985955261922536 & 0.966166990650991 \tabularnewline
42 & 99528000 & 105327207.854192 & 106935124.916667 & 0.984963621039131 & 0.94494102737234 \tabularnewline
43 & 106549667 & 105086886.369238 & 107458847.166667 & 0.977926798398001 & 1.0139197256794 \tabularnewline
44 & 107587333 & 108519936.230411 & 108756083.333333 & 0.997828653849193 & 0.991406157589048 \tabularnewline
45 & 117091333 & 114774766.246833 & 110078222.25 & 1.04266551458441 & 1.02018358938048 \tabularnewline
46 & 114029667 & 117568562.103611 & 111501958.375 & 1.05440804643277 & 0.969899307771642 \tabularnewline
47 & 109721333 & 115603780.814118 & 112934708.375 & 1.02363376571758 & 0.949115437465003 \tabularnewline
48 & 114697000 & 113771633.781839 & 114310472.25 & 0.995286184567737 & 1.00813354073772 \tabularnewline
49 & 115063667 & 109572852.353013 & 115522000 & 0.94850203730037 & 1.05011108617759 \tabularnewline
50 & 121234667 & 114839650.796881 & 116064513.875 & 0.989446704791798 & 1.05568648248879 \tabularnewline
51 & 118393000 & 115762132.500478 & 116113708.333333 & 0.996972141895198 & 1.02272649477593 \tabularnewline
52 & 121308000 & 116336566.243013 & 116056722.208333 & 1.00241126950128 & 1.04273320003792 \tabularnewline
53 & 117579000 & 114383655.161678 & 116013027.75 & 0.985955261922536 & 1.02793532724414 \tabularnewline
54 & 117414000 & 113947335.932921 & 115686847.208333 & 0.984963621039131 & 1.03042338847764 \tabularnewline
55 & 117740333 & NA & NA & 0.977926798398001 & NA \tabularnewline
56 & 109417000 & NA & NA & 0.997828653849193 & NA \tabularnewline
57 & 116442333 & NA & NA & 1.04266551458441 & NA \tabularnewline
58 & 113311000 & NA & NA & 1.05440804643277 & NA \tabularnewline
59 & 109391333 & NA & NA & 1.02363376571758 & NA \tabularnewline
60 & 107198667 & NA & NA & 0.995286184567737 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149753&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]79717000[/C][C]NA[/C][C]NA[/C][C]0.94850203730037[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]82855667[/C][C]NA[/C][C]NA[/C][C]0.989446704791798[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]79346667[/C][C]NA[/C][C]NA[/C][C]0.996972141895198[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]76270333[/C][C]NA[/C][C]NA[/C][C]1.00241126950128[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]89532667[/C][C]NA[/C][C]NA[/C][C]0.985955261922536[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]83541333[/C][C]NA[/C][C]NA[/C][C]0.984963621039131[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]82456000[/C][C]84526002.651883[/C][C]86433875[/C][C]0.977926798398001[/C][C]0.975510463207302[/C][/ROW]
[ROW][C]8[/C][C]85818333[/C][C]86945467.1435982[/C][C]87134666.6666667[/C][C]0.997828653849193[/C][C]0.987036309302513[/C][/ROW]
[ROW][C]9[/C][C]92106667[/C][C]91789769.711529[/C][C]88033763.875[/C][C]1.04266551458441[/C][C]1.00345242492128[/C][/ROW]
[ROW][C]10[/C][C]96873333[/C][C]94373518.1195754[/C][C]89503791.6666667[/C][C]1.05440804643277[/C][C]1.02648852061716[/C][/ROW]
[ROW][C]11[/C][C]96580000[/C][C]93243666.9929224[/C][C]91090847.25[/C][C]1.02363376571758[/C][C]1.03578080007654[/C][/ROW]
[ROW][C]12[/C][C]87769000[/C][C]92169569.1996613[/C][C]92606097.25[/C][C]0.995286184567737[/C][C]0.952255725638376[/C][/ROW]
[ROW][C]13[/C][C]88396000[/C][C]89540344.4415433[/C][C]94401847.25[/C][C]0.94850203730037[/C][C]0.98721978959674[/C][/ROW]
