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Author

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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 28 Nov 2011 11:53:16 -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/Nov/28/t1322499205k5djeqkepnggf9x.htm/, Retrieved Fri, 09 May 2025 16:20:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147867, Retrieved Fri, 09 May 2025 16:20:18 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

219

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

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- R P         [Univariate Data Series] [WS8 Time Series A...] [2010-11-30 09:10:08] [afe9379cca749d06b3d6872e02cc47ed]
- RMP           [Classical Decomposition] [] [2011-11-28 11:49:18] [77e355412ccdb651b3c7eae41c3da865]
- R                 [Classical Decomposition] [] [2011-11-28 16:53:16] [5f7ae77ad4c15dc18491c39fdf8bddde] [Current]
-  M                  [Classical Decomposition] [] [2011-11-28 16:55:25] [aefb5c2d4042694c5b6b82f93ac1885a] 
-  M                  [Classical Decomposition] [] [2012-11-26 18:35:33] [c6861060a9fe16fe372e7d046f8d5b70] 
- RMPD                [Structural Time Series Models] [] [2012-11-26 18:43:45] [c6861060a9fe16fe372e7d046f8d5b70] 
- RMPD                [Exponential Smoothing] [] [2012-11-26 19:08:13] [c6861060a9fe16fe372e7d046f8d5b70] 
- R P                   [Exponential Smoothing] [] [2012-12-16 20:20:50] [c6861060a9fe16fe372e7d046f8d5b70] 
-                         [Exponential Smoothing] [] [2012-12-17 19:44:44] [74be16979710d4c4e7c6647856088456] 
- RMP                   [(Partial) Autocorrelation Function] [] [2012-12-16 21:00:20] [c6861060a9fe16fe372e7d046f8d5b70] 
- R P                     [(Partial) Autocorrelation Function] [] [2012-12-16 21:07:20] [c6861060a9fe16fe372e7d046f8d5b70] 
-   P                       [(Partial) Autocorrelation Function] [] [2012-12-16 21:08:49] [c6861060a9fe16fe372e7d046f8d5b70] 
-   P                         [(Partial) Autocorrelation Function] [] [2012-12-16 21:12:34] [c6861060a9fe16fe372e7d046f8d5b70] 
-  M                            [(Partial) Autocorrelation Function] [] [2012-12-17 19:51:04] [74be16979710d4c4e7c6647856088456] 
- RMP                           [Variance Reduction Matrix] [] [2012-12-17 19:55:19] [c6861060a9fe16fe372e7d046f8d5b70] 
- RMP                           [Standard Deviation-Mean Plot] [] [2012-12-17 19:56:12] [c6861060a9fe16fe372e7d046f8d5b70] 
-  M                          [(Partial) Autocorrelation Function] [] [2012-12-17 19:48:09] [74be16979710d4c4e7c6647856088456] 
- R                       [(Partial) Autocorrelation Function] [] [2012-12-17 19:46:20] [74be16979710d4c4e7c6647856088456] 
-                           [(Partial) Autocorrelation Function] [] [2012-12-21 15:05:58] [c6861060a9fe16fe372e7d046f8d5b70] 

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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	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147867&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147867&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147867&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	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	9700	NA	NA	1.01811015886105	NA
2	9081	NA	NA	0.942756317261889	NA
3	9084	NA	NA	0.998124205504201	NA
4	9743	NA	NA	1.01580788866985	NA
5	8587	NA	NA	0.928977968043377	NA
6	9731	NA	NA	1.0239577741302	NA
7	9563	9315.15415480101	9512.54166666667	0.979249761127741	1.02660673576414
8	9998	9421.89243073486	9512.16666666667	0.990509603217093	1.06114563220716
9	9437	9470.70552502911	9512.29166666667	0.995628167943663	0.996441075594629
