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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 14 Dec 2010 22:42:47 +0000

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/2010/Dec/14/t12923664813d20wbx1oz589lq.htm/, Retrieved Thu, 02 May 2024 18:55:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110267, Retrieved Thu, 02 May 2024 18:55:03 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W92

Estimated Impact

118

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

-     [Standard Deviation-Mean Plot] [Het aantal werklo...] [2010-12-06 17:23:48] [3e532679ec753acf7892d78d91c458c8]
- RMP     [Classical Decomposition] [Het aantal werklo...] [2010-12-14 22:42:47] [6b57770a9d87785617c80b642e34c9c4] [Current]
- RMP       [Exponential Smoothing] [Het aantal werklo...] [2011-01-16 20:21:55] [74be16979710d4c4e7c6647856088456] 
- R PD      [Classical Decomposition] [standard deviatio...] [2011-05-19 08:08:59] [d460d5fbfa759ad1669bb34c73f51f31] 

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110267&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110267&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110267&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	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	591000	NA	NA	490.451388888854	NA
2	589000	NA	NA	-3572.04861111115	NA
3	584000	NA	NA	-12499.1319444444	NA
4	573000	NA	NA	-15009.5486111111	NA
5	567000	NA	NA	-26624.1319444444	NA
6	569000	NA	NA	-23759.5486111111	NA
7	621000	622563.368055556	596333.333333333	26230.0347222222	-1563.36805555562
8	629000	631427.951388889	596458.333333333	34969.6180555556	-2427.95138888888
9	628000	620886.284722222	596333.333333333	24552.9513888889	7113.71527777775
10	612000	602886.284722222	596208.333333333	6677.9513888889	9113.71527777787
11	595000	589000.868055555	596500	-7499.13194444446	5999.13194444461
12	597000	592959.201388889	596916.666666667	-3957.46527777779	4040.79861111112
13	593000	597532.118055556	597041.666666667	490.451388888854	-4532.1180555555
14	590000	593302.951388889	596875	-3572.04861111115	-3302.95138888888
15	580000	583917.534722222	596416.666666667	-12499.1319444444	-3917.53472222225
16	574000	580073.784722222	595083.333333333	-15009.5486111111	-6073.78472222225
17	573000	566250.868055556	592875	-26624.1319444444	6749.1319444445
18	573000	566240.451388889	590000	-23759.5486111111	6759.54861111112
19	620000	613230.034722222	587000	26230.0347222222	6769.96527777775
20	626000	618927.951388889	583958.333333333	34969.6180555556	7072.04861111101
21	620000	604802.951388889	580250	24552.9513888889	15197.0486111111
22	588000	582927.951388889	576250	6677.9513888889	5072.04861111112
23	566000	564167.534722222	571666.666666667	-7499.13194444446	1832.46527777775
24	557000	562042.534722222	566000	-3957.46527777779	-5042.53472222225
25	561000	560698.784722222	560208.333333333	490.451388888854	301.215277777752
26	549000	551386.284722222	554958.333333333	-3572.04861111115	-2386.28472222225
27	532000	536667.534722222	549166.666666667	-12499.1319444444	-4667.53472222225
28	526000	528365.451388889	543375	-15009.5486111111	-2365.45138888888
29	511000	511875.868055556	538500	-26624.1319444444	-875.86805555562
