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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 28 Nov 2014 08:39:53 +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/2014/Nov/28/t14171640698zznlxlfafc96bs.htm/, Retrieved Sun, 19 May 2024 15:20:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=260791, Retrieved Sun, 19 May 2024 15:20:34 +0000

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105

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-       [Classical Decomposition] [] [2014-11-28 08:39:53] [dea8d4b5c2c472598207c5e5950771f6] [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	'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=260791&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=260791&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260791&T=0

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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	1.5	NA	NA	-0.048259	NA
2	1.439	NA	NA	-0.0199174	NA
3	1.49	NA	NA	0.0156743	NA
4	1.502	NA	NA	0.0388243	NA
5	1.531	NA	NA	0.024866	NA
6	1.611	NA	NA	0.0221326	NA
7	1.644	1.4966	1.47296	0.023641	0.147401
8	1.559	1.4812	1.45242	0.0287826	0.0778007
9	1.553	1.46314	1.43658	0.0265576	0.089859
10	1.494	1.41466	1.41967	-0.00500903	0.0793424
11	1.298	1.35625	1.40262	-0.0463757	-0.0582493
12	1.215	1.32467	1.38558	-0.0609174	-0.109666
13	1.179	1.31807	1.36633	-0.048259	-0.139074
14	1.267	1.32987	1.34979	-0.0199174	-0.0628743
15	1.282	1.3533	1.33763	0.0156743	-0.0712993
16	1.304	1.36399	1.32517	0.0388243	-0.059991
17	1.32	1.34907	1.32421	0.024866	-0.0290743
18	1.413	1.35917	1.33704	0.0221326	0.0538257
19	1.38	1.37952	1.35588	0.023641	0.000484028
20	1.426	1.40312	1.37433	0.0287826	0.022884
21	1.394	1.4171	1.39054	0.0265576	-0.0230993
22	1.354	1.40357	1.40858	-0.00500903	-0.0495743
23	1.415	1.38112	1.4275	-0.0463757	0.0338757
24	1.406	1.38046	1.44138	-0.0609174	0.0255424
25	1.44	1.40278	1.45104	-0.048259	0.0372174
26	1.449	1.43946	1.45938	-0.0199174	0.00954236
27	1.489	1.48197	1.46629	0.0156743	0.00703403
28	1.53	1.51453	1.47571	0.0388243	0.0154674
29	1.548	1.50928	1.48442	0.024866	0.0387174
30	1.518	1.51613	1.494	0.0221326	0.00186736
31	1.507	1.53018	1.50654	0.023641	-0.0231826
32	1.499	1.54707	1.51829	0.0287826	-0.0480743
33	1.487	1.55706	1.5305	0.0265576	-0.0700576
34	1.487	1.53774	1.54275	-0.00500903	-0.050741
35	1.491	1.50833	1.55471	-0.0463757	-0.0173326
36	1.56	1.50646	1.56738	-0.0609174	0.0535424
37	1.587	1.53028	1.57854	-0.048259	0.0567174
38	1.584	1.5705	1.59042	-0.0199174	0.0135007
