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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 24 Nov 2015 10:12:08 +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/t1448359949h3y4p0efeb2vp27.htm/, Retrieved Tue, 14 May 2024 06:34:57 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284003, Retrieved Tue, 14 May 2024 06:34:57 +0000

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122

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-       [Classical Decomposition] [] [2015-11-24 10:12:08] [a231c0efc426ce58c731cc3abc4c2d25] [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	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=284003&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=284003&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284003&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	85.74	NA	NA	-0.204507	NA
2	86.62	NA	NA	-0.11334	NA
3	86.66	NA	NA	0.39891	NA
4	87.39	NA	NA	0.669826	NA
5	87.59	NA	NA	0.237826	NA
6	88.8	NA	NA	-0.123507	NA
7	88.64	88.172	88.3146	-0.14259	0.468007
8	89.55	88.8482	88.6579	0.190243	0.70184
9	89.04	89.3484	89.0117	0.336743	-0.30841
10	88.49	89.1196	89.4275	-0.307924	-0.629576
11	89.5	89.3951	89.8729	-0.47784	0.104924
12	89.46	89.8157	90.2796	-0.46384	-0.355743
13	90.33	90.4255	90.63	-0.204507	-0.0954931
14	90.27	90.8304	90.9438	-0.11334	-0.56041
15	91.5	91.6485	91.2496	0.39891	-0.148493
16	92.53	92.2815	91.6117	0.669826	0.248507
17	93.14	92.2182	91.9804	0.237826	0.921757
18	93.01	92.2573	92.3808	-0.123507	0.752674
19	92.84	92.6895	92.8321	-0.14259	0.150507
20	92.88	93.489	93.2988	0.190243	-0.608993
21	93.05	94.1284	93.7917	0.336743	-1.07841
22	93.17	93.9733	94.2812	-0.307924	-0.803326
23	93.67	94.2647	94.7425	-0.47784	-0.59466
24	94.9	94.7128	95.1767	-0.46384	0.187174
25	95.72	95.4001	95.6046	-0.204507	0.319924
26	96.08	95.9267	96.04	-0.11334	0.15334
27	97.52	96.8939	96.495	0.39891	0.62609
28	98.26	97.6307	96.9608	0.669826	0.62934
29	98.48	97.6391	97.4012	0.237826	0.840924
30	98.09	97.6369	97.7604	-0.123507	0.45309
31	98.03	97.9237	98.0662	-0.14259	0.10634
32	98.14	98.5702	98.38	0.190243	-0.430243
33	98.71	99.0142	98.6775	0.336743	-0.304243
34	98.69	98.6375	98.9454	-0.307924	0.0525069
35	98.72	98.6617	99.1396	-0.47784	0.0582569
36	98.47	98.7924	99.2562	-0.46384	-0.32241
37	99.49	99.1655	99.37	-0.204507	0.324507
38	99.84	99.4417	99.555	-0.11334	0.39834
39	100.9	100.206	99.8075	0.39891	0.69359
40	101.31	100.721	100.052	0.669826	0.588507
41	100.09	100.468	100.23	0.237826	-0.377826
42	99.28	100.234	100.357	-0.123507	-0.953993
43	99.57	100.292	100.435	-0.14259	-0.72241
44	101.04	100.669	100.479	0.190243	0.371007