30	499000	510615.451388889	534375	-23759.5486111111	-11615.4513888888
31	555000	556980.034722222	530750	26230.0347222222	-1980.03472222213
32	565000	562177.951388889	527208.333333333	34969.6180555556	2822.04861111112
33	542000	548427.951388889	523875	24552.9513888889	-6427.95138888876
34	527000	527427.951388889	520750	6677.9513888889	-427.951388888818
35	510000	510000.868055556	517500	-7499.13194444446	-0.868055555503815
36	514000	510917.534722222	514875	-3957.46527777779	3082.46527777787
37	517000	513365.451388889	512875	490.451388888854	3634.54861111118
38	508000	506886.284722222	510458.333333333	-3572.04861111115	1113.71527777781
39	493000	495667.534722222	508166.666666667	-12499.1319444444	-2667.53472222213
40	490000	491282.118055555	506291.666666667	-15009.5486111111	-1282.11805555539
41	469000	478459.201388889	505083.333333333	-26624.1319444444	-9459.20138888882
42	478000	481073.784722222	504833.333333333	-23759.5486111111	-3073.78472222213
43	528000	531605.034722222	505375	26230.0347222222	-3605.03472222213
44	534000	541844.618055556	506875	34969.6180555556	-7844.6180555555
45	518000	534261.284722222	509708.333333333	24552.9513888889	-16261.2847222221
46	506000	520136.284722222	513458.333333333	6677.9513888889	-14136.2847222222
47	502000	510209.201388889	517708.333333333	-7499.13194444446	-8209.20138888893
48	516000	518459.201388889	522416.666666667	-3957.46527777779	-2459.20138888888
49	528000	527782.118055556	527291.666666667	490.451388888854	217.881944444380
50	533000	528802.951388889	532375	-3572.04861111115	4197.04861111112
51	536000	525125.868055556	537625	-12499.1319444444	10874.1319444444
52	537000	527657.118055556	542666.666666667	-15009.5486111111	9342.8819444445
53	524000	520792.534722222	547416.666666667	-26624.1319444444	3207.46527777775
54	536000	528448.784722222	552208.333333333	-23759.5486111111	7551.21527777764
55	587000	NA	NA	26230.0347222222	NA
56	597000	NA	NA	34969.6180555556	NA
57	581000	NA	NA	24552.9513888889	NA
58	564000	NA	NA	6677.9513888889	NA
59	558000	NA	NA	-7499.13194444446	NA
60	575000	NA	NA	-3957.46527777779	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 591000 & NA & NA & 490.451388888854 & NA \tabularnewline
2 & 589000 & NA & NA & -3572.04861111115 & NA \tabularnewline
3 & 584000 & NA & NA & -12499.1319444444 & NA \tabularnewline
4 & 573000 & NA & NA & -15009.5486111111 & NA \tabularnewline
5 & 567000 & NA & NA & -26624.1319444444 & NA \tabularnewline
6 & 569000 & NA & NA & -23759.5486111111 & NA \tabularnewline
7 & 621000 & 622563.368055556 & 596333.333333333 & 26230.0347222222 & -1563.36805555562 \tabularnewline
8 & 629000 & 631427.951388889 & 596458.333333333 & 34969.6180555556 & -2427.95138888888 \tabularnewline
9 & 628000 & 620886.284722222 & 596333.333333333 & 24552.9513888889 & 7113.71527777775 \tabularnewline
10 & 612000 & 602886.284722222 & 596208.333333333 & 6677.9513888889 & 9113.71527777787 \tabularnewline
11 & 595000 & 589000.868055555 & 596500 & -7499.13194444446 & 5999.13194444461 \tabularnewline
12 & 597000 & 592959.201388889 & 596916.666666667 & -3957.46527777779 & 4040.79861111112 \tabularnewline
13 & 593000 & 597532.118055556 & 597041.666666667 & 490.451388888854 & -4532.1180555555 \tabularnewline