39	1.647	1.62051	1.60483	0.0156743	0.0264924
40	1.666	1.6567	1.61788	0.0388243	0.00930069
41	1.699	1.65387	1.629	0.024866	0.045134
42	1.671	1.65851	1.63638	0.0221326	0.0124924
43	1.622	1.66547	1.64183	0.023641	-0.0434743
44	1.669	1.67891	1.65013	0.0287826	-0.00990764
45	1.663	1.68581	1.65925	0.0265576	-0.0228076
46	1.624	1.66503	1.67004	-0.00500903	-0.0410326
47	1.621	1.63308	1.67946	-0.0463757	-0.0120826
48	1.607	1.62412	1.68504	-0.0609174	-0.0171243
49	1.671	1.64278	1.69104	-0.048259	0.0282174
50	1.699	1.67796	1.69788	-0.0199174	0.0210424
51	1.751	1.72367	1.708	0.0156743	0.0273257
52	1.821	1.76195	1.72312	0.0388243	0.0590507
53	1.77	1.76278	1.73792	0.024866	0.00721736
54	1.734	1.77234	1.75021	0.0221326	-0.038341
55	1.703	1.78239	1.75875	0.023641	-0.079391
56	1.752	1.79287	1.76408	0.0287826	-0.040866
57	1.823	1.79506	1.7685	0.0265576	0.0279424
58	1.827	1.76316	1.76817	-0.00500903	0.0638424
59	1.773	1.71737	1.76375	-0.0463757	0.0556257
60	1.75	1.70046	1.76138	-0.0609174	0.0495424
61	1.733	1.71424	1.7625	-0.048259	0.018759
62	1.765	1.74437	1.76429	-0.0199174	0.0206257
63	1.791	1.77872	1.76304	0.0156743	0.012284
64	1.773	1.79499	1.75617	0.0388243	-0.021991
65	1.712	1.77216	1.74729	0.024866	-0.0601576
66	1.735	1.76301	1.74088	0.0221326	-0.0280076
67	1.729	NA	NA	0.023641	NA
68	1.769	NA	NA	0.0287826	NA
69	1.776	NA	NA	0.0265576	NA
70	1.709	NA	NA	-0.00500903	NA
71	1.678	NA	NA	-0.0463757	NA
72	1.691	NA	NA	-0.0609174	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.5 & NA & NA & -0.048259 & NA \tabularnewline
2 & 1.439 & NA & NA & -0.0199174 & NA \tabularnewline
3 & 1.49 & NA & NA & 0.0156743 & NA \tabularnewline
4 & 1.502 & NA & NA & 0.0388243 & NA \tabularnewline
5 & 1.531 & NA & NA & 0.024866 & NA \tabularnewline
6 & 1.611 & NA & NA & 0.0221326 & NA \tabularnewline
7 & 1.644 & 1.4966 & 1.47296 & 0.023641 & 0.147401 \tabularnewline
8 & 1.559 & 1.4812 & 1.45242 & 0.0287826 & 0.0778007 \tabularnewline
9 & 1.553 & 1.46314 & 1.43658 & 0.0265576 & 0.089859 \tabularnewline
10 & 1.494 & 1.41466 & 1.41967 & -0.00500903 & 0.0793424 \tabularnewline
11 & 1.298 & 1.35625 & 1.40262 & -0.0463757 & -0.0582493 \tabularnewline
12 & 1.215 & 1.32467 & 1.38558 & -0.0609174 & -0.109666 \tabularnewline
13 & 1.179 & 1.31807 & 1.36633 & -0.048259 & -0.139074 \tabularnewline
14 & 1.267 & 1.32987 & 1.34979 & -0.0199174 & -0.0628743 \tabularnewline
15 & 1.282 & 1.3533 & 1.33763 & 0.0156743 & -0.0712993 \tabularnewline
16 & 1.304 & 1.36399 & 1.32517 & 0.0388243 & -0.059991 \tabularnewline
