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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Tue, 07 Dec 2010 08:20:52 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/07/t1291709966qfpq632dcviobuk.htm/, Retrieved Fri, 03 May 2024 23:21:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106002, Retrieved Fri, 03 May 2024 23:21:47 +0000

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Estimated Impact

167

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [Unemployment] [2010-11-30 13:33:27] [b98453cac15ba1066b407e146608df68]
-    D      [Classical Decomposition] [CD-Model - Uitvoer] [2010-12-07 08:20:52] [85c2b01fe80f9fc86b9396d4d142e465] [Current]

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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	3 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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106002&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]3 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=106002&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106002&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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	16198.9	NA	NA	-815.591782407408	NA
2	16554.2	NA	NA	-610.665393518518	NA
3	19554.2	NA	NA	664.852662037038	NA
4	15903.8	NA	NA	66.1221064814794	NA
5	18003.8	NA	NA	-102.082060185186	NA
6	18329.6	NA	NA	1315.98877314815	NA
7	16260.7	17743.3748842593	17277.9666666667	465.408217592592	-1482.67488425926
8	14851.9	15178.3443287037	17354.7416666667	-2176.39733796296	-326.444328703703
9	18174.1	18593.1471064815	17383.4416666667	1209.70543981481	-419.047106481481
10	18406.6	19116.7137731481	17439.925	1676.78877314815	-710.113773148147
11	18466.5	17311.5887731481	17507.4541666667	-195.865393518516	1154.91122685185
12	16016.5	16063.8859953704	17562.15	-1498.26400462963	-47.3859953703686
13	17428.5	16865.6665509259	17681.2583333333	-815.591782407408	562.833449074074
14	17167.2	17205.0846064815	17815.75	-610.665393518518	-37.8846064814825
15	19630	18544.8234953704	17879.9708333333	664.852662037038	1085.17650462963
16	17183.6	18042.2971064815	17976.175	66.1221064814794	-858.697106481482
17	18344.7	17982.3971064815	18084.4791666667	-102.082060185186	362.302893518518
18	19301.4	19439.8721064815	18123.8833333333	1315.98877314815	-138.472106481480
19	18147.5	18663.1790509259	18197.7708333333	465.408217592592	-515.679050925926
20	16192.9	16153.0651620370	18329.4625	-2176.39733796296	39.8348379629606
21	18374.4	19598.4804398148	18388.775	1209.70543981481	-1224.08043981481
22	20515.2	20188.2846064815	18511.4958333333	1676.78877314815	326.915393518517
23	18957.2	18496.6804398148	18692.5458333333	-195.865393518516	460.519560185185
24	16471.5	17289.4984953704	18787.7625	-1498.26400462963	-817.998495370372
25	18746.8	18106.0665509259	18921.6583333333	-815.591782407408	640.733449074076
26	19009.5	18388.4054398148	18999.0708333333	-610.665393518518	621.094560185185
27	19211.2	19744.5026620370	19079.65	664.852662037038	-533.302662037036
28	20547.7	19195.0137731481	19128.8916666667	66.1221064814794	1352.68622685186
29	19325.8	18855.0512731482	18957.1333333333	-102.082060185186	470.748726851849
30	20605.5	20047.8887731481	18731.9	1315.98877314815	557.611226851852
31	20056.9	18906.5498842593	18441.1416666667	465.408217592592	1150.35011574074