14 & 590000 & 593302.951388889 & 596875 & -3572.04861111115 & -3302.95138888888 \tabularnewline
15 & 580000 & 583917.534722222 & 596416.666666667 & -12499.1319444444 & -3917.53472222225 \tabularnewline
16 & 574000 & 580073.784722222 & 595083.333333333 & -15009.5486111111 & -6073.78472222225 \tabularnewline
17 & 573000 & 566250.868055556 & 592875 & -26624.1319444444 & 6749.1319444445 \tabularnewline
18 & 573000 & 566240.451388889 & 590000 & -23759.5486111111 & 6759.54861111112 \tabularnewline
19 & 620000 & 613230.034722222 & 587000 & 26230.0347222222 & 6769.96527777775 \tabularnewline
20 & 626000 & 618927.951388889 & 583958.333333333 & 34969.6180555556 & 7072.04861111101 \tabularnewline
21 & 620000 & 604802.951388889 & 580250 & 24552.9513888889 & 15197.0486111111 \tabularnewline
22 & 588000 & 582927.951388889 & 576250 & 6677.9513888889 & 5072.04861111112 \tabularnewline
23 & 566000 & 564167.534722222 & 571666.666666667 & -7499.13194444446 & 1832.46527777775 \tabularnewline
24 & 557000 & 562042.534722222 & 566000 & -3957.46527777779 & -5042.53472222225 \tabularnewline
25 & 561000 & 560698.784722222 & 560208.333333333 & 490.451388888854 & 301.215277777752 \tabularnewline
26 & 549000 & 551386.284722222 & 554958.333333333 & -3572.04861111115 & -2386.28472222225 \tabularnewline
27 & 532000 & 536667.534722222 & 549166.666666667 & -12499.1319444444 & -4667.53472222225 \tabularnewline
28 & 526000 & 528365.451388889 & 543375 & -15009.5486111111 & -2365.45138888888 \tabularnewline
29 & 511000 & 511875.868055556 & 538500 & -26624.1319444444 & -875.86805555562 \tabularnewline
30 & 499000 & 510615.451388889 & 534375 & -23759.5486111111 & -11615.4513888888 \tabularnewline
31 & 555000 & 556980.034722222 & 530750 & 26230.0347222222 & -1980.03472222213 \tabularnewline
32 & 565000 & 562177.951388889 & 527208.333333333 & 34969.6180555556 & 2822.04861111112 \tabularnewline
33 & 542000 & 548427.951388889 & 523875 & 24552.9513888889 & -6427.95138888876 \tabularnewline
34 & 527000 & 527427.951388889 & 520750 & 6677.9513888889 & -427.951388888818 \tabularnewline
35 & 510000 & 510000.868055556 & 517500 & -7499.13194444446 & -0.868055555503815 \tabularnewline
36 & 514000 & 510917.534722222 & 514875 & -3957.46527777779 & 3082.46527777787 \tabularnewline
37 & 517000 & 513365.451388889 & 512875 & 490.451388888854 & 3634.54861111118 \tabularnewline
38 & 508000 & 506886.284722222 & 510458.333333333 & -3572.04861111115 & 1113.71527777781 \tabularnewline
39 & 493000 & 495667.534722222 & 508166.666666667 & -12499.1319444444 & -2667.53472222213 \tabularnewline
40 & 490000 & 491282.118055555 & 506291.666666667 & -15009.5486111111 & -1282.11805555539 \tabularnewline
41 & 469000 & 478459.201388889 & 505083.333333333 & -26624.1319444444 & -9459.20138888882 \tabularnewline
42 & 478000 & 481073.784722222 & 504833.333333333 & -23759.5486111111 & -3073.78472222213 \tabularnewline
43 & 528000 & 531605.034722222 & 505375 & 26230.0347222222 & -3605.03472222213 \tabularnewline
44 & 534000 & 541844.618055556 & 506875 & 34969.6180555556 & -7844.6180555555 \tabularnewline
45 & 518000 & 534261.284722222 & 509708.333333333 & 24552.9513888889 & -16261.2847222221 \tabularnewline