10	10038	9990.31112618686	9503.66666666667	1.05120596887379	1.00477351237722
11	9918	9891.18114011102	9497.70833333333	1.04142818382796	1.00271139103703
12	9252	9633.37405645077	9498.08333333333	1.01424400253919	0.960411164954672
13	9737	9639.5518266097	9468.08333333333	1.01811015886105	1.01010920166654
14	9035	8873.81168076719	9412.625	0.942756317261889	1.0181644962764
15	9133	9339.94725300556	9357.5	0.998124205504201	0.977842781399117
16	9487	9475.83691347058	9328.375	1.01580788866985	1.00117805811047
17	8700	8651.10732740394	9312.5	0.928977968043377	1.00565160860289
18	9627	9526.04983236227	9303.16666666667	1.0239577741302	1.0105972747796
19	8947	9107.43079922179	9300.41666666667	0.979249761127741	0.982384626053321
20	9283	9190.40208221633	9278.45833333333	0.990509603217093	1.01007550235075
21	8829	9224.86833656102	9265.375	0.995628167943663	0.957086830714746
22	9947	9746.86934389517	9272.08333333333	1.05120596887379	1.02053281408047
23	9628	9653.04122874235	9269.04166666666	1.04142818382796	0.997405871564312
24	9318	9375.9251204729	9244.25	1.01424400253919	0.993821930131841
25	9605	9415.10095783745	9247.625	1.01811015886105	1.02016962356675
26	8640	8732.51607771756	9262.75	0.942756317261889	0.98940556457106
27	9214	9257.39406350865	9274.79166666667	0.998124205504201	0.995312496885089
28	9567	9449.8491616521	9302.79166666667	1.01580788866985	1.01239711199024
29	8547	8643.21101467557	9304	0.928977968043377	0.98886860282455
30	9185	9533.0042122449	9309.95833333333	1.0239577741302	0.963494801376685
31	9470	9123.34360784012	9316.66666666667	0.979249761127741	1.03799663884872
32	9123	9225.06991832893	9313.45833333333	0.990509603217093	0.988935594067842
33	9278	9290.87018719428	9331.66666666667	0.995628167943663	0.998614749002518
34	10170	9829.56421344657	9350.75	1.05120596887379	1.03463386363433
35	9434	9763.82315179705	9375.41666666667	1.04142818382796	0.96621987651053
36	9655	9549.48762540742	9415.375	1.01424400253919	1.01104900898681
37	9429	9595.34887721248	9424.66666666667	1.01811015886105	0.982663592607088
38	8739	8872.67251688383	9411.41666666667	0.942756317261889	0.984934356967479
39	9552	9412.72714299024	9430.41666666667	0.998124205504201	1.01479622801065
40	9687	9607.08775775246	9457.58333333333	1.01580788866985	1.00831805061665
41	9019	8817.35567626837	9491.45833333333	0.928977968043377	1.02286902458459
42	9672	9756.35500172705	9528.08333333333	1.0239577741302	0.991353840475042
43	9206	9348.12223009231	9546.20833333333	0.979249761127741	0.984796708195063
44	9069	9487.92640428266	9578.83333333333	0.990509603217093	0.955846368697214
45	9788	9576.36656435213	9618.41666666667	0.995628167943663	1.02209955458845
46	10312	10128.807512586	9635.41666666667	1.05120596887379	1.01808628381835
47	10105	10036.503764596	9637.25	1.04142818382796	1.00682471077684
48	9863	9797.68158486212	9660.08333333333	1.01424400253919	1.00666672156797
49	9656	9878.21381634938	9702.5	1.01811015886105	0.977504656157413
50	9295	9194.07385804369	9752.33333333333	0.942756317261889	1.01097730380619
51	9946	9767.35235550417	9785.70833333333	0.998124205504201	1.018290283589
52	9701	9931.3844262103	9776.83333333333	1.01580788866985	0.976802385616824
53	9049	9082.8498380521	9777.25	0.928977968043377	0.996273213952047
54	10190	10034.4448672179	9799.66666666667	1.0239577741302	1.01550211644396
55	9706	9623.49542333611	9827.41666666667	0.979249761127741	1.00857324423554
56	9765	9751.77339983961	9845.20833333333	0.990509603217093	1.00135632767683
57	9893	9795.73663735572	9838.75	0.995628167943663	1.00992915247163
58	9994	10354.3787934068	9850	1.05120596887379	0.965195517703459
59	10433	10278.1151032441	9869.25	1.04142818382796	1.01506938725633