32	16141.4	15865.0609953704	18041.4583333333	-2176.39733796296	276.33900462963
33	20359.8	18891.9221064815	17682.2166666667	1209.70543981481	1467.87789351852
34	19711.6	18940.4846064815	17263.6958333333	1676.78877314815	771.115393518518
35	15638.6	16581.5804398148	16777.4458333333	-195.865393518516	-942.980439814815
36	14384.5	14843.1276620370	16341.3916666667	-1498.26400462963	-458.627662037035
37	13855.6	15099.0373842593	15914.6291666667	-815.591782407408	-1243.43738425926
38	14308.3	14931.3804398148	15542.0458333333	-610.665393518518	-623.080439814816
39	15290.6	15882.3443287037	15217.4916666667	664.852662037038	-591.744328703706
40	14423.8	14957.6596064815	14891.5375	66.1221064814794	-533.859606481483
41	13779.7	14652.6221064815	14754.7041666667	-102.082060185186	-872.92210648148
42	15686.3	16145.3096064815	14829.3208333333	1315.98877314815	-459.009606481481
43	14733.8	15408.3415509259	14942.9333333333	465.408217592592	-674.541550925927
44	12522.5	12878.5443287037	15054.9416666667	-2176.39733796296	-356.044328703703
45	16189.4	16473.0679398148	15263.3625	1209.70543981481	-283.667939814814
46	16059.1	17197.0012731481	15520.2125	1676.78877314815	-1137.90127314815
47	16007.1	15564.5096064815	15760.375	-195.865393518516	442.59039351852
48	15806.8	14570.0443287037	16068.3083333333	-1498.26400462963	1236.75567129630
49	15160	NA	16364.975	NA	NA
50	15692.1	NA	NA	NA	NA
51	18908.9	NA	NA	NA	NA
52	16969.9	NA	NA	NA	NA
53	16997.5	NA	NA	NA	NA
54	19858.9	NA	NA	NA	NA
55	17681.2	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 16198.9 & NA & NA & -815.591782407408 & NA \tabularnewline
2 & 16554.2 & NA & NA & -610.665393518518 & NA \tabularnewline
3 & 19554.2 & NA & NA & 664.852662037038 & NA \tabularnewline
4 & 15903.8 & NA & NA & 66.1221064814794 & NA \tabularnewline
5 & 18003.8 & NA & NA & -102.082060185186 & NA \tabularnewline
6 & 18329.6 & NA & NA & 1315.98877314815 & NA \tabularnewline
7 & 16260.7 & 17743.3748842593 & 17277.9666666667 & 465.408217592592 & -1482.67488425926 \tabularnewline
8 & 14851.9 & 15178.3443287037 & 17354.7416666667 & -2176.39733796296 & -326.444328703703 \tabularnewline
9 & 18174.1 & 18593.1471064815 & 17383.4416666667 & 1209.70543981481 & -419.047106481481 \tabularnewline
10 & 18406.6 & 19116.7137731481 & 17439.925 & 1676.78877314815 & -710.113773148147 \tabularnewline
11 & 18466.5 & 17311.5887731481 & 17507.4541666667 & -195.865393518516 & 1154.91122685185 \tabularnewline
12 & 16016.5 & 16063.8859953704 & 17562.15 & -1498.26400462963 & -47.3859953703686 \tabularnewline
13 & 17428.5 & 16865.6665509259 & 17681.2583333333 & -815.591782407408 & 562.833449074074 \tabularnewline
14 & 17167.2 & 17205.0846064815 & 17815.75 & -610.665393518518 & -37.8846064814825 \tabularnewline
15 & 19630 & 18544.8234953704 & 17879.9708333333 & 664.852662037038 & 1085.17650462963 \tabularnewline
16 & 17183.6 & 18042.2971064815 & 17976.175 & 66.1221064814794 & -858.697106481482 \tabularnewline
17 & 18344.7 & 17982.3971064815 & 18084.4791666667 & -102.082060185186 & 362.302893518518 \tabularnewline
18 & 19301.4 & 19439.8721064815 & 18123.8833333333 & 1315.98877314815 & -138.472106481480 \tabularnewline
19 & 18147.5 & 18663.1790509259 & 18197.7708333333 & 465.408217592592 & -515.679050925926 \tabularnewline
20 & 16192.9 & 16153.0651620370 & 18329.4625 & -2176.39733796296 & 39.8348379629606 \tabularnewline