46 & 506000 & 520136.284722222 & 513458.333333333 & 6677.9513888889 & -14136.2847222222 \tabularnewline
47 & 502000 & 510209.201388889 & 517708.333333333 & -7499.13194444446 & -8209.20138888893 \tabularnewline
48 & 516000 & 518459.201388889 & 522416.666666667 & -3957.46527777779 & -2459.20138888888 \tabularnewline
49 & 528000 & 527782.118055556 & 527291.666666667 & 490.451388888854 & 217.881944444380 \tabularnewline
50 & 533000 & 528802.951388889 & 532375 & -3572.04861111115 & 4197.04861111112 \tabularnewline
51 & 536000 & 525125.868055556 & 537625 & -12499.1319444444 & 10874.1319444444 \tabularnewline
52 & 537000 & 527657.118055556 & 542666.666666667 & -15009.5486111111 & 9342.8819444445 \tabularnewline
53 & 524000 & 520792.534722222 & 547416.666666667 & -26624.1319444444 & 3207.46527777775 \tabularnewline
54 & 536000 & 528448.784722222 & 552208.333333333 & -23759.5486111111 & 7551.21527777764 \tabularnewline
55 & 587000 & NA & NA & 26230.0347222222 & NA \tabularnewline
56 & 597000 & NA & NA & 34969.6180555556 & NA \tabularnewline
57 & 581000 & NA & NA & 24552.9513888889 & NA \tabularnewline
58 & 564000 & NA & NA & 6677.9513888889 & NA \tabularnewline
59 & 558000 & NA & NA & -7499.13194444446 & NA \tabularnewline
60 & 575000 & NA & NA & -3957.46527777779 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110267&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]591000[/C][C]NA[/C][C]NA[/C][C]490.451388888854[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]589000[/C][C]NA[/C][C]NA[/C][C]-3572.04861111115[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]584000[/C][C]NA[/C][C]NA[/C][C]-12499.1319444444[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]573000[/C][C]NA[/C][C]NA[/C][C]-15009.5486111111[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]567000[/C][C]NA[/C][C]NA[/C][C]-26624.1319444444[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]569000[/C][C]NA[/C][C]NA[/C][C]-23759.5486111111[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]621000[/C][C]622563.368055556[/C][C]596333.333333333[/C][C]26230.0347222222[/C][C]-1563.36805555562[/C][/ROW]
[ROW][C]8[/C][C]629000[/C][C]631427.951388889[/C][C]596458.333333333[/C][C]34969.6180555556[/C][C]-2427.95138888888[/C][/ROW]
[ROW][C]9[/C][C]628000[/C][C]620886.284722222[/C][C]596333.333333333[/C][C]24552.9513888889[/C][C]7113.71527777775[/C][/ROW]
[ROW][C]10[/C][C]612000[/C][C]602886.284722222[/C][C]596208.333333333[/C][C]6677.9513888889[/C][C]9113.71527777787[/C][/ROW]
[ROW][C]11[/C][C]595000[/C][C]589000.868055555[/C][C]596500[/C][C]-7499.13194444446[/C][C]5999.13194444461[/C][/ROW]
[ROW][C]12[/C][C]597000[/C][C]592959.201388889[/C][C]596916.666666667[/C][C]-3957.46527777779[/C][C]4040.79861111112[/C][/ROW]
[ROW][C]13[/C][C]593000[/C][C]597532.118055556[/C][C]597041.666666667[/C][C]490.451388888854[/C][C]-4532.1180555555[/C][/ROW]
[ROW][C]14[/C][C]590000[/C][C]593302.951388889[/C][C]596875[/C][C]-3572.04861111115[/C][C]-3302.95138888888[/C][/ROW]
[ROW][C]15[/C][C]580000[/C][C]583917.534722222[/C][C]596416.666666667[/C][C]-12499.1319444444[/C][C]-3917.53472222225[/C][/ROW]
[ROW][C]16[/C][C]574000[/C][C]580073.784722222[/C][C]595083.333333333[/C][C]-15009.5486111111[/C][C]-6073.78472222225[/C][/ROW]