60	10073	10021.9562899236	9881.20833333333	1.01424400253919	1.00509318825584
61	10112	10068.3458885167	9889.25	1.01811015886105	1.00433577788911
62	9266	9347.31104111197	9914.875	0.942756317261889	0.991301130265769
63	9820	9933.83115528056	9952.5	0.998124205504201	0.988541062003047
64	10097	10136.662270379	9978.91666666667	1.01580788866985	0.99608724555272
65	9115	9290.39899907913	10000.6666666667	0.928977968043377	0.981120401922833
66	10411	10268.9311974937	10028.6666666667	1.0239577741302	1.01383481881162
67	9678	9865.12530189438	10074.1666666667	0.979249761127741	0.981031634554257
68	10408	10021.4809105489	10117.5	0.990509603217093	1.03856905909427
69	10153	10081.8967666255	10126.1666666667	0.995628167943663	1.00705256510956
70	10368	NA	NA	1.05120596887379	NA
71	10581	NA	NA	1.04142818382796	NA
72	10597	NA	NA	1.01424400253919	NA
73	10680	NA	NA	NA	NA
74	9738	NA	NA	NA	NA
75	9556	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 9700 & NA & NA & 1.01811015886105 & NA \tabularnewline
2 & 9081 & NA & NA & 0.942756317261889 & NA \tabularnewline
3 & 9084 & NA & NA & 0.998124205504201 & NA \tabularnewline
4 & 9743 & NA & NA & 1.01580788866985 & NA \tabularnewline
5 & 8587 & NA & NA & 0.928977968043377 & NA \tabularnewline
6 & 9731 & NA & NA & 1.0239577741302 & NA \tabularnewline
7 & 9563 & 9315.15415480101 & 9512.54166666667 & 0.979249761127741 & 1.02660673576414 \tabularnewline
8 & 9998 & 9421.89243073486 & 9512.16666666667 & 0.990509603217093 & 1.06114563220716 \tabularnewline
9 & 9437 & 9470.70552502911 & 9512.29166666667 & 0.995628167943663 & 0.996441075594629 \tabularnewline
10 & 10038 & 9990.31112618686 & 9503.66666666667 & 1.05120596887379 & 1.00477351237722 \tabularnewline
11 & 9918 & 9891.18114011102 & 9497.70833333333 & 1.04142818382796 & 1.00271139103703 \tabularnewline
12 & 9252 & 9633.37405645077 & 9498.08333333333 & 1.01424400253919 & 0.960411164954672 \tabularnewline
13 & 9737 & 9639.5518266097 & 9468.08333333333 & 1.01811015886105 & 1.01010920166654 \tabularnewline
14 & 9035 & 8873.81168076719 & 9412.625 & 0.942756317261889 & 1.0181644962764 \tabularnewline
15 & 9133 & 9339.94725300556 & 9357.5 & 0.998124205504201 & 0.977842781399117 \tabularnewline
16 & 9487 & 9475.83691347058 & 9328.375 & 1.01580788866985 & 1.00117805811047 \tabularnewline
17 & 8700 & 8651.10732740394 & 9312.5 & 0.928977968043377 & 1.00565160860289 \tabularnewline
18 & 9627 & 9526.04983236227 & 9303.16666666667 & 1.0239577741302 & 1.0105972747796 \tabularnewline
19 & 8947 & 9107.43079922179 & 9300.41666666667 & 0.979249761127741 & 0.982384626053321 \tabularnewline
20 & 9283 & 9190.40208221633 & 9278.45833333333 & 0.990509603217093 & 1.01007550235075 \tabularnewline
21 & 8829 & 9224.86833656102 & 9265.375 & 0.995628167943663 & 0.957086830714746 \tabularnewline
22 & 9947 & 9746.86934389517 & 9272.08333333333 & 1.05120596887379 & 1.02053281408047 \tabularnewline
23 & 9628 & 9653.04122874235 & 9269.04166666666 & 1.04142818382796 & 0.997405871564312 \tabularnewline
24 & 9318 & 9375.9251204729 & 9244.25 & 1.01424400253919 & 0.993821930131841 \tabularnewline
25 & 9605 & 9415.10095783745 & 9247.625 & 1.01811015886105 & 1.02016962356675 \tabularnewline
26 & 8640 & 8732.51607771756 & 9262.75 & 0.942756317261889 & 0.98940556457106 \tabularnewline
27 & 9214 & 9257.39406350865 & 9274.79166666667 & 0.998124205504201 & 0.995312496885089 \tabularnewline
28 & 9567 & 9449.8491616521 & 9302.79166666667 & 1.01580788866985 & 1.01239711199024 \tabularnewline
29 & 8547 & 8643.21101467557 & 9304 & 0.928977968043377 & 0.98886860282455 \tabularnewline
30 & 9185 & 9533.0042122449 & 9309.95833333333 & 1.0239577741302 & 0.963494801376685 \tabularnewline