17 & 1.32 & 1.34907 & 1.32421 & 0.024866 & -0.0290743 \tabularnewline
18 & 1.413 & 1.35917 & 1.33704 & 0.0221326 & 0.0538257 \tabularnewline
19 & 1.38 & 1.37952 & 1.35588 & 0.023641 & 0.000484028 \tabularnewline
20 & 1.426 & 1.40312 & 1.37433 & 0.0287826 & 0.022884 \tabularnewline
21 & 1.394 & 1.4171 & 1.39054 & 0.0265576 & -0.0230993 \tabularnewline
22 & 1.354 & 1.40357 & 1.40858 & -0.00500903 & -0.0495743 \tabularnewline
23 & 1.415 & 1.38112 & 1.4275 & -0.0463757 & 0.0338757 \tabularnewline
24 & 1.406 & 1.38046 & 1.44138 & -0.0609174 & 0.0255424 \tabularnewline
25 & 1.44 & 1.40278 & 1.45104 & -0.048259 & 0.0372174 \tabularnewline
26 & 1.449 & 1.43946 & 1.45938 & -0.0199174 & 0.00954236 \tabularnewline
27 & 1.489 & 1.48197 & 1.46629 & 0.0156743 & 0.00703403 \tabularnewline
28 & 1.53 & 1.51453 & 1.47571 & 0.0388243 & 0.0154674 \tabularnewline
29 & 1.548 & 1.50928 & 1.48442 & 0.024866 & 0.0387174 \tabularnewline
30 & 1.518 & 1.51613 & 1.494 & 0.0221326 & 0.00186736 \tabularnewline
31 & 1.507 & 1.53018 & 1.50654 & 0.023641 & -0.0231826 \tabularnewline
32 & 1.499 & 1.54707 & 1.51829 & 0.0287826 & -0.0480743 \tabularnewline
33 & 1.487 & 1.55706 & 1.5305 & 0.0265576 & -0.0700576 \tabularnewline
34 & 1.487 & 1.53774 & 1.54275 & -0.00500903 & -0.050741 \tabularnewline
35 & 1.491 & 1.50833 & 1.55471 & -0.0463757 & -0.0173326 \tabularnewline
36 & 1.56 & 1.50646 & 1.56738 & -0.0609174 & 0.0535424 \tabularnewline
37 & 1.587 & 1.53028 & 1.57854 & -0.048259 & 0.0567174 \tabularnewline
38 & 1.584 & 1.5705 & 1.59042 & -0.0199174 & 0.0135007 \tabularnewline
39 & 1.647 & 1.62051 & 1.60483 & 0.0156743 & 0.0264924 \tabularnewline
40 & 1.666 & 1.6567 & 1.61788 & 0.0388243 & 0.00930069 \tabularnewline
41 & 1.699 & 1.65387 & 1.629 & 0.024866 & 0.045134 \tabularnewline
42 & 1.671 & 1.65851 & 1.63638 & 0.0221326 & 0.0124924 \tabularnewline
43 & 1.622 & 1.66547 & 1.64183 & 0.023641 & -0.0434743 \tabularnewline
44 & 1.669 & 1.67891 & 1.65013 & 0.0287826 & -0.00990764 \tabularnewline
45 & 1.663 & 1.68581 & 1.65925 & 0.0265576 & -0.0228076 \tabularnewline
46 & 1.624 & 1.66503 & 1.67004 & -0.00500903 & -0.0410326 \tabularnewline
47 & 1.621 & 1.63308 & 1.67946 & -0.0463757 & -0.0120826 \tabularnewline
48 & 1.607 & 1.62412 & 1.68504 & -0.0609174 & -0.0171243 \tabularnewline
49 & 1.671 & 1.64278 & 1.69104 & -0.048259 & 0.0282174 \tabularnewline
50 & 1.699 & 1.67796 & 1.69788 & -0.0199174 & 0.0210424 \tabularnewline
51 & 1.751 & 1.72367 & 1.708 & 0.0156743 & 0.0273257 \tabularnewline
52 & 1.821 & 1.76195 & 1.72312 & 0.0388243 & 0.0590507 \tabularnewline