[ROW][C]17[/C][C]573000[/C][C]566250.868055556[/C][C]592875[/C][C]-26624.1319444444[/C][C]6749.1319444445[/C][/ROW]
[ROW][C]18[/C][C]573000[/C][C]566240.451388889[/C][C]590000[/C][C]-23759.5486111111[/C][C]6759.54861111112[/C][/ROW]
[ROW][C]19[/C][C]620000[/C][C]613230.034722222[/C][C]587000[/C][C]26230.0347222222[/C][C]6769.96527777775[/C][/ROW]
[ROW][C]20[/C][C]626000[/C][C]618927.951388889[/C][C]583958.333333333[/C][C]34969.6180555556[/C][C]7072.04861111101[/C][/ROW]
[ROW][C]21[/C][C]620000[/C][C]604802.951388889[/C][C]580250[/C][C]24552.9513888889[/C][C]15197.0486111111[/C][/ROW]
[ROW][C]22[/C][C]588000[/C][C]582927.951388889[/C][C]576250[/C][C]6677.9513888889[/C][C]5072.04861111112[/C][/ROW]
[ROW][C]23[/C][C]566000[/C][C]564167.534722222[/C][C]571666.666666667[/C][C]-7499.13194444446[/C][C]1832.46527777775[/C][/ROW]
[ROW][C]24[/C][C]557000[/C][C]562042.534722222[/C][C]566000[/C][C]-3957.46527777779[/C][C]-5042.53472222225[/C][/ROW]
[ROW][C]25[/C][C]561000[/C][C]560698.784722222[/C][C]560208.333333333[/C][C]490.451388888854[/C][C]301.215277777752[/C][/ROW]
[ROW][C]26[/C][C]549000[/C][C]551386.284722222[/C][C]554958.333333333[/C][C]-3572.04861111115[/C][C]-2386.28472222225[/C][/ROW]
[ROW][C]27[/C][C]532000[/C][C]536667.534722222[/C][C]549166.666666667[/C][C]-12499.1319444444[/C][C]-4667.53472222225[/C][/ROW]
[ROW][C]28[/C][C]526000[/C][C]528365.451388889[/C][C]543375[/C][C]-15009.5486111111[/C][C]-2365.45138888888[/C][/ROW]
[ROW][C]29[/C][C]511000[/C][C]511875.868055556[/C][C]538500[/C][C]-26624.1319444444[/C][C]-875.86805555562[/C][/ROW]
[ROW][C]30[/C][C]499000[/C][C]510615.451388889[/C][C]534375[/C][C]-23759.5486111111[/C][C]-11615.4513888888[/C][/ROW]
[ROW][C]31[/C][C]555000[/C][C]556980.034722222[/C][C]530750[/C][C]26230.0347222222[/C][C]-1980.03472222213[/C][/ROW]
[ROW][C]32[/C][C]565000[/C][C]562177.951388889[/C][C]527208.333333333[/C][C]34969.6180555556[/C][C]2822.04861111112[/C][/ROW]
[ROW][C]33[/C][C]542000[/C][C]548427.951388889[/C][C]523875[/C][C]24552.9513888889[/C][C]-6427.95138888876[/C][/ROW]
[ROW][C]34[/C][C]527000[/C][C]527427.951388889[/C][C]520750[/C][C]6677.9513888889[/C][C]-427.951388888818[/C][/ROW]
[ROW][C]35[/C][C]510000[/C][C]510000.868055556[/C][C]517500[/C][C]-7499.13194444446[/C][C]-0.868055555503815[/C][/ROW]
[ROW][C]36[/C][C]514000[/C][C]510917.534722222[/C][C]514875[/C][C]-3957.46527777779[/C][C]3082.46527777787[/C][/ROW]
[ROW][C]37[/C][C]517000[/C][C]513365.451388889[/C][C]512875[/C][C]490.451388888854[/C][C]3634.54861111118[/C][/ROW]
[ROW][C]38[/C][C]508000[/C][C]506886.284722222[/C][C]510458.333333333[/C][C]-3572.04861111115[/C][C]1113.71527777781[/C][/ROW]
[ROW][C]39[/C][C]493000[/C][C]495667.534722222[/C][C]508166.666666667[/C][C]-12499.1319444444[/C][C]-2667.53472222213[/C][/ROW]
[ROW][C]40[/C][C]490000[/C][C]491282.118055555[/C][C]506291.666666667[/C][C]-15009.5486111111[/C][C]-1282.11805555539[/C][/ROW]
[ROW][C]41[/C][C]469000[/C][C]478459.201388889[/C][C]505083.333333333[/C][C]-26624.1319444444[/C][C]-9459.20138888882[/C][/ROW]
[ROW][C]42[/C][C]478000[/C][C]481073.784722222[/C][C]504833.333333333[/C][C]-23759.5486111111[/C][C]-3073.78472222213[/C][/ROW]
