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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 24 Nov 2015 12:57:34 +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/2015/Nov/24/t1448369959a00bsmffd8ntohr.htm/, Retrieved Tue, 14 May 2024 11:52:33 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284013, Retrieved Tue, 14 May 2024 11:52:33 +0000

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Estimated Impact

128

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

-       [Classical Decomposition] [Classical Deompos...] [2015-11-24 12:57:34] [25948359fd1b125334369436fee15348] [Current]

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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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284013&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284013&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284013&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	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.91	NA	NA	0.12509	NA
2	98.15	NA	NA	-0.20141	NA
3	98.59	NA	NA	0.000673611	NA
4	98.6	NA	NA	-0.0384931	NA
5	98.7	NA	NA	0.00109028	NA
6	98.33	NA	NA	-0.107243	NA
7	98.33	98.4742	98.6817	-0.207493	-0.144174
8	98.6	98.5644	98.6467	-0.0822431	0.0355764
9	98.52	98.564	98.6437	-0.0797431	-0.0440069
10	99.17	98.7833	98.68	0.10334	0.38666
11	99.49	99.013	98.6896	0.323424	0.476993
12	98.83	98.8605	98.6975	0.163007	-0.0305069
13	98.83	98.8343	98.7092	0.12509	-0.00425694
14	97.39	98.4811	98.6825	-0.20141	-1.09109
15	99.28	98.6203	98.6196	0.000673611	0.659743
16	98.78	98.5003	98.5387	-0.0384931	0.279743
17	98.75	98.4361	98.435	0.00109028	0.31391
18	98.47	98.254	98.3612	-0.107243	0.215993
19	98.47	98.1129	98.3204	-0.207493	0.357076
20	97.82	98.2636	98.3458	-0.0822431	-0.44359
21	97.79	98.2644	98.3442	-0.0797431	-0.474424
22	97.96	98.3696	98.2662	0.10334	-0.40959
23	98.21	98.5184	98.195	0.323424	-0.308424
24	98.34	98.2805	98.1175	0.163007	0.0594931
25	98.34	98.1693	98.0442	0.12509	0.170743
26	98.49	97.7998	98.0013	-0.20141	0.69016
27	98.14	97.9907	97.99	0.000673611	0.149326
28	98.05	97.9215	97.96	-0.0384931	0.128493
29	97.77	97.8986	97.8975	0.00109028	-0.12859
30	97.59	97.7069	97.8142	-0.107243	-0.116924
31	97.59	97.515	97.7225	-0.207493	0.0749931
32	97.67	97.5278	97.61	-0.0822431	0.142243
33	97.67	97.3944	97.4742	-0.0797431	0.275576
34	97.36	97.4425	97.3392	0.10334	-0.0825069
35	97.31	97.5701	97.2467	0.323424	-0.26009
36	97.24	97.3672	97.2042	0.163007	-0.127174
37	97.24	97.3068	97.1817	0.12509	-0.0667569
38	96.89	96.9865	97.1879	-0.20141	-0.0965069
39	96.48	97.214	97.2133	0.000673611	-0.734007
40	96.47	97.2223	97.2608	-0.0384931	-0.75234
41	97.13	97.3536	97.3525	0.00109028	-0.22359