[ROW][C]14[/C][C]90995667[/C][C]95152162.5278859[/C][C]96167041.7083333[/C][C]0.989446704791798[/C][C]0.95631738241716[/C][/ROW]
[ROW][C]15[/C][C]92785000[/C][C]97319200.2625932[/C][C]97614763.9166667[/C][C]0.996972141895198[/C][C]0.953408985581892[/C][/ROW]
[ROW][C]16[/C][C]98112667[/C][C]99397221.9626167[/C][C]99158125[/C][C]1.00241126950128[/C][C]0.987076550659536[/C][/ROW]
[ROW][C]17[/C][C]105779667[/C][C]99766772.5606083[/C][C]101187930.541667[/C][C]0.985955261922536[/C][C]1.06026950942749[/C][/ROW]
[ROW][C]18[/C][C]103660333[/C][C]102329334.327776[/C][C]103891486.083333[/C][C]0.984963621039131[/C][C]1.0130070099739[/C][/ROW]
[ROW][C]19[/C][C]105435000[/C][C]104490459.694331[/C][C]106848958.291667[/C][C]0.977926798398001[/C][C]1.00903948847035[/C][/ROW]
[ROW][C]20[/C][C]105204000[/C][C]109650476.012069[/C][C]109889083.25[/C][C]0.997828653849193[/C][C]0.9594486392236[/C][/ROW]
[ROW][C]21[/C][C]107466333[/C][C]118310343.477234[/C][C]113469124.875[/C][C]1.04266551458441[/C][C]0.908342667610286[/C][/ROW]
[ROW][C]22[/C][C]118554333[/C][C]123297570.877075[/C][C]116935347.083333[/C][C]1.05440804643277[/C][C]0.961530159569778[/C][/ROW]
[ROW][C]23[/C][C]123614333[/C][C]121977393.591695[/C][C]119161166.5[/C][C]1.02363376571758[/C][C]1.0134200228428[/C][/ROW]
[ROW][C]24[/C][C]125620000[/C][C]120368653.036944[/C][C]120938735.916667[/C][C]0.995286184567737[/C][C]1.04362719720261[/C][/ROW]
[ROW][C]25[/C][C]121524333[/C][C]116586932.518943[/C][C]122916902.583333[/C][C]0.94850203730037[/C][C]1.04234951871862[/C][/ROW]
[ROW][C]26[/C][C]130830333[/C][C]123711400.82965[/C][C]125030888.708333[/C][C]0.989446704791798[/C][C]1.05754467351115[/C][/ROW]
[ROW][C]27[/C][C]138871333[/C][C]127182115.895678[/C][C]127568374.833333[/C][C]0.996972141895198[/C][C]1.09190928317241[/C][/ROW]
[ROW][C]28[/C][C]135215667[/C][C]129818941.975144[/C][C]129506666.5[/C][C]1.00241126950128[/C][C]1.04157116783381[/C][/ROW]
[ROW][C]29[/C][C]122096333[/C][C]128271478.525991[/C][C]130098680.416667[/C][C]0.985955261922536[/C][C]0.951858779543579[/C][/ROW]
[ROW][C]30[/C][C]130005333[/C][C]127724281.92559[/C][C]129674111[/C][C]0.984963621039131[/C][C]1.01785918104232[/C][/ROW]
[ROW][C]31[/C][C]126566000[/C][C]125591294.813986[/C][C]128426069.333333[/C][C]0.977926798398001[/C][C]1.00776092950915[/C][/ROW]
[ROW][C]32[/C][C]134808667[/C][C]126185231.291392[/C][C]126459819.333333[/C][C]0.997828653849193[/C][C]1.06833950075104[/C][/ROW]
[ROW][C]33[/C][C]138761333[/C][C]129170197.21042[/C][C]123884597.125[/C][C]1.04266551458441[/C][C]1.07425192495414[/C][/ROW]
[ROW][C]34[/C][C]133778333[/C][C]127613014.082958[/C][C]121028111[/C][C]1.05440804643277[/C][C]1.04831261890761[/C][/ROW]
[ROW][C]35[/C][C]122598667[/C][C]121635997.570561[/C][C]118827652.666667[/C][C]1.02363376571758[/C][C]1.00791434648185[/C][/ROW]
[ROW][C]36[/C][C]116446000[/C][C]116188741.477974[/C][C]116739027.708333[/C][C]0.995286184567737[/C][C]1.00221414328749[/C][/ROW]
[ROW][C]37[/C][C]100745333[/C][C]108731649.569162[/C][C]114635124.958333[/C][C]0.94850203730037[/C][C]0.926550212373245[/C][/ROW]
[ROW][C]38[/C][C]104419333[/C][C]111477881.895286[/C][C]112666888.833333[/C][C]0.989446704791798[/C][C]0.936682068449095[/C][/ROW]
[ROW][C]39[/C][C]103477000[/C][C]110294778.731749[/C][C]110629749.916667[/C][C]0.996972141895198[/C][C]0.938185843335967[/C][/ROW]
[ROW][C]40[/C][C]102054333[/C][C]109166568.99332[/C][C]108903972.166667[/C][C]1.00241126950128[/C][C]0.934849688334936[/C][/ROW]