31 & 9470 & 9123.34360784012 & 9316.66666666667 & 0.979249761127741 & 1.03799663884872 \tabularnewline
32 & 9123 & 9225.06991832893 & 9313.45833333333 & 0.990509603217093 & 0.988935594067842 \tabularnewline
33 & 9278 & 9290.87018719428 & 9331.66666666667 & 0.995628167943663 & 0.998614749002518 \tabularnewline
34 & 10170 & 9829.56421344657 & 9350.75 & 1.05120596887379 & 1.03463386363433 \tabularnewline
35 & 9434 & 9763.82315179705 & 9375.41666666667 & 1.04142818382796 & 0.96621987651053 \tabularnewline
36 & 9655 & 9549.48762540742 & 9415.375 & 1.01424400253919 & 1.01104900898681 \tabularnewline
37 & 9429 & 9595.34887721248 & 9424.66666666667 & 1.01811015886105 & 0.982663592607088 \tabularnewline
38 & 8739 & 8872.67251688383 & 9411.41666666667 & 0.942756317261889 & 0.984934356967479 \tabularnewline
39 & 9552 & 9412.72714299024 & 9430.41666666667 & 0.998124205504201 & 1.01479622801065 \tabularnewline
40 & 9687 & 9607.08775775246 & 9457.58333333333 & 1.01580788866985 & 1.00831805061665 \tabularnewline
41 & 9019 & 8817.35567626837 & 9491.45833333333 & 0.928977968043377 & 1.02286902458459 \tabularnewline
42 & 9672 & 9756.35500172705 & 9528.08333333333 & 1.0239577741302 & 0.991353840475042 \tabularnewline
43 & 9206 & 9348.12223009231 & 9546.20833333333 & 0.979249761127741 & 0.984796708195063 \tabularnewline
44 & 9069 & 9487.92640428266 & 9578.83333333333 & 0.990509603217093 & 0.955846368697214 \tabularnewline
45 & 9788 & 9576.36656435213 & 9618.41666666667 & 0.995628167943663 & 1.02209955458845 \tabularnewline
46 & 10312 & 10128.807512586 & 9635.41666666667 & 1.05120596887379 & 1.01808628381835 \tabularnewline
47 & 10105 & 10036.503764596 & 9637.25 & 1.04142818382796 & 1.00682471077684 \tabularnewline
48 & 9863 & 9797.68158486212 & 9660.08333333333 & 1.01424400253919 & 1.00666672156797 \tabularnewline
49 & 9656 & 9878.21381634938 & 9702.5 & 1.01811015886105 & 0.977504656157413 \tabularnewline
50 & 9295 & 9194.07385804369 & 9752.33333333333 & 0.942756317261889 & 1.01097730380619 \tabularnewline
51 & 9946 & 9767.35235550417 & 9785.70833333333 & 0.998124205504201 & 1.018290283589 \tabularnewline
52 & 9701 & 9931.3844262103 & 9776.83333333333 & 1.01580788866985 & 0.976802385616824 \tabularnewline
53 & 9049 & 9082.8498380521 & 9777.25 & 0.928977968043377 & 0.996273213952047 \tabularnewline
54 & 10190 & 10034.4448672179 & 9799.66666666667 & 1.0239577741302 & 1.01550211644396 \tabularnewline
55 & 9706 & 9623.49542333611 & 9827.41666666667 & 0.979249761127741 & 1.00857324423554 \tabularnewline
56 & 9765 & 9751.77339983961 & 9845.20833333333 & 0.990509603217093 & 1.00135632767683 \tabularnewline
57 & 9893 & 9795.73663735572 & 9838.75 & 0.995628167943663 & 1.00992915247163 \tabularnewline
58 & 9994 & 10354.3787934068 & 9850 & 1.05120596887379 & 0.965195517703459 \tabularnewline
59 & 10433 & 10278.1151032441 & 9869.25 & 1.04142818382796 & 1.01506938725633 \tabularnewline
60 & 10073 & 10021.9562899236 & 9881.20833333333 & 1.01424400253919 & 1.00509318825584 \tabularnewline
61 & 10112 & 10068.3458885167 & 9889.25 & 1.01811015886105 & 1.00433577788911 \tabularnewline
62 & 9266 & 9347.31104111197 & 9914.875 & 0.942756317261889 & 0.991301130265769 \tabularnewline
63 & 9820 & 9933.83115528056 & 9952.5 & 0.998124205504201 & 0.988541062003047 \tabularnewline
64 & 10097 & 10136.662270379 & 9978.91666666667 & 1.01580788866985 & 0.99608724555272 \tabularnewline
65 & 9115 & 9290.39899907913 & 10000.6666666667 & 0.928977968043377 & 0.981120401922833 \tabularnewline
66 & 10411 & 10268.9311974937 & 10028.6666666667 & 1.0239577741302 & 1.01383481881162 \tabularnewline
