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Author

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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 19 Dec 2012 17:49:10 -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/2012/Dec/19/t1355957386zcn1ynpn163p1we.htm/, Retrieved Fri, 01 Nov 2024 00:03:04 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=202460, Retrieved Fri, 01 Nov 2024 00:03:04 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

103

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]
- RMP         [Classical Decomposition] [Classical Decompo...] [2012-12-16 18:18:45] [f5077040b712f13d41cbe2e9b961fc0e]
- R P             [Classical Decomposition] [Multiplicatieve m...] [2012-12-19 22:49:10] [4bea8166bbee0e00c4800f3bcc822f1b] [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	4 seconds
R Server	'George Udny Yule' @ yule.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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202460&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202460&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202460&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' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	9700	NA	NA	1.01644971718006	NA
2	9081	NA	NA	0.941218770592134	NA
3	9084	NA	NA	0.996496359028844	NA
4	9743	NA	NA	1.01415120177448	NA
5	8587	NA	NA	0.927462892562165	NA
6	9731	NA	NA	1.02228779554002	NA
7	9563	9342.86436350146	9512.54166666667	0.982162779506157	1.0235619000698
8	9998	9504.12522355389	9512.16666666667	0.999154614989983	1.05196425392441
9	9437	9451.29144722635	9512.29166666667	0.993587221504774	0.998487884189569
10	10038	10070.7453680243	9503.66666666667	1.05966946456009	0.996748466292451
11	9918	9862.09653660449	9497.70833333333	1.03836590790984	1.00566851715434
12	9252	9583.50220731205	9498.08333333333	1.00899327485146	0.965409074872532
13	9737	9623.83062640392	9468.08333333333	1.01644971718006	1.01175928567213
14	9035	8859.33933054478	9412.625	0.941218770592134	1.01982773916895
15	9133	9324.71467961241	9357.5	0.996496359028844	0.979440155951198
16	9487	9460.38271685297	9328.375	1.01415120177448	1.00281355246861
17	8700	8636.99818698516	9312.5	0.927462892562165	1.00729441081854
18	9627	9510.51374320806	9303.16666666667	1.02228779554002	1.01224815608674
19	8947	9134.52308389872	9300.41666666667	0.982162779506157	0.979470949695309
20	9283	9270.61446374227	9278.45833333333	0.999154614989983	1.00133599949671
21	8829	9205.95820244979	9265.375	0.993587221504774	0.959052801005605
22	9947	9825.3435811899	9272.08333333333	1.05966946456009	1.0123818997071
23	9628	9624.65686566244	9269.04166666666	1.03836590790984	1.00034735101565
24	9318	9327.38608104559	9244.25	1.00899327485146	0.998993707244019
25	9605	9399.74581583726	9247.625	1.01644971718006	1.02183614197492
26	8640	8718.27416730228	9262.75	0.941218770592134	0.991021827737897
27	9214	9242.2961265844	9274.79166666667	0.996496359028844	0.996938409438862
28	9567	9434.43734860757	9302.79166666667	1.01415120177448	1.01405093345731
29	8547	8629.11475239838	9304	0.927462892562165	0.990483988826831
30	9185	9517.45678115277	9309.95833333333	1.02228779554002	0.965068737500219
31	9470	9150.4832290657	9316.66666666667	0.982162779506157	1.03491802158813
32	9123	9305.58487526692	9313.45833333333	0.999154614989983	0.98037900059864
33	9278	9271.82475534205	9331.66666666667	0.993587221504774	1.00066602258141