45	101.87	100.817	100.48	0.336743	1.05284
46	101.39	100.093	100.401	-0.307924	1.29667
47	100.3	99.8347	100.312	-0.47784	0.46534
48	99.95	99.8145	100.278	-0.46384	0.135507
49	99.87	100.091	100.296	-0.204507	-0.221326
50	100.51	100.165	100.278	-0.11334	0.345424
51	100.27	100.608	100.209	0.39891	-0.33766
52	100.04	100.778	100.108	0.669826	-0.73816
53	99.23	100.252	100.015	0.237826	-1.02241
54	99.32	99.8694	99.9929	-0.123507	-0.54941
55	99.95	99.8557	99.9983	-0.14259	0.0942569
56	100.23	100.167	99.9767	0.190243	0.0630903
57	101.02	100.285	99.9483	0.336743	0.734924
58	99.83	99.6496	99.9575	-0.307924	0.180424
59	99.61	99.5472	100.025	-0.47784	0.0628403
60	100.12	99.6678	100.132	-0.46384	0.452174
61	99.83	100.061	100.265	-0.204507	-0.23091
62	100.03	100.27	100.383	-0.11334	-0.239993
63	100.07	100.807	100.408	0.39891	-0.736826
64	100.46	101.091	100.422	0.669826	-0.631493
65	100.43	100.696	100.458	0.237826	-0.265743
66	100.68	100.286	100.409	-0.123507	0.39434
67	101.8	NA	NA	-0.14259	NA
68	101.21	NA	NA	0.190243	NA
69	100.63	NA	NA	0.336743	NA
70	100.55	NA	NA	-0.307924	NA
71	99.76	NA	NA	-0.47784	NA
72	98.8	NA	NA	-0.46384	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 85.74 & NA & NA & -0.204507 & NA \tabularnewline
2 & 86.62 & NA & NA & -0.11334 & NA \tabularnewline
3 & 86.66 & NA & NA & 0.39891 & NA \tabularnewline
4 & 87.39 & NA & NA & 0.669826 & NA \tabularnewline
5 & 87.59 & NA & NA & 0.237826 & NA \tabularnewline
6 & 88.8 & NA & NA & -0.123507 & NA \tabularnewline
7 & 88.64 & 88.172 & 88.3146 & -0.14259 & 0.468007 \tabularnewline
8 & 89.55 & 88.8482 & 88.6579 & 0.190243 & 0.70184 \tabularnewline
9 & 89.04 & 89.3484 & 89.0117 & 0.336743 & -0.30841 \tabularnewline
10 & 88.49 & 89.1196 & 89.4275 & -0.307924 & -0.629576 \tabularnewline
11 & 89.5 & 89.3951 & 89.8729 & -0.47784 & 0.104924 \tabularnewline
12 & 89.46 & 89.8157 & 90.2796 & -0.46384 & -0.355743 \tabularnewline
13 & 90.33 & 90.4255 & 90.63 & -0.204507 & -0.0954931 \tabularnewline
14 & 90.27 & 90.8304 & 90.9438 & -0.11334 & -0.56041 \tabularnewline
15 & 91.5 & 91.6485 & 91.2496 & 0.39891 & -0.148493 \tabularnewline
16 & 92.53 & 92.2815 & 91.6117 & 0.669826 & 0.248507 \tabularnewline
17 & 93.14 & 92.2182 & 91.9804 & 0.237826 & 0.921757 \tabularnewline
18 & 93.01 & 92.2573 & 92.3808 & -0.123507 & 0.752674 \tabularnewline
19 & 92.84 & 92.6895 & 92.8321 & -0.14259 & 0.150507 \tabularnewline
20 & 92.88 & 93.489 & 93.2988 & 0.190243 & -0.608993 \tabularnewline
21 & 93.05 & 94.1284 & 93.7917 & 0.336743 & -1.07841 \tabularnewline
22 & 93.17 & 93.9733 & 94.2812 & -0.307924 & -0.803326 \tabularnewline