[ROW][C]41[/C][C]102446667[/C][C]106034120.386345[/C][C]107544555.5[/C][C]0.985955261922536[/C][C]0.966166990650991[/C][/ROW]
[ROW][C]42[/C][C]99528000[/C][C]105327207.854192[/C][C]106935124.916667[/C][C]0.984963621039131[/C][C]0.94494102737234[/C][/ROW]
[ROW][C]43[/C][C]106549667[/C][C]105086886.369238[/C][C]107458847.166667[/C][C]0.977926798398001[/C][C]1.0139197256794[/C][/ROW]
[ROW][C]44[/C][C]107587333[/C][C]108519936.230411[/C][C]108756083.333333[/C][C]0.997828653849193[/C][C]0.991406157589048[/C][/ROW]
[ROW][C]45[/C][C]117091333[/C][C]114774766.246833[/C][C]110078222.25[/C][C]1.04266551458441[/C][C]1.02018358938048[/C][/ROW]
[ROW][C]46[/C][C]114029667[/C][C]117568562.103611[/C][C]111501958.375[/C][C]1.05440804643277[/C][C]0.969899307771642[/C][/ROW]
[ROW][C]47[/C][C]109721333[/C][C]115603780.814118[/C][C]112934708.375[/C][C]1.02363376571758[/C][C]0.949115437465003[/C][/ROW]
[ROW][C]48[/C][C]114697000[/C][C]113771633.781839[/C][C]114310472.25[/C][C]0.995286184567737[/C][C]1.00813354073772[/C][/ROW]
[ROW][C]49[/C][C]115063667[/C][C]109572852.353013[/C][C]115522000[/C][C]0.94850203730037[/C][C]1.05011108617759[/C][/ROW]
[ROW][C]50[/C][C]121234667[/C][C]114839650.796881[/C][C]116064513.875[/C][C]0.989446704791798[/C][C]1.05568648248879[/C][/ROW]
[ROW][C]51[/C][C]118393000[/C][C]115762132.500478[/C][C]116113708.333333[/C][C]0.996972141895198[/C][C]1.02272649477593[/C][/ROW]
[ROW][C]52[/C][C]121308000[/C][C]116336566.243013[/C][C]116056722.208333[/C][C]1.00241126950128[/C][C]1.04273320003792[/C][/ROW]
[ROW][C]53[/C][C]117579000[/C][C]114383655.161678[/C][C]116013027.75[/C][C]0.985955261922536[/C][C]1.02793532724414[/C][/ROW]
[ROW][C]54[/C][C]117414000[/C][C]113947335.932921[/C][C]115686847.208333[/C][C]0.984963621039131[/C][C]1.03042338847764[/C][/ROW]
[ROW][C]55[/C][C]117740333[/C][C]NA[/C][C]NA[/C][C]0.977926798398001[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]109417000[/C][C]NA[/C][C]NA[/C][C]0.997828653849193[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]116442333[/C][C]NA[/C][C]NA[/C][C]1.04266551458441[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]113311000[/C][C]NA[/C][C]NA[/C][C]1.05440804643277[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]109391333[/C][C]NA[/C][C]NA[/C][C]1.02363376571758[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]107198667[/C][C]NA[/C][C]NA[/C][C]0.995286184567737[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149753&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
t	Observations	Fit	Trend	Seasonal	Random
1	79717000	NA	NA	0.94850203730037	NA
2	82855667	NA	NA	0.989446704791798	NA
3	79346667	NA	NA	0.996972141895198	NA
4	76270333	NA	NA	1.00241126950128	NA
5	89532667	NA	NA	0.985955261922536	NA
6	83541333	NA	NA	0.984963621039131	NA
7	82456000	84526002.651883	86433875	0.977926798398001	0.975510463207302
8	85818333	86945467.1435982	87134666.6666667	0.997828653849193	0.987036309302513
9	92106667	91789769.711529	88033763.875	1.04266551458441	1.00345242492128
10	96873333	94373518.1195754	89503791.6666667	1.05440804643277	1.02648852061716
11	96580000	93243666.9929224	91090847.25	1.02363376571758	1.03578080007654
12	87769000	92169569.1996613	92606097.25	0.995286184567737	0.952255725638376
13	88396000	89540344.4415433	94401847.25	0.94850203730037	0.98721978959674
14	90995667	95152162.5278859	96167041.7083333	0.989446704791798	0.95631738241716
15	92785000	97319200.2625932	97614763.9166667	0.996972141895198	0.953408985581892