53 & 1.77 & 1.76278 & 1.73792 & 0.024866 & 0.00721736 \tabularnewline
54 & 1.734 & 1.77234 & 1.75021 & 0.0221326 & -0.038341 \tabularnewline
55 & 1.703 & 1.78239 & 1.75875 & 0.023641 & -0.079391 \tabularnewline
56 & 1.752 & 1.79287 & 1.76408 & 0.0287826 & -0.040866 \tabularnewline
57 & 1.823 & 1.79506 & 1.7685 & 0.0265576 & 0.0279424 \tabularnewline
58 & 1.827 & 1.76316 & 1.76817 & -0.00500903 & 0.0638424 \tabularnewline
59 & 1.773 & 1.71737 & 1.76375 & -0.0463757 & 0.0556257 \tabularnewline
60 & 1.75 & 1.70046 & 1.76138 & -0.0609174 & 0.0495424 \tabularnewline
61 & 1.733 & 1.71424 & 1.7625 & -0.048259 & 0.018759 \tabularnewline
62 & 1.765 & 1.74437 & 1.76429 & -0.0199174 & 0.0206257 \tabularnewline
63 & 1.791 & 1.77872 & 1.76304 & 0.0156743 & 0.012284 \tabularnewline
64 & 1.773 & 1.79499 & 1.75617 & 0.0388243 & -0.021991 \tabularnewline
65 & 1.712 & 1.77216 & 1.74729 & 0.024866 & -0.0601576 \tabularnewline
66 & 1.735 & 1.76301 & 1.74088 & 0.0221326 & -0.0280076 \tabularnewline
67 & 1.729 & NA & NA & 0.023641 & NA \tabularnewline
68 & 1.769 & NA & NA & 0.0287826 & NA \tabularnewline
69 & 1.776 & NA & NA & 0.0265576 & NA \tabularnewline
70 & 1.709 & NA & NA & -0.00500903 & NA \tabularnewline
71 & 1.678 & NA & NA & -0.0463757 & NA \tabularnewline
72 & 1.691 & NA & NA & -0.0609174 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260791&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]1.5[/C][C]NA[/C][C]NA[/C][C]-0.048259[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.439[/C][C]NA[/C][C]NA[/C][C]-0.0199174[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.49[/C][C]NA[/C][C]NA[/C][C]0.0156743[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.502[/C][C]NA[/C][C]NA[/C][C]0.0388243[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.531[/C][C]NA[/C][C]NA[/C][C]0.024866[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.611[/C][C]NA[/C][C]NA[/C][C]0.0221326[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.644[/C][C]1.4966[/C][C]1.47296[/C][C]0.023641[/C][C]0.147401[/C][/ROW]
[ROW][C]8[/C][C]1.559[/C][C]1.4812[/C][C]1.45242[/C][C]0.0287826[/C][C]0.0778007[/C][/ROW]
[ROW][C]9[/C][C]1.553[/C][C]1.46314[/C][C]1.43658[/C][C]0.0265576[/C][C]0.089859[/C][/ROW]
[ROW][C]10[/C][C]1.494[/C][C]1.41466[/C][C]1.41967[/C][C]-0.00500903[/C][C]0.0793424[/C][/ROW]
[ROW][C]11[/C][C]1.298[/C][C]1.35625[/C][C]1.40262[/C][C]-0.0463757[/C][C]-0.0582493[/C][/ROW]
[ROW][C]12[/C][C]1.215[/C][C]1.32467[/C][C]1.38558[/C][C]-0.0609174[/C][C]-0.109666[/C][/ROW]