34	10170	9908.7042457353	9350.75	1.05966946456009	1.02637032530032
35	9434	9735.11303911636	9375.41666666667	1.03836590790984	0.969069384412234
36	9655	9500.05005520455	9415.375	1.00899327485146	1.01631043456561
37	9429	9579.69976784968	9424.66666666667	1.01644971718006	0.984268842291337
38	8739	8858.20202453032	9411.41666666667	0.941218770592134	0.986543316104079
39	9552	9397.37587245826	9430.41666666667	0.996496359028844	1.01645396860148
40	9687	9591.41950338225	9457.58333333333	1.01415120177448	1.00996520865176
41	9019	8802.9754004666	9491.45833333333	0.927462892562165	1.02453995265305
42	9672	9740.44330655493	9528.08333333333	1.02228779554002	0.992973286286788
43	9206	9375.9305104115	9546.20833333333	0.982162779506157	0.981875877789111
44	9069	9570.73553121988	9578.83333333333	0.999154614989983	0.94757607400359
45	9788	9556.73589110854	9618.41666666667	0.993587221504774	1.02419906875386
46	10312	10210.3568199801	9635.41666666667	1.05966946456009	1.00995490968749
47	10105	10006.9918460041	9637.25	1.03836590790984	1.00979396760826
48	9863	9746.95911783799	9660.08333333333	1.00899327485146	1.01190534204146
49	9656	9862.10338093954	9702.5	1.01644971718006	0.97910147835827
50	9295	9179.07919040468	9752.33333333333	0.941218770592134	1.01262880591732
51	9946	9751.42272468489	9785.70833333333	0.996496359028844	1.01995373196391
52	9701	9915.18727454875	9776.83333333333	1.01415120177448	0.978398060609652
53	9049	9068.03656630342	9777.25	0.927462892562165	0.99790069590432
54	10190	10018.0796336937	9799.66666666667	1.02228779554002	1.01716101015289
55	9706	9652.12286869847	9827.41666666667	0.982162779506157	1.00558189447383
56	9765	9836.88534178784	9845.20833333333	0.999154614989983	0.992692265967311
57	9893	9775.65627558009	9838.75	0.993587221504774	1.01200366718223
58	9994	10437.7442259169	9850	1.05966946456009	0.957486577912581
59	10433	10247.8927366392	9869.25	1.03836590790984	1.01806295870946
60	10073	9970.07275573952	9881.20833333333	1.00899327485146	1.01032362017632
61	10112	10051.9253656229	9889.25	1.01644971718006	1.00597643060329
62	9266	9332.06645807468	9914.875	0.941218770592134	0.992920489971702
63	9820	9917.63001323457	9952.5	0.996496359028844	0.990155912944495
64	10097	10120.1303299073	9978.91666666667	1.01415120177448	0.997714423712609
65	9115	9275.24723421669	10000.6666666667	0.927462892562165	0.982723130697204
66	10411	10252.1835388723	10028.6666666667	1.02228779554002	1.0154909888733
67	9678	9894.47153454161	10074.1666666667	0.982162779506157	0.97812197106375
68	10408	10108.9468171612	10117.5	0.999154614989983	1.02958302068927
69	10153	10061.2298028276	10126.1666666667	0.993587221504774	1.00912117096725
70	10368	NA	NA	1.05966946456009	NA
71	10581	NA	NA	1.03836590790984	NA
72	10597	NA	NA	1.00899327485146	NA
73	10680	NA	NA	1.01644971718006	NA
74	9738	NA	NA	0.941218770592134	NA
75	9556	NA	NA	0.996496359028844	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 9700 & NA & NA & 1.01644971718006 & NA \tabularnewline
2 & 9081 & NA & NA & 0.941218770592134 & NA \tabularnewline
3 & 9084 & NA & NA & 0.996496359028844 & NA \tabularnewline
4 & 9743 & NA & NA & 1.01415120177448 & NA \tabularnewline
5 & 8587 & NA & NA & 0.927462892562165 & NA \tabularnewline
6 & 9731 & NA & NA & 1.02228779554002 & NA \tabularnewline
7 & 9563 & 9342.86436350146 & 9512.54166666667 & 0.982162779506157 & 1.0235619000698 \tabularnewline
8 & 9998 & 9504.12522355389 & 9512.16666666667 & 0.999154614989983 & 1.05196425392441 \tabularnewline