21 & 18374.4 & 19598.4804398148 & 18388.775 & 1209.70543981481 & -1224.08043981481 \tabularnewline
22 & 20515.2 & 20188.2846064815 & 18511.4958333333 & 1676.78877314815 & 326.915393518517 \tabularnewline
23 & 18957.2 & 18496.6804398148 & 18692.5458333333 & -195.865393518516 & 460.519560185185 \tabularnewline
24 & 16471.5 & 17289.4984953704 & 18787.7625 & -1498.26400462963 & -817.998495370372 \tabularnewline
25 & 18746.8 & 18106.0665509259 & 18921.6583333333 & -815.591782407408 & 640.733449074076 \tabularnewline
26 & 19009.5 & 18388.4054398148 & 18999.0708333333 & -610.665393518518 & 621.094560185185 \tabularnewline
27 & 19211.2 & 19744.5026620370 & 19079.65 & 664.852662037038 & -533.302662037036 \tabularnewline
28 & 20547.7 & 19195.0137731481 & 19128.8916666667 & 66.1221064814794 & 1352.68622685186 \tabularnewline
29 & 19325.8 & 18855.0512731482 & 18957.1333333333 & -102.082060185186 & 470.748726851849 \tabularnewline
30 & 20605.5 & 20047.8887731481 & 18731.9 & 1315.98877314815 & 557.611226851852 \tabularnewline
31 & 20056.9 & 18906.5498842593 & 18441.1416666667 & 465.408217592592 & 1150.35011574074 \tabularnewline
32 & 16141.4 & 15865.0609953704 & 18041.4583333333 & -2176.39733796296 & 276.33900462963 \tabularnewline
33 & 20359.8 & 18891.9221064815 & 17682.2166666667 & 1209.70543981481 & 1467.87789351852 \tabularnewline
34 & 19711.6 & 18940.4846064815 & 17263.6958333333 & 1676.78877314815 & 771.115393518518 \tabularnewline
35 & 15638.6 & 16581.5804398148 & 16777.4458333333 & -195.865393518516 & -942.980439814815 \tabularnewline
36 & 14384.5 & 14843.1276620370 & 16341.3916666667 & -1498.26400462963 & -458.627662037035 \tabularnewline
37 & 13855.6 & 15099.0373842593 & 15914.6291666667 & -815.591782407408 & -1243.43738425926 \tabularnewline
38 & 14308.3 & 14931.3804398148 & 15542.0458333333 & -610.665393518518 & -623.080439814816 \tabularnewline
39 & 15290.6 & 15882.3443287037 & 15217.4916666667 & 664.852662037038 & -591.744328703706 \tabularnewline
40 & 14423.8 & 14957.6596064815 & 14891.5375 & 66.1221064814794 & -533.859606481483 \tabularnewline
41 & 13779.7 & 14652.6221064815 & 14754.7041666667 & -102.082060185186 & -872.92210648148 \tabularnewline
42 & 15686.3 & 16145.3096064815 & 14829.3208333333 & 1315.98877314815 & -459.009606481481 \tabularnewline
43 & 14733.8 & 15408.3415509259 & 14942.9333333333 & 465.408217592592 & -674.541550925927 \tabularnewline
44 & 12522.5 & 12878.5443287037 & 15054.9416666667 & -2176.39733796296 & -356.044328703703 \tabularnewline
45 & 16189.4 & 16473.0679398148 & 15263.3625 & 1209.70543981481 & -283.667939814814 \tabularnewline
46 & 16059.1 & 17197.0012731481 & 15520.2125 & 1676.78877314815 & -1137.90127314815 \tabularnewline
47 & 16007.1 & 15564.5096064815 & 15760.375 & -195.865393518516 & 442.59039351852 \tabularnewline
48 & 15806.8 & 14570.0443287037 & 16068.3083333333 & -1498.26400462963 & 1236.75567129630 \tabularnewline
49 & 15160 & NA & 16364.975 & NA & NA \tabularnewline
50 & 15692.1 & NA & NA & NA & NA \tabularnewline
51 & 18908.9 & NA & NA & NA & NA \tabularnewline
52 & 16969.9 & NA & NA & NA & NA \tabularnewline
53 & 16997.5 & NA & NA & NA & NA \tabularnewline
54 & 19858.9 & NA & NA & NA & NA \tabularnewline