[ROW][C]13[/C][C]1.179[/C][C]1.31807[/C][C]1.36633[/C][C]-0.048259[/C][C]-0.139074[/C][/ROW]
[ROW][C]14[/C][C]1.267[/C][C]1.32987[/C][C]1.34979[/C][C]-0.0199174[/C][C]-0.0628743[/C][/ROW]
[ROW][C]15[/C][C]1.282[/C][C]1.3533[/C][C]1.33763[/C][C]0.0156743[/C][C]-0.0712993[/C][/ROW]
[ROW][C]16[/C][C]1.304[/C][C]1.36399[/C][C]1.32517[/C][C]0.0388243[/C][C]-0.059991[/C][/ROW]
[ROW][C]17[/C][C]1.32[/C][C]1.34907[/C][C]1.32421[/C][C]0.024866[/C][C]-0.0290743[/C][/ROW]
[ROW][C]18[/C][C]1.413[/C][C]1.35917[/C][C]1.33704[/C][C]0.0221326[/C][C]0.0538257[/C][/ROW]
[ROW][C]19[/C][C]1.38[/C][C]1.37952[/C][C]1.35588[/C][C]0.023641[/C][C]0.000484028[/C][/ROW]
[ROW][C]20[/C][C]1.426[/C][C]1.40312[/C][C]1.37433[/C][C]0.0287826[/C][C]0.022884[/C][/ROW]
[ROW][C]21[/C][C]1.394[/C][C]1.4171[/C][C]1.39054[/C][C]0.0265576[/C][C]-0.0230993[/C][/ROW]
[ROW][C]22[/C][C]1.354[/C][C]1.40357[/C][C]1.40858[/C][C]-0.00500903[/C][C]-0.0495743[/C][/ROW]
[ROW][C]23[/C][C]1.415[/C][C]1.38112[/C][C]1.4275[/C][C]-0.0463757[/C][C]0.0338757[/C][/ROW]
[ROW][C]24[/C][C]1.406[/C][C]1.38046[/C][C]1.44138[/C][C]-0.0609174[/C][C]0.0255424[/C][/ROW]
[ROW][C]25[/C][C]1.44[/C][C]1.40278[/C][C]1.45104[/C][C]-0.048259[/C][C]0.0372174[/C][/ROW]
[ROW][C]26[/C][C]1.449[/C][C]1.43946[/C][C]1.45938[/C][C]-0.0199174[/C][C]0.00954236[/C][/ROW]
[ROW][C]27[/C][C]1.489[/C][C]1.48197[/C][C]1.46629[/C][C]0.0156743[/C][C]0.00703403[/C][/ROW]
[ROW][C]28[/C][C]1.53[/C][C]1.51453[/C][C]1.47571[/C][C]0.0388243[/C][C]0.0154674[/C][/ROW]
[ROW][C]29[/C][C]1.548[/C][C]1.50928[/C][C]1.48442[/C][C]0.024866[/C][C]0.0387174[/C][/ROW]
[ROW][C]30[/C][C]1.518[/C][C]1.51613[/C][C]1.494[/C][C]0.0221326[/C][C]0.00186736[/C][/ROW]
[ROW][C]31[/C][C]1.507[/C][C]1.53018[/C][C]1.50654[/C][C]0.023641[/C][C]-0.0231826[/C][/ROW]
[ROW][C]32[/C][C]1.499[/C][C]1.54707[/C][C]1.51829[/C][C]0.0287826[/C][C]-0.0480743[/C][/ROW]
[ROW][C]33[/C][C]1.487[/C][C]1.55706[/C][C]1.5305[/C][C]0.0265576[/C][C]-0.0700576[/C][/ROW]
[ROW][C]34[/C][C]1.487[/C][C]1.53774[/C][C]1.54275[/C][C]-0.00500903[/C][C]-0.050741[/C][/ROW]
[ROW][C]35[/C][C]1.491[/C][C]1.50833[/C][C]1.55471[/C][C]-0.0463757[/C][C]-0.0173326[/C][/ROW]
[ROW][C]36[/C][C]1.56[/C][C]1.50646[/C][C]1.56738[/C][C]-0.0609174[/C][C]0.0535424[/C][/ROW]
[ROW][C]37[/C][C]1.587[/C][C]1.53028[/C][C]1.57854[/C][C]-0.048259[/C][C]0.0567174[/C][/ROW]
[ROW][C]38[/C][C]1.584[/C][C]1.5705[/C][C]1.59042[/C][C]-0.0199174[/C][C]0.0135007[/C][/ROW]
[ROW][C]39[/C][C]1.647[/C][C]1.62051[/C][C]1.60483[/C][C]0.0156743[/C][C]0.0264924[/C][/ROW]