67 & 9678 & 9865.12530189438 & 10074.1666666667 & 0.979249761127741 & 0.981031634554257 \tabularnewline
68 & 10408 & 10021.4809105489 & 10117.5 & 0.990509603217093 & 1.03856905909427 \tabularnewline
69 & 10153 & 10081.8967666255 & 10126.1666666667 & 0.995628167943663 & 1.00705256510956 \tabularnewline
70 & 10368 & NA & NA & 1.05120596887379 & NA \tabularnewline
71 & 10581 & NA & NA & 1.04142818382796 & NA \tabularnewline
72 & 10597 & NA & NA & 1.01424400253919 & NA \tabularnewline
73 & 10680 & NA & NA & NA & NA \tabularnewline
74 & 9738 & NA & NA & NA & NA \tabularnewline
75 & 9556 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147867&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]9700[/C][C]NA[/C][C]NA[/C][C]1.01811015886105[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9081[/C][C]NA[/C][C]NA[/C][C]0.942756317261889[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]9084[/C][C]NA[/C][C]NA[/C][C]0.998124205504201[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]9743[/C][C]NA[/C][C]NA[/C][C]1.01580788866985[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]8587[/C][C]NA[/C][C]NA[/C][C]0.928977968043377[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]9731[/C][C]NA[/C][C]NA[/C][C]1.0239577741302[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]9563[/C][C]9315.15415480101[/C][C]9512.54166666667[/C][C]0.979249761127741[/C][C]1.02660673576414[/C][/ROW]
[ROW][C]8[/C][C]9998[/C][C]9421.89243073486[/C][C]9512.16666666667[/C][C]0.990509603217093[/C][C]1.06114563220716[/C][/ROW]
[ROW][C]9[/C][C]9437[/C][C]9470.70552502911[/C][C]9512.29166666667[/C][C]0.995628167943663[/C][C]0.996441075594629[/C][/ROW]
[ROW][C]10[/C][C]10038[/C][C]9990.31112618686[/C][C]9503.66666666667[/C][C]1.05120596887379[/C][C]1.00477351237722[/C][/ROW]
[ROW][C]11[/C][C]9918[/C][C]9891.18114011102[/C][C]9497.70833333333[/C][C]1.04142818382796[/C][C]1.00271139103703[/C][/ROW]
[ROW][C]12[/C][C]9252[/C][C]9633.37405645077[/C][C]9498.08333333333[/C][C]1.01424400253919[/C][C]0.960411164954672[/C][/ROW]
[ROW][C]13[/C][C]9737[/C][C]9639.5518266097[/C][C]9468.08333333333[/C][C]1.01811015886105[/C][C]1.01010920166654[/C][/ROW]
[ROW][C]14[/C][C]9035[/C][C]8873.81168076719[/C][C]9412.625[/C][C]0.942756317261889[/C][C]1.0181644962764[/C][/ROW]
[ROW][C]15[/C][C]9133[/C][C]9339.94725300556[/C][C]9357.5[/C][C]0.998124205504201[/C][C]0.977842781399117[/C][/ROW]
[ROW][C]16[/C][C]9487[/C][C]9475.83691347058[/C][C]9328.375[/C][C]1.01580788866985[/C][C]1.00117805811047[/C][/ROW]
[ROW][C]17[/C][C]8700[/C][C]8651.10732740394[/C][C]9312.5[/C][C]0.928977968043377[/C][C]1.00565160860289[/C][/ROW]
[ROW][C]18[/C][C]9627[/C][C]9526.04983236227[/C][C]9303.16666666667[/C][C]1.0239577741302[/C][C]1.0105972747796[/C][/ROW]
[ROW][C]19[/C][C]8947[/C][C]9107.43079922179[/C][C]9300.41666666667[/C][C]0.979249761127741[/C][C]0.982384626053321[/C][/ROW]
[ROW][C]20[/C][C]9283[/C][C]9190.40208221633[/C][C]9278.45833333333[/C][C]0.990509603217093[/C][C]1.01007550235075[/C][/ROW]
[ROW][C]21[/C][C]8829[/C][C]9224.86833656102[/C][C]9265.375[/C][C]0.995628167943663[/C][C]0.957086830714746[/C][/ROW]
[ROW][C]22[/C][C]9947[/C][C]9746.86934389517[/C][C]9272.08333333333[/C][C]1.05120596887379[/C][C]1.02053281408047[/C][/ROW]
[ROW][C]23[/C][C]9628[/C][C]9653.04122874235[/C][C]9269.04166666666[/C][C]1.04142818382796[/C][C]0.997405871564312[/C][/ROW]
[ROW][C]24[/C][C]9318[/C][C]9375.9251204729[/C][C]9244.25[/C][C]1.01424400253919[/C][C]0.993821930131841[/C][/ROW]
[ROW][C]25[/C][C]9605[/C][C]9415.10095783745[/C][C]9247.625[/C][C]1.01811015886105[/C][C]1.02016962356675[/C][/ROW]
[ROW][C]26[/C][C]8640[/C][C]8732.51607771756[/C][C]9262.75[/C][C]0.942756317261889[/C][C]0.98940556457106[/C][/ROW]