55 & 17681.2 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106002&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]16198.9[/C][C]NA[/C][C]NA[/C][C]-815.591782407408[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]16554.2[/C][C]NA[/C][C]NA[/C][C]-610.665393518518[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]19554.2[/C][C]NA[/C][C]NA[/C][C]664.852662037038[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]15903.8[/C][C]NA[/C][C]NA[/C][C]66.1221064814794[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]18003.8[/C][C]NA[/C][C]NA[/C][C]-102.082060185186[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]18329.6[/C][C]NA[/C][C]NA[/C][C]1315.98877314815[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]16260.7[/C][C]17743.3748842593[/C][C]17277.9666666667[/C][C]465.408217592592[/C][C]-1482.67488425926[/C][/ROW]
[ROW][C]8[/C][C]14851.9[/C][C]15178.3443287037[/C][C]17354.7416666667[/C][C]-2176.39733796296[/C][C]-326.444328703703[/C][/ROW]
[ROW][C]9[/C][C]18174.1[/C][C]18593.1471064815[/C][C]17383.4416666667[/C][C]1209.70543981481[/C][C]-419.047106481481[/C][/ROW]
[ROW][C]10[/C][C]18406.6[/C][C]19116.7137731481[/C][C]17439.925[/C][C]1676.78877314815[/C][C]-710.113773148147[/C][/ROW]
[ROW][C]11[/C][C]18466.5[/C][C]17311.5887731481[/C][C]17507.4541666667[/C][C]-195.865393518516[/C][C]1154.91122685185[/C][/ROW]
[ROW][C]12[/C][C]16016.5[/C][C]16063.8859953704[/C][C]17562.15[/C][C]-1498.26400462963[/C][C]-47.3859953703686[/C][/ROW]
[ROW][C]13[/C][C]17428.5[/C][C]16865.6665509259[/C][C]17681.2583333333[/C][C]-815.591782407408[/C][C]562.833449074074[/C][/ROW]
[ROW][C]14[/C][C]17167.2[/C][C]17205.0846064815[/C][C]17815.75[/C][C]-610.665393518518[/C][C]-37.8846064814825[/C][/ROW]
[ROW][C]15[/C][C]19630[/C][C]18544.8234953704[/C][C]17879.9708333333[/C][C]664.852662037038[/C][C]1085.17650462963[/C][/ROW]
[ROW][C]16[/C][C]17183.6[/C][C]18042.2971064815[/C][C]17976.175[/C][C]66.1221064814794[/C][C]-858.697106481482[/C][/ROW]
[ROW][C]17[/C][C]18344.7[/C][C]17982.3971064815[/C][C]18084.4791666667[/C][C]-102.082060185186[/C][C]362.302893518518[/C][/ROW]
[ROW][C]18[/C][C]19301.4[/C][C]19439.8721064815[/C][C]18123.8833333333[/C][C]1315.98877314815[/C][C]-138.472106481480[/C][/ROW]
[ROW][C]19[/C][C]18147.5[/C][C]18663.1790509259[/C][C]18197.7708333333[/C][C]465.408217592592[/C][C]-515.679050925926[/C][/ROW]
[ROW][C]20[/C][C]16192.9[/C][C]16153.0651620370[/C][C]18329.4625[/C][C]-2176.39733796296[/C][C]39.8348379629606[/C][/ROW]
[ROW][C]21[/C][C]18374.4[/C][C]19598.4804398148[/C][C]18388.775[/C][C]1209.70543981481[/C][C]-1224.08043981481[/C][/ROW]
[ROW][C]22[/C][C]20515.2[/C][C]20188.2846064815[/C][C]18511.4958333333[/C][C]1676.78877314815[/C][C]326.915393518517[/C][/ROW]
[ROW][C]23[/C][C]18957.2[/C][C]18496.6804398148[/C][C]18692.5458333333[/C][C]-195.865393518516[/C][C]460.519560185185[/C][/ROW]
[ROW][C]24[/C][C]16471.5[/C][C]17289.4984953704[/C][C]18787.7625[/C][C]-1498.26400462963[/C][C]-817.998495370372[/C][/ROW]
[ROW][C]25[/C][C]18746.8[/C][C]18106.0665509259[/C][C]18921.6583333333[/C][C]-815.591782407408[/C][C]640.733449074076[/C][/ROW]
[ROW][C]26[/C][C]19009.5[/C][C]18388.4054398148[/C][C]18999.0708333333[/C][C]-610.665393518518[/C][C]621.094560185185[/C][/ROW]
[ROW][C]27[/C][C]19211.2[/C][C]19744.5026620370[/C][C]19079.65[/C][C]664.852662037038[/C][C]-533.302662037036[/C][/ROW]
[ROW][C]28[/C][C]20547.7[/C][C]19195.0137731481[/C][C]19128.8916666667[/C][C]66.1221064814794[/C][C]1352.68622685186[/C][/ROW]
[ROW][C]29[/C][C]19325.8[/C][C]18855.0512731482[/C][C]18957.1333333333[/C][C]-102.082060185186[/C][C]470.748726851849[/C][/ROW]