42	97.21	97.3648	97.4721	-0.107243	-0.15484
43	97.43	97.3913	97.5988	-0.207493	0.0387431
44	97.98	97.6565	97.7387	-0.0822431	0.323493
45	97.97	97.8498	97.9296	-0.0797431	0.12016
46	98.2	98.2808	98.1775	0.10334	-0.0808403
47	98.67	98.7438	98.4204	0.323424	-0.0738403
48	98.75	98.7913	98.6283	0.163007	-0.0413403
49	98.77	98.9409	98.8158	0.12509	-0.170924
50	98.72	98.7965	98.9979	-0.20141	-0.0765069
51	99.23	99.2019	99.2012	0.000673611	0.0280764
52	99.67	99.3919	99.4304	-0.0384931	0.278076
53	99.76	99.6648	99.6638	0.00109028	0.0951597
54	99.57	99.7823	99.8896	-0.107243	-0.21234
55	99.57	99.9079	100.115	-0.207493	-0.337924
56	100.21	100.279	100.361	-0.0822431	-0.0690069
57	100.62	100.509	100.588	-0.0797431	0.11141
58	101.05	100.875	100.772	0.10334	0.174993
59	101.42	101.266	100.942	0.323424	0.154076
60	101.42	101.292	101.129	0.163007	0.128243
61	101.52	101.46	101.335	0.12509	0.0599097
62	101.87	101.307	101.509	-0.20141	0.56266
63	101.53	101.644	101.644	0.000673611	-0.114424
64	101.77	101.715	101.754	-0.0384931	0.0547431
65	101.76	101.828	101.827	0.00109028	-0.0681736
66	102.04	101.783	101.89	-0.107243	0.256826
67	102.05	NA	NA	-0.207493	NA
68	101.9	NA	NA	-0.0822431	NA
69	102.17	NA	NA	-0.0797431	NA
70	102.14	NA	NA	0.10334	NA
71	102.09	NA	NA	0.323424	NA
72	102.27	NA	NA	0.163007	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 98.91 & NA & NA & 0.12509 & NA \tabularnewline
2 & 98.15 & NA & NA & -0.20141 & NA \tabularnewline
3 & 98.59 & NA & NA & 0.000673611 & NA \tabularnewline
4 & 98.6 & NA & NA & -0.0384931 & NA \tabularnewline
5 & 98.7 & NA & NA & 0.00109028 & NA \tabularnewline
6 & 98.33 & NA & NA & -0.107243 & NA \tabularnewline
7 & 98.33 & 98.4742 & 98.6817 & -0.207493 & -0.144174 \tabularnewline
8 & 98.6 & 98.5644 & 98.6467 & -0.0822431 & 0.0355764 \tabularnewline
9 & 98.52 & 98.564 & 98.6437 & -0.0797431 & -0.0440069 \tabularnewline
10 & 99.17 & 98.7833 & 98.68 & 0.10334 & 0.38666 \tabularnewline
11 & 99.49 & 99.013 & 98.6896 & 0.323424 & 0.476993 \tabularnewline
12 & 98.83 & 98.8605 & 98.6975 & 0.163007 & -0.0305069 \tabularnewline
13 & 98.83 & 98.8343 & 98.7092 & 0.12509 & -0.00425694 \tabularnewline
14 & 97.39 & 98.4811 & 98.6825 & -0.20141 & -1.09109 \tabularnewline
15 & 99.28 & 98.6203 & 98.6196 & 0.000673611 & 0.659743 \tabularnewline
16 & 98.78 & 98.5003 & 98.5387 & -0.0384931 & 0.279743 \tabularnewline
17 & 98.75 & 98.4361 & 98.435 & 0.00109028 & 0.31391 \tabularnewline
18 & 98.47 & 98.254 & 98.3612 & -0.107243 & 0.215993 \tabularnewline
19 & 98.47 & 98.1129 & 98.3204 & -0.207493 & 0.357076 \tabularnewline
20 & 97.82 & 98.2636 & 98.3458 & -0.0822431 & -0.44359 \tabularnewline
21 & 97.79 & 98.2644 & 98.3442 & -0.0797431 & -0.474424 \tabularnewline