9 & 9437 & 9451.29144722635 & 9512.29166666667 & 0.993587221504774 & 0.998487884189569 \tabularnewline
10 & 10038 & 10070.7453680243 & 9503.66666666667 & 1.05966946456009 & 0.996748466292451 \tabularnewline
11 & 9918 & 9862.09653660449 & 9497.70833333333 & 1.03836590790984 & 1.00566851715434 \tabularnewline
12 & 9252 & 9583.50220731205 & 9498.08333333333 & 1.00899327485146 & 0.965409074872532 \tabularnewline
13 & 9737 & 9623.83062640392 & 9468.08333333333 & 1.01644971718006 & 1.01175928567213 \tabularnewline
14 & 9035 & 8859.33933054478 & 9412.625 & 0.941218770592134 & 1.01982773916895 \tabularnewline
15 & 9133 & 9324.71467961241 & 9357.5 & 0.996496359028844 & 0.979440155951198 \tabularnewline
16 & 9487 & 9460.38271685297 & 9328.375 & 1.01415120177448 & 1.00281355246861 \tabularnewline
17 & 8700 & 8636.99818698516 & 9312.5 & 0.927462892562165 & 1.00729441081854 \tabularnewline
18 & 9627 & 9510.51374320806 & 9303.16666666667 & 1.02228779554002 & 1.01224815608674 \tabularnewline
19 & 8947 & 9134.52308389872 & 9300.41666666667 & 0.982162779506157 & 0.979470949695309 \tabularnewline
20 & 9283 & 9270.61446374227 & 9278.45833333333 & 0.999154614989983 & 1.00133599949671 \tabularnewline
21 & 8829 & 9205.95820244979 & 9265.375 & 0.993587221504774 & 0.959052801005605 \tabularnewline
22 & 9947 & 9825.3435811899 & 9272.08333333333 & 1.05966946456009 & 1.0123818997071 \tabularnewline
23 & 9628 & 9624.65686566244 & 9269.04166666666 & 1.03836590790984 & 1.00034735101565 \tabularnewline
24 & 9318 & 9327.38608104559 & 9244.25 & 1.00899327485146 & 0.998993707244019 \tabularnewline
25 & 9605 & 9399.74581583726 & 9247.625 & 1.01644971718006 & 1.02183614197492 \tabularnewline
26 & 8640 & 8718.27416730228 & 9262.75 & 0.941218770592134 & 0.991021827737897 \tabularnewline
27 & 9214 & 9242.2961265844 & 9274.79166666667 & 0.996496359028844 & 0.996938409438862 \tabularnewline
28 & 9567 & 9434.43734860757 & 9302.79166666667 & 1.01415120177448 & 1.01405093345731 \tabularnewline
29 & 8547 & 8629.11475239838 & 9304 & 0.927462892562165 & 0.990483988826831 \tabularnewline
30 & 9185 & 9517.45678115277 & 9309.95833333333 & 1.02228779554002 & 0.965068737500219 \tabularnewline
31 & 9470 & 9150.4832290657 & 9316.66666666667 & 0.982162779506157 & 1.03491802158813 \tabularnewline
32 & 9123 & 9305.58487526692 & 9313.45833333333 & 0.999154614989983 & 0.98037900059864 \tabularnewline
33 & 9278 & 9271.82475534205 & 9331.66666666667 & 0.993587221504774 & 1.00066602258141 \tabularnewline
34 & 10170 & 9908.7042457353 & 9350.75 & 1.05966946456009 & 1.02637032530032 \tabularnewline
35 & 9434 & 9735.11303911636 & 9375.41666666667 & 1.03836590790984 & 0.969069384412234 \tabularnewline
36 & 9655 & 9500.05005520455 & 9415.375 & 1.00899327485146 & 1.01631043456561 \tabularnewline
37 & 9429 & 9579.69976784968 & 9424.66666666667 & 1.01644971718006 & 0.984268842291337 \tabularnewline
38 & 8739 & 8858.20202453032 & 9411.41666666667 & 0.941218770592134 & 0.986543316104079 \tabularnewline
39 & 9552 & 9397.37587245826 & 9430.41666666667 & 0.996496359028844 & 1.01645396860148 \tabularnewline
40 & 9687 & 9591.41950338225 & 9457.58333333333 & 1.01415120177448 & 1.00996520865176 \tabularnewline
41 & 9019 & 8802.9754004666 & 9491.45833333333 & 0.927462892562165 & 1.02453995265305 \tabularnewline
42 & 9672 & 9740.44330655493 & 9528.08333333333 & 1.02228779554002 & 0.992973286286788 \tabularnewline