[ROW][C]30[/C][C]20605.5[/C][C]20047.8887731481[/C][C]18731.9[/C][C]1315.98877314815[/C][C]557.611226851852[/C][/ROW]
[ROW][C]31[/C][C]20056.9[/C][C]18906.5498842593[/C][C]18441.1416666667[/C][C]465.408217592592[/C][C]1150.35011574074[/C][/ROW]
[ROW][C]32[/C][C]16141.4[/C][C]15865.0609953704[/C][C]18041.4583333333[/C][C]-2176.39733796296[/C][C]276.33900462963[/C][/ROW]
[ROW][C]33[/C][C]20359.8[/C][C]18891.9221064815[/C][C]17682.2166666667[/C][C]1209.70543981481[/C][C]1467.87789351852[/C][/ROW]
[ROW][C]34[/C][C]19711.6[/C][C]18940.4846064815[/C][C]17263.6958333333[/C][C]1676.78877314815[/C][C]771.115393518518[/C][/ROW]
[ROW][C]35[/C][C]15638.6[/C][C]16581.5804398148[/C][C]16777.4458333333[/C][C]-195.865393518516[/C][C]-942.980439814815[/C][/ROW]
[ROW][C]36[/C][C]14384.5[/C][C]14843.1276620370[/C][C]16341.3916666667[/C][C]-1498.26400462963[/C][C]-458.627662037035[/C][/ROW]
[ROW][C]37[/C][C]13855.6[/C][C]15099.0373842593[/C][C]15914.6291666667[/C][C]-815.591782407408[/C][C]-1243.43738425926[/C][/ROW]
[ROW][C]38[/C][C]14308.3[/C][C]14931.3804398148[/C][C]15542.0458333333[/C][C]-610.665393518518[/C][C]-623.080439814816[/C][/ROW]
[ROW][C]39[/C][C]15290.6[/C][C]15882.3443287037[/C][C]15217.4916666667[/C][C]664.852662037038[/C][C]-591.744328703706[/C][/ROW]
[ROW][C]40[/C][C]14423.8[/C][C]14957.6596064815[/C][C]14891.5375[/C][C]66.1221064814794[/C][C]-533.859606481483[/C][/ROW]
[ROW][C]41[/C][C]13779.7[/C][C]14652.6221064815[/C][C]14754.7041666667[/C][C]-102.082060185186[/C][C]-872.92210648148[/C][/ROW]
[ROW][C]42[/C][C]15686.3[/C][C]16145.3096064815[/C][C]14829.3208333333[/C][C]1315.98877314815[/C][C]-459.009606481481[/C][/ROW]
[ROW][C]43[/C][C]14733.8[/C][C]15408.3415509259[/C][C]14942.9333333333[/C][C]465.408217592592[/C][C]-674.541550925927[/C][/ROW]
[ROW][C]44[/C][C]12522.5[/C][C]12878.5443287037[/C][C]15054.9416666667[/C][C]-2176.39733796296[/C][C]-356.044328703703[/C][/ROW]
[ROW][C]45[/C][C]16189.4[/C][C]16473.0679398148[/C][C]15263.3625[/C][C]1209.70543981481[/C][C]-283.667939814814[/C][/ROW]
[ROW][C]46[/C][C]16059.1[/C][C]17197.0012731481[/C][C]15520.2125[/C][C]1676.78877314815[/C][C]-1137.90127314815[/C][/ROW]
[ROW][C]47[/C][C]16007.1[/C][C]15564.5096064815[/C][C]15760.375[/C][C]-195.865393518516[/C][C]442.59039351852[/C][/ROW]
[ROW][C]48[/C][C]15806.8[/C][C]14570.0443287037[/C][C]16068.3083333333[/C][C]-1498.26400462963[/C][C]1236.75567129630[/C][/ROW]
[ROW][C]49[/C][C]15160[/C][C]NA[/C][C]16364.975[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]15692.1[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]18908.9[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]16969.9[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]16997.5[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]19858.9[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]17681.2[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106002&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106002&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	16198.9	NA	NA	-815.591782407408	NA
2	16554.2	NA	NA	-610.665393518518	NA
3	19554.2	NA	NA	664.852662037038	NA
4	15903.8	NA	NA	66.1221064814794	NA
5	18003.8	NA	NA	-102.082060185186	NA
6	18329.6	NA	NA	1315.98877314815	NA
7	16260.7	17743.3748842593	17277.9666666667	465.408217592592	-1482.67488425926