[ROW][C]43[/C][C]528000[/C][C]531605.034722222[/C][C]505375[/C][C]26230.0347222222[/C][C]-3605.03472222213[/C][/ROW]
[ROW][C]44[/C][C]534000[/C][C]541844.618055556[/C][C]506875[/C][C]34969.6180555556[/C][C]-7844.6180555555[/C][/ROW]
[ROW][C]45[/C][C]518000[/C][C]534261.284722222[/C][C]509708.333333333[/C][C]24552.9513888889[/C][C]-16261.2847222221[/C][/ROW]
[ROW][C]46[/C][C]506000[/C][C]520136.284722222[/C][C]513458.333333333[/C][C]6677.9513888889[/C][C]-14136.2847222222[/C][/ROW]
[ROW][C]47[/C][C]502000[/C][C]510209.201388889[/C][C]517708.333333333[/C][C]-7499.13194444446[/C][C]-8209.20138888893[/C][/ROW]
[ROW][C]48[/C][C]516000[/C][C]518459.201388889[/C][C]522416.666666667[/C][C]-3957.46527777779[/C][C]-2459.20138888888[/C][/ROW]
[ROW][C]49[/C][C]528000[/C][C]527782.118055556[/C][C]527291.666666667[/C][C]490.451388888854[/C][C]217.881944444380[/C][/ROW]
[ROW][C]50[/C][C]533000[/C][C]528802.951388889[/C][C]532375[/C][C]-3572.04861111115[/C][C]4197.04861111112[/C][/ROW]
[ROW][C]51[/C][C]536000[/C][C]525125.868055556[/C][C]537625[/C][C]-12499.1319444444[/C][C]10874.1319444444[/C][/ROW]
[ROW][C]52[/C][C]537000[/C][C]527657.118055556[/C][C]542666.666666667[/C][C]-15009.5486111111[/C][C]9342.8819444445[/C][/ROW]
[ROW][C]53[/C][C]524000[/C][C]520792.534722222[/C][C]547416.666666667[/C][C]-26624.1319444444[/C][C]3207.46527777775[/C][/ROW]
[ROW][C]54[/C][C]536000[/C][C]528448.784722222[/C][C]552208.333333333[/C][C]-23759.5486111111[/C][C]7551.21527777764[/C][/ROW]
[ROW][C]55[/C][C]587000[/C][C]NA[/C][C]NA[/C][C]26230.0347222222[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]597000[/C][C]NA[/C][C]NA[/C][C]34969.6180555556[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]581000[/C][C]NA[/C][C]NA[/C][C]24552.9513888889[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]564000[/C][C]NA[/C][C]NA[/C][C]6677.9513888889[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]558000[/C][C]NA[/C][C]NA[/C][C]-7499.13194444446[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]575000[/C][C]NA[/C][C]NA[/C][C]-3957.46527777779[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110267&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110267&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	591000	NA	NA	490.451388888854	NA
2	589000	NA	NA	-3572.04861111115	NA
3	584000	NA	NA	-12499.1319444444	NA
4	573000	NA	NA	-15009.5486111111	NA
5	567000	NA	NA	-26624.1319444444	NA
6	569000	NA	NA	-23759.5486111111	NA
7	621000	622563.368055556	596333.333333333	26230.0347222222	-1563.36805555562
8	629000	631427.951388889	596458.333333333	34969.6180555556	-2427.95138888888
9	628000	620886.284722222	596333.333333333	24552.9513888889	7113.71527777775
10	612000	602886.284722222	596208.333333333	6677.9513888889	9113.71527777787
11	595000	589000.868055555	596500	-7499.13194444446	5999.13194444461
12	597000	592959.201388889	596916.666666667	-3957.46527777779	4040.79861111112
13	593000	597532.118055556	597041.666666667	490.451388888854	-4532.1180555555
14	590000	593302.951388889	596875	-3572.04861111115	-3302.95138888888
15	580000	583917.534722222	596416.666666667	-12499.1319444444	-3917.53472222225
16	574000	580073.784722222	595083.333333333	-15009.5486111111	-6073.78472222225