43 & 9206 & 9375.9305104115 & 9546.20833333333 & 0.982162779506157 & 0.981875877789111 \tabularnewline
44 & 9069 & 9570.73553121988 & 9578.83333333333 & 0.999154614989983 & 0.94757607400359 \tabularnewline
45 & 9788 & 9556.73589110854 & 9618.41666666667 & 0.993587221504774 & 1.02419906875386 \tabularnewline
46 & 10312 & 10210.3568199801 & 9635.41666666667 & 1.05966946456009 & 1.00995490968749 \tabularnewline
47 & 10105 & 10006.9918460041 & 9637.25 & 1.03836590790984 & 1.00979396760826 \tabularnewline
48 & 9863 & 9746.95911783799 & 9660.08333333333 & 1.00899327485146 & 1.01190534204146 \tabularnewline
49 & 9656 & 9862.10338093954 & 9702.5 & 1.01644971718006 & 0.97910147835827 \tabularnewline
50 & 9295 & 9179.07919040468 & 9752.33333333333 & 0.941218770592134 & 1.01262880591732 \tabularnewline
51 & 9946 & 9751.42272468489 & 9785.70833333333 & 0.996496359028844 & 1.01995373196391 \tabularnewline
52 & 9701 & 9915.18727454875 & 9776.83333333333 & 1.01415120177448 & 0.978398060609652 \tabularnewline
53 & 9049 & 9068.03656630342 & 9777.25 & 0.927462892562165 & 0.99790069590432 \tabularnewline
54 & 10190 & 10018.0796336937 & 9799.66666666667 & 1.02228779554002 & 1.01716101015289 \tabularnewline
55 & 9706 & 9652.12286869847 & 9827.41666666667 & 0.982162779506157 & 1.00558189447383 \tabularnewline
56 & 9765 & 9836.88534178784 & 9845.20833333333 & 0.999154614989983 & 0.992692265967311 \tabularnewline
57 & 9893 & 9775.65627558009 & 9838.75 & 0.993587221504774 & 1.01200366718223 \tabularnewline
58 & 9994 & 10437.7442259169 & 9850 & 1.05966946456009 & 0.957486577912581 \tabularnewline
59 & 10433 & 10247.8927366392 & 9869.25 & 1.03836590790984 & 1.01806295870946 \tabularnewline
60 & 10073 & 9970.07275573952 & 9881.20833333333 & 1.00899327485146 & 1.01032362017632 \tabularnewline
61 & 10112 & 10051.9253656229 & 9889.25 & 1.01644971718006 & 1.00597643060329 \tabularnewline
62 & 9266 & 9332.06645807468 & 9914.875 & 0.941218770592134 & 0.992920489971702 \tabularnewline
63 & 9820 & 9917.63001323457 & 9952.5 & 0.996496359028844 & 0.990155912944495 \tabularnewline
64 & 10097 & 10120.1303299073 & 9978.91666666667 & 1.01415120177448 & 0.997714423712609 \tabularnewline
65 & 9115 & 9275.24723421669 & 10000.6666666667 & 0.927462892562165 & 0.982723130697204 \tabularnewline
66 & 10411 & 10252.1835388723 & 10028.6666666667 & 1.02228779554002 & 1.0154909888733 \tabularnewline
67 & 9678 & 9894.47153454161 & 10074.1666666667 & 0.982162779506157 & 0.97812197106375 \tabularnewline
68 & 10408 & 10108.9468171612 & 10117.5 & 0.999154614989983 & 1.02958302068927 \tabularnewline
69 & 10153 & 10061.2298028276 & 10126.1666666667 & 0.993587221504774 & 1.00912117096725 \tabularnewline
70 & 10368 & NA & NA & 1.05966946456009 & NA \tabularnewline
71 & 10581 & NA & NA & 1.03836590790984 & NA \tabularnewline
72 & 10597 & NA & NA & 1.00899327485146 & NA \tabularnewline
73 & 10680 & NA & NA & 1.01644971718006 & NA \tabularnewline
74 & 9738 & NA & NA & 0.941218770592134 & NA \tabularnewline
75 & 9556 & NA & NA & 0.996496359028844 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202460&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]1.01644971718006[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9081[/C][C]NA[/C][C]NA[/C][C]0.941218770592134[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]9084[/C][C]NA[/C][C]NA[/C][C]0.996496359028844[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]9743[/C][C]NA[/C][C]NA[/C][C]1.01415120177448[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]8587[/C][C]NA[/C][C]NA[/C][C]0.927462892562165[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]9731[/C][C]NA[/C][C]NA[/C][C]1.02228779554002[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]9563[/C][C]9342.86436350146[/C][C]9512.54166666667[/C][C]0.982162779506157[/C][C]1.0235619000698[/C][/ROW]