23 & 93.67 & 94.2647 & 94.7425 & -0.47784 & -0.59466 \tabularnewline
24 & 94.9 & 94.7128 & 95.1767 & -0.46384 & 0.187174 \tabularnewline
25 & 95.72 & 95.4001 & 95.6046 & -0.204507 & 0.319924 \tabularnewline
26 & 96.08 & 95.9267 & 96.04 & -0.11334 & 0.15334 \tabularnewline
27 & 97.52 & 96.8939 & 96.495 & 0.39891 & 0.62609 \tabularnewline
28 & 98.26 & 97.6307 & 96.9608 & 0.669826 & 0.62934 \tabularnewline
29 & 98.48 & 97.6391 & 97.4012 & 0.237826 & 0.840924 \tabularnewline
30 & 98.09 & 97.6369 & 97.7604 & -0.123507 & 0.45309 \tabularnewline
31 & 98.03 & 97.9237 & 98.0662 & -0.14259 & 0.10634 \tabularnewline
32 & 98.14 & 98.5702 & 98.38 & 0.190243 & -0.430243 \tabularnewline
33 & 98.71 & 99.0142 & 98.6775 & 0.336743 & -0.304243 \tabularnewline
34 & 98.69 & 98.6375 & 98.9454 & -0.307924 & 0.0525069 \tabularnewline
35 & 98.72 & 98.6617 & 99.1396 & -0.47784 & 0.0582569 \tabularnewline
36 & 98.47 & 98.7924 & 99.2562 & -0.46384 & -0.32241 \tabularnewline
37 & 99.49 & 99.1655 & 99.37 & -0.204507 & 0.324507 \tabularnewline
38 & 99.84 & 99.4417 & 99.555 & -0.11334 & 0.39834 \tabularnewline
39 & 100.9 & 100.206 & 99.8075 & 0.39891 & 0.69359 \tabularnewline
40 & 101.31 & 100.721 & 100.052 & 0.669826 & 0.588507 \tabularnewline
41 & 100.09 & 100.468 & 100.23 & 0.237826 & -0.377826 \tabularnewline
42 & 99.28 & 100.234 & 100.357 & -0.123507 & -0.953993 \tabularnewline
43 & 99.57 & 100.292 & 100.435 & -0.14259 & -0.72241 \tabularnewline
44 & 101.04 & 100.669 & 100.479 & 0.190243 & 0.371007 \tabularnewline
45 & 101.87 & 100.817 & 100.48 & 0.336743 & 1.05284 \tabularnewline
46 & 101.39 & 100.093 & 100.401 & -0.307924 & 1.29667 \tabularnewline
47 & 100.3 & 99.8347 & 100.312 & -0.47784 & 0.46534 \tabularnewline
48 & 99.95 & 99.8145 & 100.278 & -0.46384 & 0.135507 \tabularnewline
49 & 99.87 & 100.091 & 100.296 & -0.204507 & -0.221326 \tabularnewline
50 & 100.51 & 100.165 & 100.278 & -0.11334 & 0.345424 \tabularnewline
51 & 100.27 & 100.608 & 100.209 & 0.39891 & -0.33766 \tabularnewline
52 & 100.04 & 100.778 & 100.108 & 0.669826 & -0.73816 \tabularnewline
53 & 99.23 & 100.252 & 100.015 & 0.237826 & -1.02241 \tabularnewline
54 & 99.32 & 99.8694 & 99.9929 & -0.123507 & -0.54941 \tabularnewline
55 & 99.95 & 99.8557 & 99.9983 & -0.14259 & 0.0942569 \tabularnewline
56 & 100.23 & 100.167 & 99.9767 & 0.190243 & 0.0630903 \tabularnewline
57 & 101.02 & 100.285 & 99.9483 & 0.336743 & 0.734924 \tabularnewline
58 & 99.83 & 99.6496 & 99.9575 & -0.307924 & 0.180424 \tabularnewline
59 & 99.61 & 99.5472 & 100.025 & -0.47784 & 0.0628403 \tabularnewline
60 & 100.12 & 99.6678 & 100.132 & -0.46384 & 0.452174 \tabularnewline
61 & 99.83 & 100.061 & 100.265 & -0.204507 & -0.23091 \tabularnewline