8	14851.9	15178.3443287037	17354.7416666667	-2176.39733796296	-326.444328703703
9	18174.1	18593.1471064815	17383.4416666667	1209.70543981481	-419.047106481481
10	18406.6	19116.7137731481	17439.925	1676.78877314815	-710.113773148147
11	18466.5	17311.5887731481	17507.4541666667	-195.865393518516	1154.91122685185
12	16016.5	16063.8859953704	17562.15	-1498.26400462963	-47.3859953703686
13	17428.5	16865.6665509259	17681.2583333333	-815.591782407408	562.833449074074
14	17167.2	17205.0846064815	17815.75	-610.665393518518	-37.8846064814825
15	19630	18544.8234953704	17879.9708333333	664.852662037038	1085.17650462963
16	17183.6	18042.2971064815	17976.175	66.1221064814794	-858.697106481482
17	18344.7	17982.3971064815	18084.4791666667	-102.082060185186	362.302893518518
18	19301.4	19439.8721064815	18123.8833333333	1315.98877314815	-138.472106481480
19	18147.5	18663.1790509259	18197.7708333333	465.408217592592	-515.679050925926
20	16192.9	16153.0651620370	18329.4625	-2176.39733796296	39.8348379629606
21	18374.4	19598.4804398148	18388.775	1209.70543981481	-1224.08043981481
22	20515.2	20188.2846064815	18511.4958333333	1676.78877314815	326.915393518517
23	18957.2	18496.6804398148	18692.5458333333	-195.865393518516	460.519560185185
24	16471.5	17289.4984953704	18787.7625	-1498.26400462963	-817.998495370372
25	18746.8	18106.0665509259	18921.6583333333	-815.591782407408	640.733449074076
26	19009.5	18388.4054398148	18999.0708333333	-610.665393518518	621.094560185185
27	19211.2	19744.5026620370	19079.65	664.852662037038	-533.302662037036
28	20547.7	19195.0137731481	19128.8916666667	66.1221064814794	1352.68622685186
29	19325.8	18855.0512731482	18957.1333333333	-102.082060185186	470.748726851849
30	20605.5	20047.8887731481	18731.9	1315.98877314815	557.611226851852
31	20056.9	18906.5498842593	18441.1416666667	465.408217592592	1150.35011574074
32	16141.4	15865.0609953704	18041.4583333333	-2176.39733796296	276.33900462963
33	20359.8	18891.9221064815	17682.2166666667	1209.70543981481	1467.87789351852
34	19711.6	18940.4846064815	17263.6958333333	1676.78877314815	771.115393518518
35	15638.6	16581.5804398148	16777.4458333333	-195.865393518516	-942.980439814815
36	14384.5	14843.1276620370	16341.3916666667	-1498.26400462963	-458.627662037035
37	13855.6	15099.0373842593	15914.6291666667	-815.591782407408	-1243.43738425926
38	14308.3	14931.3804398148	15542.0458333333	-610.665393518518	-623.080439814816
39	15290.6	15882.3443287037	15217.4916666667	664.852662037038	-591.744328703706
40	14423.8	14957.6596064815	14891.5375	66.1221064814794	-533.859606481483
41	13779.7	14652.6221064815	14754.7041666667	-102.082060185186	-872.92210648148
42	15686.3	16145.3096064815	14829.3208333333	1315.98877314815	-459.009606481481
43	14733.8	15408.3415509259	14942.9333333333	465.408217592592	-674.541550925927
44	12522.5	12878.5443287037	15054.9416666667	-2176.39733796296	-356.044328703703
45	16189.4	16473.0679398148	15263.3625	1209.70543981481	-283.667939814814
46	16059.1	17197.0012731481	15520.2125	1676.78877314815	-1137.90127314815
47	16007.1	15564.5096064815	15760.375	-195.865393518516	442.59039351852
48	15806.8	14570.0443287037	16068.3083333333	-1498.26400462963	1236.75567129630
49	15160	NA	16364.975	NA	NA
50	15692.1	NA	NA	NA	NA
51	18908.9	NA	NA	NA	NA
52	16969.9	NA	NA	NA	NA
53	16997.5	NA	NA	NA	NA
54	19858.9	NA	NA	NA	NA
55	17681.2	NA	NA	NA	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