22 & 97.96 & 98.3696 & 98.2662 & 0.10334 & -0.40959 \tabularnewline
23 & 98.21 & 98.5184 & 98.195 & 0.323424 & -0.308424 \tabularnewline
24 & 98.34 & 98.2805 & 98.1175 & 0.163007 & 0.0594931 \tabularnewline
25 & 98.34 & 98.1693 & 98.0442 & 0.12509 & 0.170743 \tabularnewline
26 & 98.49 & 97.7998 & 98.0013 & -0.20141 & 0.69016 \tabularnewline
27 & 98.14 & 97.9907 & 97.99 & 0.000673611 & 0.149326 \tabularnewline
28 & 98.05 & 97.9215 & 97.96 & -0.0384931 & 0.128493 \tabularnewline
29 & 97.77 & 97.8986 & 97.8975 & 0.00109028 & -0.12859 \tabularnewline
30 & 97.59 & 97.7069 & 97.8142 & -0.107243 & -0.116924 \tabularnewline
31 & 97.59 & 97.515 & 97.7225 & -0.207493 & 0.0749931 \tabularnewline
32 & 97.67 & 97.5278 & 97.61 & -0.0822431 & 0.142243 \tabularnewline
33 & 97.67 & 97.3944 & 97.4742 & -0.0797431 & 0.275576 \tabularnewline
34 & 97.36 & 97.4425 & 97.3392 & 0.10334 & -0.0825069 \tabularnewline
35 & 97.31 & 97.5701 & 97.2467 & 0.323424 & -0.26009 \tabularnewline
36 & 97.24 & 97.3672 & 97.2042 & 0.163007 & -0.127174 \tabularnewline
37 & 97.24 & 97.3068 & 97.1817 & 0.12509 & -0.0667569 \tabularnewline
38 & 96.89 & 96.9865 & 97.1879 & -0.20141 & -0.0965069 \tabularnewline
39 & 96.48 & 97.214 & 97.2133 & 0.000673611 & -0.734007 \tabularnewline
40 & 96.47 & 97.2223 & 97.2608 & -0.0384931 & -0.75234 \tabularnewline
41 & 97.13 & 97.3536 & 97.3525 & 0.00109028 & -0.22359 \tabularnewline
42 & 97.21 & 97.3648 & 97.4721 & -0.107243 & -0.15484 \tabularnewline
43 & 97.43 & 97.3913 & 97.5988 & -0.207493 & 0.0387431 \tabularnewline
44 & 97.98 & 97.6565 & 97.7387 & -0.0822431 & 0.323493 \tabularnewline
45 & 97.97 & 97.8498 & 97.9296 & -0.0797431 & 0.12016 \tabularnewline
46 & 98.2 & 98.2808 & 98.1775 & 0.10334 & -0.0808403 \tabularnewline
47 & 98.67 & 98.7438 & 98.4204 & 0.323424 & -0.0738403 \tabularnewline
48 & 98.75 & 98.7913 & 98.6283 & 0.163007 & -0.0413403 \tabularnewline
49 & 98.77 & 98.9409 & 98.8158 & 0.12509 & -0.170924 \tabularnewline
50 & 98.72 & 98.7965 & 98.9979 & -0.20141 & -0.0765069 \tabularnewline
51 & 99.23 & 99.2019 & 99.2012 & 0.000673611 & 0.0280764 \tabularnewline
52 & 99.67 & 99.3919 & 99.4304 & -0.0384931 & 0.278076 \tabularnewline
53 & 99.76 & 99.6648 & 99.6638 & 0.00109028 & 0.0951597 \tabularnewline
54 & 99.57 & 99.7823 & 99.8896 & -0.107243 & -0.21234 \tabularnewline
55 & 99.57 & 99.9079 & 100.115 & -0.207493 & -0.337924 \tabularnewline
56 & 100.21 & 100.279 & 100.361 & -0.0822431 & -0.0690069 \tabularnewline
57 & 100.62 & 100.509 & 100.588 & -0.0797431 & 0.11141 \tabularnewline
58 & 101.05 & 100.875 & 100.772 & 0.10334 & 0.174993 \tabularnewline
59 & 101.42 & 101.266 & 100.942 & 0.323424 & 0.154076 \tabularnewline
60 & 101.42 & 101.292 & 101.129 & 0.163007 & 0.128243 \tabularnewline