62 & 100.03 & 100.27 & 100.383 & -0.11334 & -0.239993 \tabularnewline
63 & 100.07 & 100.807 & 100.408 & 0.39891 & -0.736826 \tabularnewline
64 & 100.46 & 101.091 & 100.422 & 0.669826 & -0.631493 \tabularnewline
65 & 100.43 & 100.696 & 100.458 & 0.237826 & -0.265743 \tabularnewline
66 & 100.68 & 100.286 & 100.409 & -0.123507 & 0.39434 \tabularnewline
67 & 101.8 & NA & NA & -0.14259 & NA \tabularnewline
68 & 101.21 & NA & NA & 0.190243 & NA \tabularnewline
69 & 100.63 & NA & NA & 0.336743 & NA \tabularnewline
70 & 100.55 & NA & NA & -0.307924 & NA \tabularnewline
71 & 99.76 & NA & NA & -0.47784 & NA \tabularnewline
72 & 98.8 & NA & NA & -0.46384 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284003&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]85.74[/C][C]NA[/C][C]NA[/C][C]-0.204507[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]86.62[/C][C]NA[/C][C]NA[/C][C]-0.11334[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]86.66[/C][C]NA[/C][C]NA[/C][C]0.39891[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]87.39[/C][C]NA[/C][C]NA[/C][C]0.669826[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]87.59[/C][C]NA[/C][C]NA[/C][C]0.237826[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]88.8[/C][C]NA[/C][C]NA[/C][C]-0.123507[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]88.64[/C][C]88.172[/C][C]88.3146[/C][C]-0.14259[/C][C]0.468007[/C][/ROW]
[ROW][C]8[/C][C]89.55[/C][C]88.8482[/C][C]88.6579[/C][C]0.190243[/C][C]0.70184[/C][/ROW]
[ROW][C]9[/C][C]89.04[/C][C]89.3484[/C][C]89.0117[/C][C]0.336743[/C][C]-0.30841[/C][/ROW]
[ROW][C]10[/C][C]88.49[/C][C]89.1196[/C][C]89.4275[/C][C]-0.307924[/C][C]-0.629576[/C][/ROW]
[ROW][C]11[/C][C]89.5[/C][C]89.3951[/C][C]89.8729[/C][C]-0.47784[/C][C]0.104924[/C][/ROW]
[ROW][C]12[/C][C]89.46[/C][C]89.8157[/C][C]90.2796[/C][C]-0.46384[/C][C]-0.355743[/C][/ROW]
[ROW][C]13[/C][C]90.33[/C][C]90.4255[/C][C]90.63[/C][C]-0.204507[/C][C]-0.0954931[/C][/ROW]
[ROW][C]14[/C][C]90.27[/C][C]90.8304[/C][C]90.9438[/C][C]-0.11334[/C][C]-0.56041[/C][/ROW]
[ROW][C]15[/C][C]91.5[/C][C]91.6485[/C][C]91.2496[/C][C]0.39891[/C][C]-0.148493[/C][/ROW]
[ROW][C]16[/C][C]92.53[/C][C]92.2815[/C][C]91.6117[/C][C]0.669826[/C][C]0.248507[/C][/ROW]
[ROW][C]17[/C][C]93.14[/C][C]92.2182[/C][C]91.9804[/C][C]0.237826[/C][C]0.921757[/C][/ROW]
[ROW][C]18[/C][C]93.01[/C][C]92.2573[/C][C]92.3808[/C][C]-0.123507[/C][C]0.752674[/C][/ROW]
[ROW][C]19[/C][C]92.84[/C][C]92.6895[/C][C]92.8321[/C][C]-0.14259[/C][C]0.150507[/C][/ROW]
[ROW][C]20[/C][C]92.88[/C][C]93.489[/C][C]93.2988[/C][C]0.190243[/C][C]-0.608993[/C][/ROW]