16	98112667	99397221.9626167	99158125	1.00241126950128	0.987076550659536
17	105779667	99766772.5606083	101187930.541667	0.985955261922536	1.06026950942749
18	103660333	102329334.327776	103891486.083333	0.984963621039131	1.0130070099739
19	105435000	104490459.694331	106848958.291667	0.977926798398001	1.00903948847035
20	105204000	109650476.012069	109889083.25	0.997828653849193	0.9594486392236
21	107466333	118310343.477234	113469124.875	1.04266551458441	0.908342667610286
22	118554333	123297570.877075	116935347.083333	1.05440804643277	0.961530159569778
23	123614333	121977393.591695	119161166.5	1.02363376571758	1.0134200228428
24	125620000	120368653.036944	120938735.916667	0.995286184567737	1.04362719720261
25	121524333	116586932.518943	122916902.583333	0.94850203730037	1.04234951871862
26	130830333	123711400.82965	125030888.708333	0.989446704791798	1.05754467351115
27	138871333	127182115.895678	127568374.833333	0.996972141895198	1.09190928317241
28	135215667	129818941.975144	129506666.5	1.00241126950128	1.04157116783381
29	122096333	128271478.525991	130098680.416667	0.985955261922536	0.951858779543579
30	130005333	127724281.92559	129674111	0.984963621039131	1.01785918104232
31	126566000	125591294.813986	128426069.333333	0.977926798398001	1.00776092950915
32	134808667	126185231.291392	126459819.333333	0.997828653849193	1.06833950075104
33	138761333	129170197.21042	123884597.125	1.04266551458441	1.07425192495414
34	133778333	127613014.082958	121028111	1.05440804643277	1.04831261890761
35	122598667	121635997.570561	118827652.666667	1.02363376571758	1.00791434648185
36	116446000	116188741.477974	116739027.708333	0.995286184567737	1.00221414328749
37	100745333	108731649.569162	114635124.958333	0.94850203730037	0.926550212373245
38	104419333	111477881.895286	112666888.833333	0.989446704791798	0.936682068449095
39	103477000	110294778.731749	110629749.916667	0.996972141895198	0.938185843335967
40	102054333	109166568.99332	108903972.166667	1.00241126950128	0.934849688334936
41	102446667	106034120.386345	107544555.5	0.985955261922536	0.966166990650991
42	99528000	105327207.854192	106935124.916667	0.984963621039131	0.94494102737234
43	106549667	105086886.369238	107458847.166667	0.977926798398001	1.0139197256794
44	107587333	108519936.230411	108756083.333333	0.997828653849193	0.991406157589048
45	117091333	114774766.246833	110078222.25	1.04266551458441	1.02018358938048
46	114029667	117568562.103611	111501958.375	1.05440804643277	0.969899307771642
47	109721333	115603780.814118	112934708.375	1.02363376571758	0.949115437465003
48	114697000	113771633.781839	114310472.25	0.995286184567737	1.00813354073772
49	115063667	109572852.353013	115522000	0.94850203730037	1.05011108617759
50	121234667	114839650.796881	116064513.875	0.989446704791798	1.05568648248879
51	118393000	115762132.500478	116113708.333333	0.996972141895198	1.02272649477593
52	121308000	116336566.243013	116056722.208333	1.00241126950128	1.04273320003792
53	117579000	114383655.161678	116013027.75	0.985955261922536	1.02793532724414
54	117414000	113947335.932921	115686847.208333	0.984963621039131	1.03042338847764
55	117740333	NA	NA	0.977926798398001	NA
56	109417000	NA	NA	0.997828653849193	NA
57	116442333	NA	NA	1.04266551458441	NA
58	113311000	NA	NA	1.05440804643277	NA
59	109391333	NA	NA	1.02363376571758	NA
60	107198667	NA	NA	0.995286184567737	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code