61 & 101.52 & 101.46 & 101.335 & 0.12509 & 0.0599097 \tabularnewline
62 & 101.87 & 101.307 & 101.509 & -0.20141 & 0.56266 \tabularnewline
63 & 101.53 & 101.644 & 101.644 & 0.000673611 & -0.114424 \tabularnewline
64 & 101.77 & 101.715 & 101.754 & -0.0384931 & 0.0547431 \tabularnewline
65 & 101.76 & 101.828 & 101.827 & 0.00109028 & -0.0681736 \tabularnewline
66 & 102.04 & 101.783 & 101.89 & -0.107243 & 0.256826 \tabularnewline
67 & 102.05 & NA & NA & -0.207493 & NA \tabularnewline
68 & 101.9 & NA & NA & -0.0822431 & NA \tabularnewline
69 & 102.17 & NA & NA & -0.0797431 & NA \tabularnewline
70 & 102.14 & NA & NA & 0.10334 & NA \tabularnewline
71 & 102.09 & NA & NA & 0.323424 & NA \tabularnewline
72 & 102.27 & NA & NA & 0.163007 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284013&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]98.91[/C][C]NA[/C][C]NA[/C][C]0.12509[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]98.15[/C][C]NA[/C][C]NA[/C][C]-0.20141[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]98.59[/C][C]NA[/C][C]NA[/C][C]0.000673611[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]98.6[/C][C]NA[/C][C]NA[/C][C]-0.0384931[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]98.7[/C][C]NA[/C][C]NA[/C][C]0.00109028[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]98.33[/C][C]NA[/C][C]NA[/C][C]-0.107243[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]98.33[/C][C]98.4742[/C][C]98.6817[/C][C]-0.207493[/C][C]-0.144174[/C][/ROW]
[ROW][C]8[/C][C]98.6[/C][C]98.5644[/C][C]98.6467[/C][C]-0.0822431[/C][C]0.0355764[/C][/ROW]
[ROW][C]9[/C][C]98.52[/C][C]98.564[/C][C]98.6437[/C][C]-0.0797431[/C][C]-0.0440069[/C][/ROW]
[ROW][C]10[/C][C]99.17[/C][C]98.7833[/C][C]98.68[/C][C]0.10334[/C][C]0.38666[/C][/ROW]
[ROW][C]11[/C][C]99.49[/C][C]99.013[/C][C]98.6896[/C][C]0.323424[/C][C]0.476993[/C][/ROW]
[ROW][C]12[/C][C]98.83[/C][C]98.8605[/C][C]98.6975[/C][C]0.163007[/C][C]-0.0305069[/C][/ROW]
[ROW][C]13[/C][C]98.83[/C][C]98.8343[/C][C]98.7092[/C][C]0.12509[/C][C]-0.00425694[/C][/ROW]
[ROW][C]14[/C][C]97.39[/C][C]98.4811[/C][C]98.6825[/C][C]-0.20141[/C][C]-1.09109[/C][/ROW]
[ROW][C]15[/C][C]99.28[/C][C]98.6203[/C][C]98.6196[/C][C]0.000673611[/C][C]0.659743[/C][/ROW]
[ROW][C]16[/C][C]98.78[/C][C]98.5003[/C][C]98.5387[/C][C]-0.0384931[/C][C]0.279743[/C][/ROW]
[ROW][C]17[/C][C]98.75[/C][C]98.4361[/C][C]98.435[/C][C]0.00109028[/C][C]0.31391[/C][/ROW]
[ROW][C]18[/C][C]98.47[/C][C]98.254[/C][C]98.3612[/C][C]-0.107243[/C][C]0.215993[/C][/ROW]
[ROW][C]19[/C][C]98.47[/C][C]98.1129[/C][C]98.3204[/C][C]-0.207493[/C][C]0.357076[/C][/ROW]
[ROW][C]20[/C][C]97.82[/C][C]98.2636[/C][C]98.3458[/C][C]-0.0822431[/C][C]-0.44359[/C][/ROW]