[ROW][C]21[/C][C]93.05[/C][C]94.1284[/C][C]93.7917[/C][C]0.336743[/C][C]-1.07841[/C][/ROW]
[ROW][C]22[/C][C]93.17[/C][C]93.9733[/C][C]94.2812[/C][C]-0.307924[/C][C]-0.803326[/C][/ROW]
[ROW][C]23[/C][C]93.67[/C][C]94.2647[/C][C]94.7425[/C][C]-0.47784[/C][C]-0.59466[/C][/ROW]
[ROW][C]24[/C][C]94.9[/C][C]94.7128[/C][C]95.1767[/C][C]-0.46384[/C][C]0.187174[/C][/ROW]
[ROW][C]25[/C][C]95.72[/C][C]95.4001[/C][C]95.6046[/C][C]-0.204507[/C][C]0.319924[/C][/ROW]
[ROW][C]26[/C][C]96.08[/C][C]95.9267[/C][C]96.04[/C][C]-0.11334[/C][C]0.15334[/C][/ROW]
[ROW][C]27[/C][C]97.52[/C][C]96.8939[/C][C]96.495[/C][C]0.39891[/C][C]0.62609[/C][/ROW]
[ROW][C]28[/C][C]98.26[/C][C]97.6307[/C][C]96.9608[/C][C]0.669826[/C][C]0.62934[/C][/ROW]
[ROW][C]29[/C][C]98.48[/C][C]97.6391[/C][C]97.4012[/C][C]0.237826[/C][C]0.840924[/C][/ROW]
[ROW][C]30[/C][C]98.09[/C][C]97.6369[/C][C]97.7604[/C][C]-0.123507[/C][C]0.45309[/C][/ROW]
[ROW][C]31[/C][C]98.03[/C][C]97.9237[/C][C]98.0662[/C][C]-0.14259[/C][C]0.10634[/C][/ROW]
[ROW][C]32[/C][C]98.14[/C][C]98.5702[/C][C]98.38[/C][C]0.190243[/C][C]-0.430243[/C][/ROW]
[ROW][C]33[/C][C]98.71[/C][C]99.0142[/C][C]98.6775[/C][C]0.336743[/C][C]-0.304243[/C][/ROW]
[ROW][C]34[/C][C]98.69[/C][C]98.6375[/C][C]98.9454[/C][C]-0.307924[/C][C]0.0525069[/C][/ROW]
[ROW][C]35[/C][C]98.72[/C][C]98.6617[/C][C]99.1396[/C][C]-0.47784[/C][C]0.0582569[/C][/ROW]
[ROW][C]36[/C][C]98.47[/C][C]98.7924[/C][C]99.2562[/C][C]-0.46384[/C][C]-0.32241[/C][/ROW]
[ROW][C]37[/C][C]99.49[/C][C]99.1655[/C][C]99.37[/C][C]-0.204507[/C][C]0.324507[/C][/ROW]
[ROW][C]38[/C][C]99.84[/C][C]99.4417[/C][C]99.555[/C][C]-0.11334[/C][C]0.39834[/C][/ROW]
[ROW][C]39[/C][C]100.9[/C][C]100.206[/C][C]99.8075[/C][C]0.39891[/C][C]0.69359[/C][/ROW]
[ROW][C]40[/C][C]101.31[/C][C]100.721[/C][C]100.052[/C][C]0.669826[/C][C]0.588507[/C][/ROW]
[ROW][C]41[/C][C]100.09[/C][C]100.468[/C][C]100.23[/C][C]0.237826[/C][C]-0.377826[/C][/ROW]
[ROW][C]42[/C][C]99.28[/C][C]100.234[/C][C]100.357[/C][C]-0.123507[/C][C]-0.953993[/C][/ROW]
[ROW][C]43[/C][C]99.57[/C][C]100.292[/C][C]100.435[/C][C]-0.14259[/C][C]-0.72241[/C][/ROW]
[ROW][C]44[/C][C]101.04[/C][C]100.669[/C][C]100.479[/C][C]0.190243[/C][C]0.371007[/C][/ROW]
[ROW][C]45[/C][C]101.87[/C][C]100.817[/C][C]100.48[/C][C]0.336743[/C][C]1.05284[/C][/ROW]
[ROW][C]46[/C][C]101.39[/C][C]100.093[/C][C]100.401[/C][C]-0.307924[/C][C]1.29667[/C][/ROW]
[ROW][C]47[/C][C]100.3[/C][C]99.8347[/C][C]100.312[/C][C]-0.47784[/C][C]0.46534[/C][/ROW]
[ROW][C]48[/C][C]99.95[/C][C]99.8145[/C][C]100.278[/C][C]-0.46384[/C][C]0.135507[/C][/ROW]
[ROW][C]49[/C][C]99.87[/C][C]100.091[/C][C]100.296[/C][C]-0.204507[/C][C]-0.221326[/C][/ROW]