[ROW][C]27[/C][C]9214[/C][C]9257.39406350865[/C][C]9274.79166666667[/C][C]0.998124205504201[/C][C]0.995312496885089[/C][/ROW]
[ROW][C]28[/C][C]9567[/C][C]9449.8491616521[/C][C]9302.79166666667[/C][C]1.01580788866985[/C][C]1.01239711199024[/C][/ROW]
[ROW][C]29[/C][C]8547[/C][C]8643.21101467557[/C][C]9304[/C][C]0.928977968043377[/C][C]0.98886860282455[/C][/ROW]
[ROW][C]30[/C][C]9185[/C][C]9533.0042122449[/C][C]9309.95833333333[/C][C]1.0239577741302[/C][C]0.963494801376685[/C][/ROW]
[ROW][C]31[/C][C]9470[/C][C]9123.34360784012[/C][C]9316.66666666667[/C][C]0.979249761127741[/C][C]1.03799663884872[/C][/ROW]
[ROW][C]32[/C][C]9123[/C][C]9225.06991832893[/C][C]9313.45833333333[/C][C]0.990509603217093[/C][C]0.988935594067842[/C][/ROW]
[ROW][C]33[/C][C]9278[/C][C]9290.87018719428[/C][C]9331.66666666667[/C][C]0.995628167943663[/C][C]0.998614749002518[/C][/ROW]
[ROW][C]34[/C][C]10170[/C][C]9829.56421344657[/C][C]9350.75[/C][C]1.05120596887379[/C][C]1.03463386363433[/C][/ROW]
[ROW][C]35[/C][C]9434[/C][C]9763.82315179705[/C][C]9375.41666666667[/C][C]1.04142818382796[/C][C]0.96621987651053[/C][/ROW]
[ROW][C]36[/C][C]9655[/C][C]9549.48762540742[/C][C]9415.375[/C][C]1.01424400253919[/C][C]1.01104900898681[/C][/ROW]
[ROW][C]37[/C][C]9429[/C][C]9595.34887721248[/C][C]9424.66666666667[/C][C]1.01811015886105[/C][C]0.982663592607088[/C][/ROW]
[ROW][C]38[/C][C]8739[/C][C]8872.67251688383[/C][C]9411.41666666667[/C][C]0.942756317261889[/C][C]0.984934356967479[/C][/ROW]
[ROW][C]39[/C][C]9552[/C][C]9412.72714299024[/C][C]9430.41666666667[/C][C]0.998124205504201[/C][C]1.01479622801065[/C][/ROW]
[ROW][C]40[/C][C]9687[/C][C]9607.08775775246[/C][C]9457.58333333333[/C][C]1.01580788866985[/C][C]1.00831805061665[/C][/ROW]
[ROW][C]41[/C][C]9019[/C][C]8817.35567626837[/C][C]9491.45833333333[/C][C]0.928977968043377[/C][C]1.02286902458459[/C][/ROW]
[ROW][C]42[/C][C]9672[/C][C]9756.35500172705[/C][C]9528.08333333333[/C][C]1.0239577741302[/C][C]0.991353840475042[/C][/ROW]
[ROW][C]43[/C][C]9206[/C][C]9348.12223009231[/C][C]9546.20833333333[/C][C]0.979249761127741[/C][C]0.984796708195063[/C][/ROW]
[ROW][C]44[/C][C]9069[/C][C]9487.92640428266[/C][C]9578.83333333333[/C][C]0.990509603217093[/C][C]0.955846368697214[/C][/ROW]
[ROW][C]45[/C][C]9788[/C][C]9576.36656435213[/C][C]9618.41666666667[/C][C]0.995628167943663[/C][C]1.02209955458845[/C][/ROW]
[ROW][C]46[/C][C]10312[/C][C]10128.807512586[/C][C]9635.41666666667[/C][C]1.05120596887379[/C][C]1.01808628381835[/C][/ROW]
[ROW][C]47[/C][C]10105[/C][C]10036.503764596[/C][C]9637.25[/C][C]1.04142818382796[/C][C]1.00682471077684[/C][/ROW]
[ROW][C]48[/C][C]9863[/C][C]9797.68158486212[/C][C]9660.08333333333[/C][C]1.01424400253919[/C][C]1.00666672156797[/C][/ROW]
[ROW][C]49[/C][C]9656[/C][C]9878.21381634938[/C][C]9702.5[/C][C]1.01811015886105[/C][C]0.977504656157413[/C][/ROW]
[ROW][C]50[/C][C]9295[/C][C]9194.07385804369[/C][C]9752.33333333333[/C][C]0.942756317261889[/C][C]1.01097730380619[/C][/ROW]
[ROW][C]51[/C][C]9946[/C][C]9767.35235550417[/C][C]9785.70833333333[/C][C]0.998124205504201[/C][C]1.018290283589[/C][/ROW]
[ROW][C]52[/C][C]9701[/C][C]9931.3844262103[/C][C]9776.83333333333[/C][C]1.01580788866985[/C][C]0.976802385616824[/C][/ROW]
[ROW][C]53[/C][C]9049[/C][C]9082.8498380521[/C][C]9777.25[/C][C]0.928977968043377[/C][C]0.996273213952047[/C][/ROW]
[ROW][C]54[/C][C]10190[/C][C]10034.4448672179[/C][C]9799.66666666667[/C][C]1.0239577741302[/C][C]1.01550211644396[/C][/ROW]
[ROW][C]55[/C][C]9706[/C][C]9623.49542333611[/C][C]9827.41666666667[/C][C]0.979249761127741[/C][C]1.00857324423554[/C][/ROW]
[ROW][C]56[/C][C]9765[/C][C]9751.77339983961[/C][C]9845.20833333333[/C][C]0.990509603217093[/C][C]1.00135632767683[/C][/ROW]