[ROW][C]21[/C][C]97.79[/C][C]98.2644[/C][C]98.3442[/C][C]-0.0797431[/C][C]-0.474424[/C][/ROW]
[ROW][C]22[/C][C]97.96[/C][C]98.3696[/C][C]98.2662[/C][C]0.10334[/C][C]-0.40959[/C][/ROW]
[ROW][C]23[/C][C]98.21[/C][C]98.5184[/C][C]98.195[/C][C]0.323424[/C][C]-0.308424[/C][/ROW]
[ROW][C]24[/C][C]98.34[/C][C]98.2805[/C][C]98.1175[/C][C]0.163007[/C][C]0.0594931[/C][/ROW]
[ROW][C]25[/C][C]98.34[/C][C]98.1693[/C][C]98.0442[/C][C]0.12509[/C][C]0.170743[/C][/ROW]
[ROW][C]26[/C][C]98.49[/C][C]97.7998[/C][C]98.0013[/C][C]-0.20141[/C][C]0.69016[/C][/ROW]
[ROW][C]27[/C][C]98.14[/C][C]97.9907[/C][C]97.99[/C][C]0.000673611[/C][C]0.149326[/C][/ROW]
[ROW][C]28[/C][C]98.05[/C][C]97.9215[/C][C]97.96[/C][C]-0.0384931[/C][C]0.128493[/C][/ROW]
[ROW][C]29[/C][C]97.77[/C][C]97.8986[/C][C]97.8975[/C][C]0.00109028[/C][C]-0.12859[/C][/ROW]
[ROW][C]30[/C][C]97.59[/C][C]97.7069[/C][C]97.8142[/C][C]-0.107243[/C][C]-0.116924[/C][/ROW]
[ROW][C]31[/C][C]97.59[/C][C]97.515[/C][C]97.7225[/C][C]-0.207493[/C][C]0.0749931[/C][/ROW]
[ROW][C]32[/C][C]97.67[/C][C]97.5278[/C][C]97.61[/C][C]-0.0822431[/C][C]0.142243[/C][/ROW]
[ROW][C]33[/C][C]97.67[/C][C]97.3944[/C][C]97.4742[/C][C]-0.0797431[/C][C]0.275576[/C][/ROW]
[ROW][C]34[/C][C]97.36[/C][C]97.4425[/C][C]97.3392[/C][C]0.10334[/C][C]-0.0825069[/C][/ROW]
[ROW][C]35[/C][C]97.31[/C][C]97.5701[/C][C]97.2467[/C][C]0.323424[/C][C]-0.26009[/C][/ROW]
[ROW][C]36[/C][C]97.24[/C][C]97.3672[/C][C]97.2042[/C][C]0.163007[/C][C]-0.127174[/C][/ROW]
[ROW][C]37[/C][C]97.24[/C][C]97.3068[/C][C]97.1817[/C][C]0.12509[/C][C]-0.0667569[/C][/ROW]
[ROW][C]38[/C][C]96.89[/C][C]96.9865[/C][C]97.1879[/C][C]-0.20141[/C][C]-0.0965069[/C][/ROW]
[ROW][C]39[/C][C]96.48[/C][C]97.214[/C][C]97.2133[/C][C]0.000673611[/C][C]-0.734007[/C][/ROW]
[ROW][C]40[/C][C]96.47[/C][C]97.2223[/C][C]97.2608[/C][C]-0.0384931[/C][C]-0.75234[/C][/ROW]
[ROW][C]41[/C][C]97.13[/C][C]97.3536[/C][C]97.3525[/C][C]0.00109028[/C][C]-0.22359[/C][/ROW]
[ROW][C]42[/C][C]97.21[/C][C]97.3648[/C][C]97.4721[/C][C]-0.107243[/C][C]-0.15484[/C][/ROW]
[ROW][C]43[/C][C]97.43[/C][C]97.3913[/C][C]97.5988[/C][C]-0.207493[/C][C]0.0387431[/C][/ROW]
[ROW][C]44[/C][C]97.98[/C][C]97.6565[/C][C]97.7387[/C][C]-0.0822431[/C][C]0.323493[/C][/ROW]
[ROW][C]45[/C][C]97.97[/C][C]97.8498[/C][C]97.9296[/C][C]-0.0797431[/C][C]0.12016[/C][/ROW]
[ROW][C]46[/C][C]98.2[/C][C]98.2808[/C][C]98.1775[/C][C]0.10334[/C][C]-0.0808403[/C][/ROW]
[ROW][C]47[/C][C]98.67[/C][C]98.7438[/C][C]98.4204[/C][C]0.323424[/C][C]-0.0738403[/C][/ROW]
[ROW][C]48[/C][C]98.75[/C][C]98.7913[/C][C]98.6283[/C][C]0.163007[/C][C]-0.0413403[/C][/ROW]
[ROW][C]49[/C][C]98.77[/C][C]98.9409[/C][C]98.8158[/C][C]0.12509[/C][C]-0.170924[/C][/ROW]
[ROW][C]50[/C][C]98.72[/C][C]98.7965[/C][C]98.9979[/C][C]-0.20141[/C][C]-0.0765069[/C][/ROW]