[ROW][C]8[/C][C]9998[/C][C]9504.12522355389[/C][C]9512.16666666667[/C][C]0.999154614989983[/C][C]1.05196425392441[/C][/ROW]
[ROW][C]9[/C][C]9437[/C][C]9451.29144722635[/C][C]9512.29166666667[/C][C]0.993587221504774[/C][C]0.998487884189569[/C][/ROW]
[ROW][C]10[/C][C]10038[/C][C]10070.7453680243[/C][C]9503.66666666667[/C][C]1.05966946456009[/C][C]0.996748466292451[/C][/ROW]
[ROW][C]11[/C][C]9918[/C][C]9862.09653660449[/C][C]9497.70833333333[/C][C]1.03836590790984[/C][C]1.00566851715434[/C][/ROW]
[ROW][C]12[/C][C]9252[/C][C]9583.50220731205[/C][C]9498.08333333333[/C][C]1.00899327485146[/C][C]0.965409074872532[/C][/ROW]
[ROW][C]13[/C][C]9737[/C][C]9623.83062640392[/C][C]9468.08333333333[/C][C]1.01644971718006[/C][C]1.01175928567213[/C][/ROW]
[ROW][C]14[/C][C]9035[/C][C]8859.33933054478[/C][C]9412.625[/C][C]0.941218770592134[/C][C]1.01982773916895[/C][/ROW]
[ROW][C]15[/C][C]9133[/C][C]9324.71467961241[/C][C]9357.5[/C][C]0.996496359028844[/C][C]0.979440155951198[/C][/ROW]
[ROW][C]16[/C][C]9487[/C][C]9460.38271685297[/C][C]9328.375[/C][C]1.01415120177448[/C][C]1.00281355246861[/C][/ROW]
[ROW][C]17[/C][C]8700[/C][C]8636.99818698516[/C][C]9312.5[/C][C]0.927462892562165[/C][C]1.00729441081854[/C][/ROW]
[ROW][C]18[/C][C]9627[/C][C]9510.51374320806[/C][C]9303.16666666667[/C][C]1.02228779554002[/C][C]1.01224815608674[/C][/ROW]
[ROW][C]19[/C][C]8947[/C][C]9134.52308389872[/C][C]9300.41666666667[/C][C]0.982162779506157[/C][C]0.979470949695309[/C][/ROW]
[ROW][C]20[/C][C]9283[/C][C]9270.61446374227[/C][C]9278.45833333333[/C][C]0.999154614989983[/C][C]1.00133599949671[/C][/ROW]
[ROW][C]21[/C][C]8829[/C][C]9205.95820244979[/C][C]9265.375[/C][C]0.993587221504774[/C][C]0.959052801005605[/C][/ROW]
[ROW][C]22[/C][C]9947[/C][C]9825.3435811899[/C][C]9272.08333333333[/C][C]1.05966946456009[/C][C]1.0123818997071[/C][/ROW]
[ROW][C]23[/C][C]9628[/C][C]9624.65686566244[/C][C]9269.04166666666[/C][C]1.03836590790984[/C][C]1.00034735101565[/C][/ROW]
[ROW][C]24[/C][C]9318[/C][C]9327.38608104559[/C][C]9244.25[/C][C]1.00899327485146[/C][C]0.998993707244019[/C][/ROW]
[ROW][C]25[/C][C]9605[/C][C]9399.74581583726[/C][C]9247.625[/C][C]1.01644971718006[/C][C]1.02183614197492[/C][/ROW]
[ROW][C]26[/C][C]8640[/C][C]8718.27416730228[/C][C]9262.75[/C][C]0.941218770592134[/C][C]0.991021827737897[/C][/ROW]
[ROW][C]27[/C][C]9214[/C][C]9242.2961265844[/C][C]9274.79166666667[/C][C]0.996496359028844[/C][C]0.996938409438862[/C][/ROW]
[ROW][C]28[/C][C]9567[/C][C]9434.43734860757[/C][C]9302.79166666667[/C][C]1.01415120177448[/C][C]1.01405093345731[/C][/ROW]
[ROW][C]29[/C][C]8547[/C][C]8629.11475239838[/C][C]9304[/C][C]0.927462892562165[/C][C]0.990483988826831[/C][/ROW]
[ROW][C]30[/C][C]9185[/C][C]9517.45678115277[/C][C]9309.95833333333[/C][C]1.02228779554002[/C][C]0.965068737500219[/C][/ROW]
[ROW][C]31[/C][C]9470[/C][C]9150.4832290657[/C][C]9316.66666666667[/C][C]0.982162779506157[/C][C]1.03491802158813[/C][/ROW]
[ROW][C]32[/C][C]9123[/C][C]9305.58487526692[/C][C]9313.45833333333[/C][C]0.999154614989983[/C][C]0.98037900059864[/C][/ROW]