[ROW][C]50[/C][C]100.51[/C][C]100.165[/C][C]100.278[/C][C]-0.11334[/C][C]0.345424[/C][/ROW]
[ROW][C]51[/C][C]100.27[/C][C]100.608[/C][C]100.209[/C][C]0.39891[/C][C]-0.33766[/C][/ROW]
[ROW][C]52[/C][C]100.04[/C][C]100.778[/C][C]100.108[/C][C]0.669826[/C][C]-0.73816[/C][/ROW]
[ROW][C]53[/C][C]99.23[/C][C]100.252[/C][C]100.015[/C][C]0.237826[/C][C]-1.02241[/C][/ROW]
[ROW][C]54[/C][C]99.32[/C][C]99.8694[/C][C]99.9929[/C][C]-0.123507[/C][C]-0.54941[/C][/ROW]
[ROW][C]55[/C][C]99.95[/C][C]99.8557[/C][C]99.9983[/C][C]-0.14259[/C][C]0.0942569[/C][/ROW]
[ROW][C]56[/C][C]100.23[/C][C]100.167[/C][C]99.9767[/C][C]0.190243[/C][C]0.0630903[/C][/ROW]
[ROW][C]57[/C][C]101.02[/C][C]100.285[/C][C]99.9483[/C][C]0.336743[/C][C]0.734924[/C][/ROW]
[ROW][C]58[/C][C]99.83[/C][C]99.6496[/C][C]99.9575[/C][C]-0.307924[/C][C]0.180424[/C][/ROW]
[ROW][C]59[/C][C]99.61[/C][C]99.5472[/C][C]100.025[/C][C]-0.47784[/C][C]0.0628403[/C][/ROW]
[ROW][C]60[/C][C]100.12[/C][C]99.6678[/C][C]100.132[/C][C]-0.46384[/C][C]0.452174[/C][/ROW]
[ROW][C]61[/C][C]99.83[/C][C]100.061[/C][C]100.265[/C][C]-0.204507[/C][C]-0.23091[/C][/ROW]
[ROW][C]62[/C][C]100.03[/C][C]100.27[/C][C]100.383[/C][C]-0.11334[/C][C]-0.239993[/C][/ROW]
[ROW][C]63[/C][C]100.07[/C][C]100.807[/C][C]100.408[/C][C]0.39891[/C][C]-0.736826[/C][/ROW]
[ROW][C]64[/C][C]100.46[/C][C]101.091[/C][C]100.422[/C][C]0.669826[/C][C]-0.631493[/C][/ROW]
[ROW][C]65[/C][C]100.43[/C][C]100.696[/C][C]100.458[/C][C]0.237826[/C][C]-0.265743[/C][/ROW]
[ROW][C]66[/C][C]100.68[/C][C]100.286[/C][C]100.409[/C][C]-0.123507[/C][C]0.39434[/C][/ROW]
[ROW][C]67[/C][C]101.8[/C][C]NA[/C][C]NA[/C][C]-0.14259[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.21[/C][C]NA[/C][C]NA[/C][C]0.190243[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]100.63[/C][C]NA[/C][C]NA[/C][C]0.336743[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]100.55[/C][C]NA[/C][C]NA[/C][C]-0.307924[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]99.76[/C][C]NA[/C][C]NA[/C][C]-0.47784[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]98.8[/C][C]NA[/C][C]NA[/C][C]-0.46384[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284003&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284003&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	85.74	NA	NA	-0.204507	NA
2	86.62	NA	NA	-0.11334	NA
3	86.66	NA	NA	0.39891	NA
4	87.39	NA	NA	0.669826	NA
5	87.59	NA	NA	0.237826	NA
6	88.8	NA	NA	-0.123507	NA
7	88.64	88.172	88.3146	-0.14259	0.468007
8	89.55	88.8482	88.6579	0.190243	0.70184
9	89.04	89.3484	89.0117	0.336743	-0.30841
10	88.49	89.1196	89.4275	-0.307924	-0.629576
11	89.5	89.3951	89.8729	-0.47784	0.104924