[ROW][C]57[/C][C]9893[/C][C]9795.73663735572[/C][C]9838.75[/C][C]0.995628167943663[/C][C]1.00992915247163[/C][/ROW]
[ROW][C]58[/C][C]9994[/C][C]10354.3787934068[/C][C]9850[/C][C]1.05120596887379[/C][C]0.965195517703459[/C][/ROW]
[ROW][C]59[/C][C]10433[/C][C]10278.1151032441[/C][C]9869.25[/C][C]1.04142818382796[/C][C]1.01506938725633[/C][/ROW]
[ROW][C]60[/C][C]10073[/C][C]10021.9562899236[/C][C]9881.20833333333[/C][C]1.01424400253919[/C][C]1.00509318825584[/C][/ROW]
[ROW][C]61[/C][C]10112[/C][C]10068.3458885167[/C][C]9889.25[/C][C]1.01811015886105[/C][C]1.00433577788911[/C][/ROW]
[ROW][C]62[/C][C]9266[/C][C]9347.31104111197[/C][C]9914.875[/C][C]0.942756317261889[/C][C]0.991301130265769[/C][/ROW]
[ROW][C]63[/C][C]9820[/C][C]9933.83115528056[/C][C]9952.5[/C][C]0.998124205504201[/C][C]0.988541062003047[/C][/ROW]
[ROW][C]64[/C][C]10097[/C][C]10136.662270379[/C][C]9978.91666666667[/C][C]1.01580788866985[/C][C]0.99608724555272[/C][/ROW]
[ROW][C]65[/C][C]9115[/C][C]9290.39899907913[/C][C]10000.6666666667[/C][C]0.928977968043377[/C][C]0.981120401922833[/C][/ROW]
[ROW][C]66[/C][C]10411[/C][C]10268.9311974937[/C][C]10028.6666666667[/C][C]1.0239577741302[/C][C]1.01383481881162[/C][/ROW]
[ROW][C]67[/C][C]9678[/C][C]9865.12530189438[/C][C]10074.1666666667[/C][C]0.979249761127741[/C][C]0.981031634554257[/C][/ROW]
[ROW][C]68[/C][C]10408[/C][C]10021.4809105489[/C][C]10117.5[/C][C]0.990509603217093[/C][C]1.03856905909427[/C][/ROW]
[ROW][C]69[/C][C]10153[/C][C]10081.8967666255[/C][C]10126.1666666667[/C][C]0.995628167943663[/C][C]1.00705256510956[/C][/ROW]
[ROW][C]70[/C][C]10368[/C][C]NA[/C][C]NA[/C][C]1.05120596887379[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]10581[/C][C]NA[/C][C]NA[/C][C]1.04142818382796[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]10597[/C][C]NA[/C][C]NA[/C][C]1.01424400253919[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]10680[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]74[/C][C]9738[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]75[/C][C]9556[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147867&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147867&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	9700	NA	NA	1.01811015886105	NA
2	9081	NA	NA	0.942756317261889	NA
3	9084	NA	NA	0.998124205504201	NA
4	9743	NA	NA	1.01580788866985	NA
5	8587	NA	NA	0.928977968043377	NA
6	9731	NA	NA	1.0239577741302	NA
7	9563	9315.15415480101	9512.54166666667	0.979249761127741	1.02660673576414
8	9998	9421.89243073486	9512.16666666667	0.990509603217093	1.06114563220716
9	9437	9470.70552502911	9512.29166666667	0.995628167943663	0.996441075594629
10	10038	9990.31112618686	9503.66666666667	1.05120596887379	1.00477351237722
11	9918	9891.18114011102	9497.70833333333	1.04142818382796	1.00271139103703
12	9252	9633.37405645077	9498.08333333333	1.01424400253919	0.960411164954672
13	9737	9639.5518266097	9468.08333333333	1.01811015886105	1.01010920166654
14	9035	8873.81168076719	9412.625	0.942756317261889	1.0181644962764
15	9133	9339.94725300556	9357.5	0.998124205504201	0.977842781399117
16	9487	9475.83691347058	9328.375	1.01580788866985	1.00117805811047
17	8700	8651.10732740394	9312.5	0.928977968043377	1.00565160860289
18	9627	9526.04983236227	9303.16666666667	1.0239577741302	1.0105972747796
19	8947	9107.43079922179	9300.41666666667	0.979249761127741	0.982384626053321
20	9283	9190.40208221633	9278.45833333333	0.990509603217093	1.01007550235075
21	8829	9224.86833656102	9265.375	0.995628167943663	0.957086830714746
22	9947	9746.86934389517	9272.08333333333	1.05120596887379	1.02053281408047
23	9628	9653.04122874235	9269.04166666666	1.04142818382796	0.997405871564312