[ROW][C]33[/C][C]9278[/C][C]9271.82475534205[/C][C]9331.66666666667[/C][C]0.993587221504774[/C][C]1.00066602258141[/C][/ROW]
[ROW][C]34[/C][C]10170[/C][C]9908.7042457353[/C][C]9350.75[/C][C]1.05966946456009[/C][C]1.02637032530032[/C][/ROW]
[ROW][C]35[/C][C]9434[/C][C]9735.11303911636[/C][C]9375.41666666667[/C][C]1.03836590790984[/C][C]0.969069384412234[/C][/ROW]
[ROW][C]36[/C][C]9655[/C][C]9500.05005520455[/C][C]9415.375[/C][C]1.00899327485146[/C][C]1.01631043456561[/C][/ROW]
[ROW][C]37[/C][C]9429[/C][C]9579.69976784968[/C][C]9424.66666666667[/C][C]1.01644971718006[/C][C]0.984268842291337[/C][/ROW]
[ROW][C]38[/C][C]8739[/C][C]8858.20202453032[/C][C]9411.41666666667[/C][C]0.941218770592134[/C][C]0.986543316104079[/C][/ROW]
[ROW][C]39[/C][C]9552[/C][C]9397.37587245826[/C][C]9430.41666666667[/C][C]0.996496359028844[/C][C]1.01645396860148[/C][/ROW]
[ROW][C]40[/C][C]9687[/C][C]9591.41950338225[/C][C]9457.58333333333[/C][C]1.01415120177448[/C][C]1.00996520865176[/C][/ROW]
[ROW][C]41[/C][C]9019[/C][C]8802.9754004666[/C][C]9491.45833333333[/C][C]0.927462892562165[/C][C]1.02453995265305[/C][/ROW]
[ROW][C]42[/C][C]9672[/C][C]9740.44330655493[/C][C]9528.08333333333[/C][C]1.02228779554002[/C][C]0.992973286286788[/C][/ROW]
[ROW][C]43[/C][C]9206[/C][C]9375.9305104115[/C][C]9546.20833333333[/C][C]0.982162779506157[/C][C]0.981875877789111[/C][/ROW]
[ROW][C]44[/C][C]9069[/C][C]9570.73553121988[/C][C]9578.83333333333[/C][C]0.999154614989983[/C][C]0.94757607400359[/C][/ROW]
[ROW][C]45[/C][C]9788[/C][C]9556.73589110854[/C][C]9618.41666666667[/C][C]0.993587221504774[/C][C]1.02419906875386[/C][/ROW]
[ROW][C]46[/C][C]10312[/C][C]10210.3568199801[/C][C]9635.41666666667[/C][C]1.05966946456009[/C][C]1.00995490968749[/C][/ROW]
[ROW][C]47[/C][C]10105[/C][C]10006.9918460041[/C][C]9637.25[/C][C]1.03836590790984[/C][C]1.00979396760826[/C][/ROW]
[ROW][C]48[/C][C]9863[/C][C]9746.95911783799[/C][C]9660.08333333333[/C][C]1.00899327485146[/C][C]1.01190534204146[/C][/ROW]
[ROW][C]49[/C][C]9656[/C][C]9862.10338093954[/C][C]9702.5[/C][C]1.01644971718006[/C][C]0.97910147835827[/C][/ROW]
[ROW][C]50[/C][C]9295[/C][C]9179.07919040468[/C][C]9752.33333333333[/C][C]0.941218770592134[/C][C]1.01262880591732[/C][/ROW]
[ROW][C]51[/C][C]9946[/C][C]9751.42272468489[/C][C]9785.70833333333[/C][C]0.996496359028844[/C][C]1.01995373196391[/C][/ROW]
[ROW][C]52[/C][C]9701[/C][C]9915.18727454875[/C][C]9776.83333333333[/C][C]1.01415120177448[/C][C]0.978398060609652[/C][/ROW]
[ROW][C]53[/C][C]9049[/C][C]9068.03656630342[/C][C]9777.25[/C][C]0.927462892562165[/C][C]0.99790069590432[/C][/ROW]
[ROW][C]54[/C][C]10190[/C][C]10018.0796336937[/C][C]9799.66666666667[/C][C]1.02228779554002[/C][C]1.01716101015289[/C][/ROW]
[ROW][C]55[/C][C]9706[/C][C]9652.12286869847[/C][C]9827.41666666667[/C][C]0.982162779506157[/C][C]1.00558189447383[/C][/ROW]
[ROW][C]56[/C][C]9765[/C][C]9836.88534178784[/C][C]9845.20833333333[/C][C]0.999154614989983[/C][C]0.992692265967311[/C][/ROW]
[ROW][C]57[/C][C]9893[/C][C]9775.65627558009[/C][C]9838.75[/C][C]0.993587221504774[/C][C]1.01200366718223[/C][/ROW]
[ROW][C]58[/C][C]9994[/C][C]10437.7442259169[/C][C]9850[/C][C]1.05966946456009[/C][C]0.957486577912581[/C][/ROW]
[ROW][C]59[/C][C]10433[/C][C]10247.8927366392[/C][C]9869.25[/C][C]1.03836590790984[/C][C]1.01806295870946[/C][/ROW]
[ROW][C]60[/C][C]10073[/C][C]9970.07275573952[/C][C]9881.20833333333[/C][C]1.00899327485146[/C][C]1.01032362017632[/C][/ROW]