12	89.46	89.8157	90.2796	-0.46384	-0.355743
13	90.33	90.4255	90.63	-0.204507	-0.0954931
14	90.27	90.8304	90.9438	-0.11334	-0.56041
15	91.5	91.6485	91.2496	0.39891	-0.148493
16	92.53	92.2815	91.6117	0.669826	0.248507
17	93.14	92.2182	91.9804	0.237826	0.921757
18	93.01	92.2573	92.3808	-0.123507	0.752674
19	92.84	92.6895	92.8321	-0.14259	0.150507
20	92.88	93.489	93.2988	0.190243	-0.608993
21	93.05	94.1284	93.7917	0.336743	-1.07841
22	93.17	93.9733	94.2812	-0.307924	-0.803326
23	93.67	94.2647	94.7425	-0.47784	-0.59466
24	94.9	94.7128	95.1767	-0.46384	0.187174
25	95.72	95.4001	95.6046	-0.204507	0.319924
26	96.08	95.9267	96.04	-0.11334	0.15334
27	97.52	96.8939	96.495	0.39891	0.62609
28	98.26	97.6307	96.9608	0.669826	0.62934
29	98.48	97.6391	97.4012	0.237826	0.840924
30	98.09	97.6369	97.7604	-0.123507	0.45309
31	98.03	97.9237	98.0662	-0.14259	0.10634
32	98.14	98.5702	98.38	0.190243	-0.430243
33	98.71	99.0142	98.6775	0.336743	-0.304243
34	98.69	98.6375	98.9454	-0.307924	0.0525069
35	98.72	98.6617	99.1396	-0.47784	0.0582569
36	98.47	98.7924	99.2562	-0.46384	-0.32241
37	99.49	99.1655	99.37	-0.204507	0.324507
38	99.84	99.4417	99.555	-0.11334	0.39834
39	100.9	100.206	99.8075	0.39891	0.69359
40	101.31	100.721	100.052	0.669826	0.588507
41	100.09	100.468	100.23	0.237826	-0.377826
42	99.28	100.234	100.357	-0.123507	-0.953993
43	99.57	100.292	100.435	-0.14259	-0.72241
44	101.04	100.669	100.479	0.190243	0.371007
45	101.87	100.817	100.48	0.336743	1.05284
46	101.39	100.093	100.401	-0.307924	1.29667
47	100.3	99.8347	100.312	-0.47784	0.46534
48	99.95	99.8145	100.278	-0.46384	0.135507
49	99.87	100.091	100.296	-0.204507	-0.221326
50	100.51	100.165	100.278	-0.11334	0.345424
51	100.27	100.608	100.209	0.39891	-0.33766
52	100.04	100.778	100.108	0.669826	-0.73816
53	99.23	100.252	100.015	0.237826	-1.02241
54	99.32	99.8694	99.9929	-0.123507	-0.54941
55	99.95	99.8557	99.9983	-0.14259	0.0942569
56	100.23	100.167	99.9767	0.190243	0.0630903
57	101.02	100.285	99.9483	0.336743	0.734924
58	99.83	99.6496	99.9575	-0.307924	0.180424
59	99.61	99.5472	100.025	-0.47784	0.0628403
60	100.12	99.6678	100.132	-0.46384	0.452174
61	99.83	100.061	100.265	-0.204507	-0.23091
62	100.03	100.27	100.383	-0.11334	-0.239993
63	100.07	100.807	100.408	0.39891	-0.736826
64	100.46	101.091	100.422	0.669826	-0.631493
65	100.43	100.696	100.458	0.237826	-0.265743
66	100.68	100.286	100.409	-0.123507	0.39434
67	101.8	NA	NA	-0.14259	NA
68	101.21	NA	NA	0.190243	NA
69	100.63	NA	NA	0.336743	NA
70	100.55	NA	NA	-0.307924	NA
71	99.76	NA	NA	-0.47784	NA
72	98.8	NA	NA	-0.46384	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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