[ROW][C]51[/C][C]99.23[/C][C]99.2019[/C][C]99.2012[/C][C]0.000673611[/C][C]0.0280764[/C][/ROW]
[ROW][C]52[/C][C]99.67[/C][C]99.3919[/C][C]99.4304[/C][C]-0.0384931[/C][C]0.278076[/C][/ROW]
[ROW][C]53[/C][C]99.76[/C][C]99.6648[/C][C]99.6638[/C][C]0.00109028[/C][C]0.0951597[/C][/ROW]
[ROW][C]54[/C][C]99.57[/C][C]99.7823[/C][C]99.8896[/C][C]-0.107243[/C][C]-0.21234[/C][/ROW]
[ROW][C]55[/C][C]99.57[/C][C]99.9079[/C][C]100.115[/C][C]-0.207493[/C][C]-0.337924[/C][/ROW]
[ROW][C]56[/C][C]100.21[/C][C]100.279[/C][C]100.361[/C][C]-0.0822431[/C][C]-0.0690069[/C][/ROW]
[ROW][C]57[/C][C]100.62[/C][C]100.509[/C][C]100.588[/C][C]-0.0797431[/C][C]0.11141[/C][/ROW]
[ROW][C]58[/C][C]101.05[/C][C]100.875[/C][C]100.772[/C][C]0.10334[/C][C]0.174993[/C][/ROW]
[ROW][C]59[/C][C]101.42[/C][C]101.266[/C][C]100.942[/C][C]0.323424[/C][C]0.154076[/C][/ROW]
[ROW][C]60[/C][C]101.42[/C][C]101.292[/C][C]101.129[/C][C]0.163007[/C][C]0.128243[/C][/ROW]
[ROW][C]61[/C][C]101.52[/C][C]101.46[/C][C]101.335[/C][C]0.12509[/C][C]0.0599097[/C][/ROW]
[ROW][C]62[/C][C]101.87[/C][C]101.307[/C][C]101.509[/C][C]-0.20141[/C][C]0.56266[/C][/ROW]
[ROW][C]63[/C][C]101.53[/C][C]101.644[/C][C]101.644[/C][C]0.000673611[/C][C]-0.114424[/C][/ROW]
[ROW][C]64[/C][C]101.77[/C][C]101.715[/C][C]101.754[/C][C]-0.0384931[/C][C]0.0547431[/C][/ROW]
[ROW][C]65[/C][C]101.76[/C][C]101.828[/C][C]101.827[/C][C]0.00109028[/C][C]-0.0681736[/C][/ROW]
[ROW][C]66[/C][C]102.04[/C][C]101.783[/C][C]101.89[/C][C]-0.107243[/C][C]0.256826[/C][/ROW]
[ROW][C]67[/C][C]102.05[/C][C]NA[/C][C]NA[/C][C]-0.207493[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.9[/C][C]NA[/C][C]NA[/C][C]-0.0822431[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]102.17[/C][C]NA[/C][C]NA[/C][C]-0.0797431[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]102.14[/C][C]NA[/C][C]NA[/C][C]0.10334[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]102.09[/C][C]NA[/C][C]NA[/C][C]0.323424[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]102.27[/C][C]NA[/C][C]NA[/C][C]0.163007[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284013&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284013&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	98.91	NA	NA	0.12509	NA
2	98.15	NA	NA	-0.20141	NA
3	98.59	NA	NA	0.000673611	NA
4	98.6	NA	NA	-0.0384931	NA
5	98.7	NA	NA	0.00109028	NA
6	98.33	NA	NA	-0.107243	NA
7	98.33	98.4742	98.6817	-0.207493	-0.144174
8	98.6	98.5644	98.6467	-0.0822431	0.0355764
9	98.52	98.564	98.6437	-0.0797431	-0.0440069
10	99.17	98.7833	98.68	0.10334	0.38666
11	99.49	99.013	98.6896	0.323424	0.476993
12	98.83	98.8605	98.6975	0.163007	-0.0305069
13	98.83	98.8343	98.7092	0.12509	-0.00425694
14	97.39	98.4811	98.6825	-0.20141	-1.09109