[ROW][C]61[/C][C]10112[/C][C]10051.9253656229[/C][C]9889.25[/C][C]1.01644971718006[/C][C]1.00597643060329[/C][/ROW]
[ROW][C]62[/C][C]9266[/C][C]9332.06645807468[/C][C]9914.875[/C][C]0.941218770592134[/C][C]0.992920489971702[/C][/ROW]
[ROW][C]63[/C][C]9820[/C][C]9917.63001323457[/C][C]9952.5[/C][C]0.996496359028844[/C][C]0.990155912944495[/C][/ROW]
[ROW][C]64[/C][C]10097[/C][C]10120.1303299073[/C][C]9978.91666666667[/C][C]1.01415120177448[/C][C]0.997714423712609[/C][/ROW]
[ROW][C]65[/C][C]9115[/C][C]9275.24723421669[/C][C]10000.6666666667[/C][C]0.927462892562165[/C][C]0.982723130697204[/C][/ROW]
[ROW][C]66[/C][C]10411[/C][C]10252.1835388723[/C][C]10028.6666666667[/C][C]1.02228779554002[/C][C]1.0154909888733[/C][/ROW]
[ROW][C]67[/C][C]9678[/C][C]9894.47153454161[/C][C]10074.1666666667[/C][C]0.982162779506157[/C][C]0.97812197106375[/C][/ROW]
[ROW][C]68[/C][C]10408[/C][C]10108.9468171612[/C][C]10117.5[/C][C]0.999154614989983[/C][C]1.02958302068927[/C][/ROW]
[ROW][C]69[/C][C]10153[/C][C]10061.2298028276[/C][C]10126.1666666667[/C][C]0.993587221504774[/C][C]1.00912117096725[/C][/ROW]
[ROW][C]70[/C][C]10368[/C][C]NA[/C][C]NA[/C][C]1.05966946456009[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]10581[/C][C]NA[/C][C]NA[/C][C]1.03836590790984[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]10597[/C][C]NA[/C][C]NA[/C][C]1.00899327485146[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]10680[/C][C]NA[/C][C]NA[/C][C]1.01644971718006[/C][C]NA[/C][/ROW]
[ROW][C]74[/C][C]9738[/C][C]NA[/C][C]NA[/C][C]0.941218770592134[/C][C]NA[/C][/ROW]
[ROW][C]75[/C][C]9556[/C][C]NA[/C][C]NA[/C][C]0.996496359028844[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202460&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202460&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	1.01644971718006	NA
2	9081	NA	NA	0.941218770592134	NA
3	9084	NA	NA	0.996496359028844	NA
4	9743	NA	NA	1.01415120177448	NA
5	8587	NA	NA	0.927462892562165	NA
6	9731	NA	NA	1.02228779554002	NA
7	9563	9342.86436350146	9512.54166666667	0.982162779506157	1.0235619000698
8	9998	9504.12522355389	9512.16666666667	0.999154614989983	1.05196425392441
9	9437	9451.29144722635	9512.29166666667	0.993587221504774	0.998487884189569
10	10038	10070.7453680243	9503.66666666667	1.05966946456009	0.996748466292451
11	9918	9862.09653660449	9497.70833333333	1.03836590790984	1.00566851715434
12	9252	9583.50220731205	9498.08333333333	1.00899327485146	0.965409074872532
13	9737	9623.83062640392	9468.08333333333	1.01644971718006	1.01175928567213
14	9035	8859.33933054478	9412.625	0.941218770592134	1.01982773916895
15	9133	9324.71467961241	9357.5	0.996496359028844	0.979440155951198
16	9487	9460.38271685297	9328.375	1.01415120177448	1.00281355246861
17	8700	8636.99818698516	9312.5	0.927462892562165	1.00729441081854
18	9627	9510.51374320806	9303.16666666667	1.02228779554002	1.01224815608674
19	8947	9134.52308389872	9300.41666666667	0.982162779506157	0.979470949695309
20	9283	9270.61446374227	9278.45833333333	0.999154614989983	1.00133599949671
21	8829	9205.95820244979	9265.375	0.993587221504774	0.959052801005605
22	9947	9825.3435811899	9272.08333333333	1.05966946456009	1.0123818997071
23	9628	9624.65686566244	9269.04166666666	1.03836590790984	1.00034735101565
24	9318	9327.38608104559	9244.25	1.00899327485146	0.998993707244019
25	9605	9399.74581583726	9247.625	1.01644971718006	1.02183614197492
26	8640	8718.27416730228	9262.75	0.941218770592134	0.991021827737897