17	573000	566250.868055556	592875	-26624.1319444444	6749.1319444445
18	573000	566240.451388889	590000	-23759.5486111111	6759.54861111112
19	620000	613230.034722222	587000	26230.0347222222	6769.96527777775
20	626000	618927.951388889	583958.333333333	34969.6180555556	7072.04861111101
21	620000	604802.951388889	580250	24552.9513888889	15197.0486111111
22	588000	582927.951388889	576250	6677.9513888889	5072.04861111112
23	566000	564167.534722222	571666.666666667	-7499.13194444446	1832.46527777775
24	557000	562042.534722222	566000	-3957.46527777779	-5042.53472222225
25	561000	560698.784722222	560208.333333333	490.451388888854	301.215277777752
26	549000	551386.284722222	554958.333333333	-3572.04861111115	-2386.28472222225
27	532000	536667.534722222	549166.666666667	-12499.1319444444	-4667.53472222225
28	526000	528365.451388889	543375	-15009.5486111111	-2365.45138888888
29	511000	511875.868055556	538500	-26624.1319444444	-875.86805555562
30	499000	510615.451388889	534375	-23759.5486111111	-11615.4513888888
31	555000	556980.034722222	530750	26230.0347222222	-1980.03472222213
32	565000	562177.951388889	527208.333333333	34969.6180555556	2822.04861111112
33	542000	548427.951388889	523875	24552.9513888889	-6427.95138888876
34	527000	527427.951388889	520750	6677.9513888889	-427.951388888818
35	510000	510000.868055556	517500	-7499.13194444446	-0.868055555503815
36	514000	510917.534722222	514875	-3957.46527777779	3082.46527777787
37	517000	513365.451388889	512875	490.451388888854	3634.54861111118
38	508000	506886.284722222	510458.333333333	-3572.04861111115	1113.71527777781
39	493000	495667.534722222	508166.666666667	-12499.1319444444	-2667.53472222213
40	490000	491282.118055555	506291.666666667	-15009.5486111111	-1282.11805555539
41	469000	478459.201388889	505083.333333333	-26624.1319444444	-9459.20138888882
42	478000	481073.784722222	504833.333333333	-23759.5486111111	-3073.78472222213
43	528000	531605.034722222	505375	26230.0347222222	-3605.03472222213
44	534000	541844.618055556	506875	34969.6180555556	-7844.6180555555
45	518000	534261.284722222	509708.333333333	24552.9513888889	-16261.2847222221
46	506000	520136.284722222	513458.333333333	6677.9513888889	-14136.2847222222
47	502000	510209.201388889	517708.333333333	-7499.13194444446	-8209.20138888893
48	516000	518459.201388889	522416.666666667	-3957.46527777779	-2459.20138888888
49	528000	527782.118055556	527291.666666667	490.451388888854	217.881944444380
50	533000	528802.951388889	532375	-3572.04861111115	4197.04861111112
51	536000	525125.868055556	537625	-12499.1319444444	10874.1319444444
52	537000	527657.118055556	542666.666666667	-15009.5486111111	9342.8819444445
53	524000	520792.534722222	547416.666666667	-26624.1319444444	3207.46527777775
54	536000	528448.784722222	552208.333333333	-23759.5486111111	7551.21527777764
55	587000	NA	NA	26230.0347222222	NA
56	597000	NA	NA	34969.6180555556	NA
57	581000	NA	NA	24552.9513888889	NA
58	564000	NA	NA	6677.9513888889	NA
59	558000	NA	NA	-7499.13194444446	NA
60	575000	NA	NA	-3957.46527777779	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 = 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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