15	99.28	98.6203	98.6196	0.000673611	0.659743
16	98.78	98.5003	98.5387	-0.0384931	0.279743
17	98.75	98.4361	98.435	0.00109028	0.31391
18	98.47	98.254	98.3612	-0.107243	0.215993
19	98.47	98.1129	98.3204	-0.207493	0.357076
20	97.82	98.2636	98.3458	-0.0822431	-0.44359
21	97.79	98.2644	98.3442	-0.0797431	-0.474424
22	97.96	98.3696	98.2662	0.10334	-0.40959
23	98.21	98.5184	98.195	0.323424	-0.308424
24	98.34	98.2805	98.1175	0.163007	0.0594931
25	98.34	98.1693	98.0442	0.12509	0.170743
26	98.49	97.7998	98.0013	-0.20141	0.69016
27	98.14	97.9907	97.99	0.000673611	0.149326
28	98.05	97.9215	97.96	-0.0384931	0.128493
29	97.77	97.8986	97.8975	0.00109028	-0.12859
30	97.59	97.7069	97.8142	-0.107243	-0.116924
31	97.59	97.515	97.7225	-0.207493	0.0749931
32	97.67	97.5278	97.61	-0.0822431	0.142243
33	97.67	97.3944	97.4742	-0.0797431	0.275576
34	97.36	97.4425	97.3392	0.10334	-0.0825069
35	97.31	97.5701	97.2467	0.323424	-0.26009
36	97.24	97.3672	97.2042	0.163007	-0.127174
37	97.24	97.3068	97.1817	0.12509	-0.0667569
38	96.89	96.9865	97.1879	-0.20141	-0.0965069
39	96.48	97.214	97.2133	0.000673611	-0.734007
40	96.47	97.2223	97.2608	-0.0384931	-0.75234
41	97.13	97.3536	97.3525	0.00109028	-0.22359
42	97.21	97.3648	97.4721	-0.107243	-0.15484
43	97.43	97.3913	97.5988	-0.207493	0.0387431
44	97.98	97.6565	97.7387	-0.0822431	0.323493
45	97.97	97.8498	97.9296	-0.0797431	0.12016
46	98.2	98.2808	98.1775	0.10334	-0.0808403
47	98.67	98.7438	98.4204	0.323424	-0.0738403
48	98.75	98.7913	98.6283	0.163007	-0.0413403
49	98.77	98.9409	98.8158	0.12509	-0.170924
50	98.72	98.7965	98.9979	-0.20141	-0.0765069
51	99.23	99.2019	99.2012	0.000673611	0.0280764
52	99.67	99.3919	99.4304	-0.0384931	0.278076
53	99.76	99.6648	99.6638	0.00109028	0.0951597
54	99.57	99.7823	99.8896	-0.107243	-0.21234
55	99.57	99.9079	100.115	-0.207493	-0.337924
56	100.21	100.279	100.361	-0.0822431	-0.0690069
57	100.62	100.509	100.588	-0.0797431	0.11141
58	101.05	100.875	100.772	0.10334	0.174993
59	101.42	101.266	100.942	0.323424	0.154076
60	101.42	101.292	101.129	0.163007	0.128243
61	101.52	101.46	101.335	0.12509	0.0599097
62	101.87	101.307	101.509	-0.20141	0.56266
63	101.53	101.644	101.644	0.000673611	-0.114424
64	101.77	101.715	101.754	-0.0384931	0.0547431
65	101.76	101.828	101.827	0.00109028	-0.0681736
66	102.04	101.783	101.89	-0.107243	0.256826
67	102.05	NA	NA	-0.207493	NA
68	101.9	NA	NA	-0.0822431	NA
69	102.17	NA	NA	-0.0797431	NA
70	102.14	NA	NA	0.10334	NA
71	102.09	NA	NA	0.323424	NA
72	102.27	NA	NA	0.163007	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 <- '12'
par1 <- 'multiplicative'
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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
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