27	9214	9242.2961265844	9274.79166666667	0.996496359028844	0.996938409438862
28	9567	9434.43734860757	9302.79166666667	1.01415120177448	1.01405093345731
29	8547	8629.11475239838	9304	0.927462892562165	0.990483988826831
30	9185	9517.45678115277	9309.95833333333	1.02228779554002	0.965068737500219
31	9470	9150.4832290657	9316.66666666667	0.982162779506157	1.03491802158813
32	9123	9305.58487526692	9313.45833333333	0.999154614989983	0.98037900059864
33	9278	9271.82475534205	9331.66666666667	0.993587221504774	1.00066602258141
34	10170	9908.7042457353	9350.75	1.05966946456009	1.02637032530032
35	9434	9735.11303911636	9375.41666666667	1.03836590790984	0.969069384412234
36	9655	9500.05005520455	9415.375	1.00899327485146	1.01631043456561
37	9429	9579.69976784968	9424.66666666667	1.01644971718006	0.984268842291337
38	8739	8858.20202453032	9411.41666666667	0.941218770592134	0.986543316104079
39	9552	9397.37587245826	9430.41666666667	0.996496359028844	1.01645396860148
40	9687	9591.41950338225	9457.58333333333	1.01415120177448	1.00996520865176
41	9019	8802.9754004666	9491.45833333333	0.927462892562165	1.02453995265305
42	9672	9740.44330655493	9528.08333333333	1.02228779554002	0.992973286286788
43	9206	9375.9305104115	9546.20833333333	0.982162779506157	0.981875877789111
44	9069	9570.73553121988	9578.83333333333	0.999154614989983	0.94757607400359
45	9788	9556.73589110854	9618.41666666667	0.993587221504774	1.02419906875386
46	10312	10210.3568199801	9635.41666666667	1.05966946456009	1.00995490968749
47	10105	10006.9918460041	9637.25	1.03836590790984	1.00979396760826
48	9863	9746.95911783799	9660.08333333333	1.00899327485146	1.01190534204146
49	9656	9862.10338093954	9702.5	1.01644971718006	0.97910147835827
50	9295	9179.07919040468	9752.33333333333	0.941218770592134	1.01262880591732
51	9946	9751.42272468489	9785.70833333333	0.996496359028844	1.01995373196391
52	9701	9915.18727454875	9776.83333333333	1.01415120177448	0.978398060609652
53	9049	9068.03656630342	9777.25	0.927462892562165	0.99790069590432
54	10190	10018.0796336937	9799.66666666667	1.02228779554002	1.01716101015289
55	9706	9652.12286869847	9827.41666666667	0.982162779506157	1.00558189447383
56	9765	9836.88534178784	9845.20833333333	0.999154614989983	0.992692265967311
57	9893	9775.65627558009	9838.75	0.993587221504774	1.01200366718223
58	9994	10437.7442259169	9850	1.05966946456009	0.957486577912581
59	10433	10247.8927366392	9869.25	1.03836590790984	1.01806295870946
60	10073	9970.07275573952	9881.20833333333	1.00899327485146	1.01032362017632
61	10112	10051.9253656229	9889.25	1.01644971718006	1.00597643060329
62	9266	9332.06645807468	9914.875	0.941218770592134	0.992920489971702
63	9820	9917.63001323457	9952.5	0.996496359028844	0.990155912944495
64	10097	10120.1303299073	9978.91666666667	1.01415120177448	0.997714423712609
65	9115	9275.24723421669	10000.6666666667	0.927462892562165	0.982723130697204
66	10411	10252.1835388723	10028.6666666667	1.02228779554002	1.0154909888733
67	9678	9894.47153454161	10074.1666666667	0.982162779506157	0.97812197106375
68	10408	10108.9468171612	10117.5	0.999154614989983	1.02958302068927
69	10153	10061.2298028276	10126.1666666667	0.993587221504774	1.00912117096725
70	10368	NA	NA	1.05966946456009	NA
71	10581	NA	NA	1.03836590790984	NA
72	10597	NA	NA	1.00899327485146	NA
73	10680	NA	NA	1.01644971718006	NA
74	9738	NA	NA	0.941218770592134	NA
75	9556	NA	NA	0.996496359028844	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