[ROW][C]40[/C][C]1.666[/C][C]1.6567[/C][C]1.61788[/C][C]0.0388243[/C][C]0.00930069[/C][/ROW]
[ROW][C]41[/C][C]1.699[/C][C]1.65387[/C][C]1.629[/C][C]0.024866[/C][C]0.045134[/C][/ROW]
[ROW][C]42[/C][C]1.671[/C][C]1.65851[/C][C]1.63638[/C][C]0.0221326[/C][C]0.0124924[/C][/ROW]
[ROW][C]43[/C][C]1.622[/C][C]1.66547[/C][C]1.64183[/C][C]0.023641[/C][C]-0.0434743[/C][/ROW]
[ROW][C]44[/C][C]1.669[/C][C]1.67891[/C][C]1.65013[/C][C]0.0287826[/C][C]-0.00990764[/C][/ROW]
[ROW][C]45[/C][C]1.663[/C][C]1.68581[/C][C]1.65925[/C][C]0.0265576[/C][C]-0.0228076[/C][/ROW]
[ROW][C]46[/C][C]1.624[/C][C]1.66503[/C][C]1.67004[/C][C]-0.00500903[/C][C]-0.0410326[/C][/ROW]
[ROW][C]47[/C][C]1.621[/C][C]1.63308[/C][C]1.67946[/C][C]-0.0463757[/C][C]-0.0120826[/C][/ROW]
[ROW][C]48[/C][C]1.607[/C][C]1.62412[/C][C]1.68504[/C][C]-0.0609174[/C][C]-0.0171243[/C][/ROW]
[ROW][C]49[/C][C]1.671[/C][C]1.64278[/C][C]1.69104[/C][C]-0.048259[/C][C]0.0282174[/C][/ROW]
[ROW][C]50[/C][C]1.699[/C][C]1.67796[/C][C]1.69788[/C][C]-0.0199174[/C][C]0.0210424[/C][/ROW]
[ROW][C]51[/C][C]1.751[/C][C]1.72367[/C][C]1.708[/C][C]0.0156743[/C][C]0.0273257[/C][/ROW]
[ROW][C]52[/C][C]1.821[/C][C]1.76195[/C][C]1.72312[/C][C]0.0388243[/C][C]0.0590507[/C][/ROW]
[ROW][C]53[/C][C]1.77[/C][C]1.76278[/C][C]1.73792[/C][C]0.024866[/C][C]0.00721736[/C][/ROW]
[ROW][C]54[/C][C]1.734[/C][C]1.77234[/C][C]1.75021[/C][C]0.0221326[/C][C]-0.038341[/C][/ROW]
[ROW][C]55[/C][C]1.703[/C][C]1.78239[/C][C]1.75875[/C][C]0.023641[/C][C]-0.079391[/C][/ROW]
[ROW][C]56[/C][C]1.752[/C][C]1.79287[/C][C]1.76408[/C][C]0.0287826[/C][C]-0.040866[/C][/ROW]
[ROW][C]57[/C][C]1.823[/C][C]1.79506[/C][C]1.7685[/C][C]0.0265576[/C][C]0.0279424[/C][/ROW]
[ROW][C]58[/C][C]1.827[/C][C]1.76316[/C][C]1.76817[/C][C]-0.00500903[/C][C]0.0638424[/C][/ROW]
[ROW][C]59[/C][C]1.773[/C][C]1.71737[/C][C]1.76375[/C][C]-0.0463757[/C][C]0.0556257[/C][/ROW]
[ROW][C]60[/C][C]1.75[/C][C]1.70046[/C][C]1.76138[/C][C]-0.0609174[/C][C]0.0495424[/C][/ROW]
[ROW][C]61[/C][C]1.733[/C][C]1.71424[/C][C]1.7625[/C][C]-0.048259[/C][C]0.018759[/C][/ROW]
[ROW][C]62[/C][C]1.765[/C][C]1.74437[/C][C]1.76429[/C][C]-0.0199174[/C][C]0.0206257[/C][/ROW]
[ROW][C]63[/C][C]1.791[/C][C]1.77872[/C][C]1.76304[/C][C]0.0156743[/C][C]0.012284[/C][/ROW]
[ROW][C]64[/C][C]1.773[/C][C]1.79499[/C][C]1.75617[/C][C]0.0388243[/C][C]-0.021991[/C][/ROW]
[ROW][C]65[/C][C]1.712[/C][C]1.77216[/C][C]1.74729[/C][C]0.024866[/C][C]-0.0601576[/C][/ROW]
[ROW][C]66[/C][C]1.735[/C][C]1.76301[/C][C]1.74088[/C][C]0.0221326[/C][C]-0.0280076[/C][/ROW]