24	9318	9375.9251204729	9244.25	1.01424400253919	0.993821930131841
25	9605	9415.10095783745	9247.625	1.01811015886105	1.02016962356675
26	8640	8732.51607771756	9262.75	0.942756317261889	0.98940556457106
27	9214	9257.39406350865	9274.79166666667	0.998124205504201	0.995312496885089
28	9567	9449.8491616521	9302.79166666667	1.01580788866985	1.01239711199024
29	8547	8643.21101467557	9304	0.928977968043377	0.98886860282455
30	9185	9533.0042122449	9309.95833333333	1.0239577741302	0.963494801376685
31	9470	9123.34360784012	9316.66666666667	0.979249761127741	1.03799663884872
32	9123	9225.06991832893	9313.45833333333	0.990509603217093	0.988935594067842
33	9278	9290.87018719428	9331.66666666667	0.995628167943663	0.998614749002518
34	10170	9829.56421344657	9350.75	1.05120596887379	1.03463386363433
35	9434	9763.82315179705	9375.41666666667	1.04142818382796	0.96621987651053
36	9655	9549.48762540742	9415.375	1.01424400253919	1.01104900898681
37	9429	9595.34887721248	9424.66666666667	1.01811015886105	0.982663592607088
38	8739	8872.67251688383	9411.41666666667	0.942756317261889	0.984934356967479
39	9552	9412.72714299024	9430.41666666667	0.998124205504201	1.01479622801065
40	9687	9607.08775775246	9457.58333333333	1.01580788866985	1.00831805061665
41	9019	8817.35567626837	9491.45833333333	0.928977968043377	1.02286902458459
42	9672	9756.35500172705	9528.08333333333	1.0239577741302	0.991353840475042
43	9206	9348.12223009231	9546.20833333333	0.979249761127741	0.984796708195063
44	9069	9487.92640428266	9578.83333333333	0.990509603217093	0.955846368697214
45	9788	9576.36656435213	9618.41666666667	0.995628167943663	1.02209955458845
46	10312	10128.807512586	9635.41666666667	1.05120596887379	1.01808628381835
47	10105	10036.503764596	9637.25	1.04142818382796	1.00682471077684
48	9863	9797.68158486212	9660.08333333333	1.01424400253919	1.00666672156797
49	9656	9878.21381634938	9702.5	1.01811015886105	0.977504656157413
50	9295	9194.07385804369	9752.33333333333	0.942756317261889	1.01097730380619
51	9946	9767.35235550417	9785.70833333333	0.998124205504201	1.018290283589
52	9701	9931.3844262103	9776.83333333333	1.01580788866985	0.976802385616824
53	9049	9082.8498380521	9777.25	0.928977968043377	0.996273213952047
54	10190	10034.4448672179	9799.66666666667	1.0239577741302	1.01550211644396
55	9706	9623.49542333611	9827.41666666667	0.979249761127741	1.00857324423554
56	9765	9751.77339983961	9845.20833333333	0.990509603217093	1.00135632767683
57	9893	9795.73663735572	9838.75	0.995628167943663	1.00992915247163
58	9994	10354.3787934068	9850	1.05120596887379	0.965195517703459
59	10433	10278.1151032441	9869.25	1.04142818382796	1.01506938725633
60	10073	10021.9562899236	9881.20833333333	1.01424400253919	1.00509318825584
61	10112	10068.3458885167	9889.25	1.01811015886105	1.00433577788911
62	9266	9347.31104111197	9914.875	0.942756317261889	0.991301130265769
63	9820	9933.83115528056	9952.5	0.998124205504201	0.988541062003047
64	10097	10136.662270379	9978.91666666667	1.01580788866985	0.99608724555272
65	9115	9290.39899907913	10000.6666666667	0.928977968043377	0.981120401922833
66	10411	10268.9311974937	10028.6666666667	1.0239577741302	1.01383481881162
67	9678	9865.12530189438	10074.1666666667	0.979249761127741	0.981031634554257
68	10408	10021.4809105489	10117.5	0.990509603217093	1.03856905909427
69	10153	10081.8967666255	10126.1666666667	0.995628167943663	1.00705256510956
70	10368	NA	NA	1.05120596887379	NA
71	10581	NA	NA	1.04142818382796	NA
72	10597	NA	NA	1.01424400253919	NA
73	10680	NA	NA	NA	NA
74	9738	NA	NA	NA	NA
75	9556	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 = 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