[ROW][C]67[/C][C]1.729[/C][C]NA[/C][C]NA[/C][C]0.023641[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.769[/C][C]NA[/C][C]NA[/C][C]0.0287826[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.776[/C][C]NA[/C][C]NA[/C][C]0.0265576[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.709[/C][C]NA[/C][C]NA[/C][C]-0.00500903[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.678[/C][C]NA[/C][C]NA[/C][C]-0.0463757[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.691[/C][C]NA[/C][C]NA[/C][C]-0.0609174[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260791&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260791&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	1.5	NA	NA	-0.048259	NA
2	1.439	NA	NA	-0.0199174	NA
3	1.49	NA	NA	0.0156743	NA
4	1.502	NA	NA	0.0388243	NA
5	1.531	NA	NA	0.024866	NA
6	1.611	NA	NA	0.0221326	NA
7	1.644	1.4966	1.47296	0.023641	0.147401
8	1.559	1.4812	1.45242	0.0287826	0.0778007
9	1.553	1.46314	1.43658	0.0265576	0.089859
10	1.494	1.41466	1.41967	-0.00500903	0.0793424
11	1.298	1.35625	1.40262	-0.0463757	-0.0582493
12	1.215	1.32467	1.38558	-0.0609174	-0.109666
13	1.179	1.31807	1.36633	-0.048259	-0.139074
14	1.267	1.32987	1.34979	-0.0199174	-0.0628743
15	1.282	1.3533	1.33763	0.0156743	-0.0712993
16	1.304	1.36399	1.32517	0.0388243	-0.059991
17	1.32	1.34907	1.32421	0.024866	-0.0290743
18	1.413	1.35917	1.33704	0.0221326	0.0538257
19	1.38	1.37952	1.35588	0.023641	0.000484028
20	1.426	1.40312	1.37433	0.0287826	0.022884
21	1.394	1.4171	1.39054	0.0265576	-0.0230993
22	1.354	1.40357	1.40858	-0.00500903	-0.0495743
23	1.415	1.38112	1.4275	-0.0463757	0.0338757
24	1.406	1.38046	1.44138	-0.0609174	0.0255424
25	1.44	1.40278	1.45104	-0.048259	0.0372174
26	1.449	1.43946	1.45938	-0.0199174	0.00954236
27	1.489	1.48197	1.46629	0.0156743	0.00703403
28	1.53	1.51453	1.47571	0.0388243	0.0154674
29	1.548	1.50928	1.48442	0.024866	0.0387174
30	1.518	1.51613	1.494	0.0221326	0.00186736
31	1.507	1.53018	1.50654	0.023641	-0.0231826
32	1.499	1.54707	1.51829	0.0287826	-0.0480743
33	1.487	1.55706	1.5305	0.0265576	-0.0700576
34	1.487	1.53774	1.54275	-0.00500903	-0.050741
35	1.491	1.50833	1.55471	-0.0463757	-0.0173326
36	1.56	1.50646	1.56738	-0.0609174	0.0535424
37	1.587	1.53028	1.57854	-0.048259	0.0567174
38	1.584	1.5705	1.59042	-0.0199174	0.0135007
39	1.647	1.62051	1.60483	0.0156743	0.0264924
40	1.666	1.6567	1.61788	0.0388243	0.00930069
41	1.699	1.65387	1.629	0.024866	0.045134
42	1.671	1.65851	1.63638	0.0221326	0.0124924
43	1.622	1.66547	1.64183	0.023641	-0.0434743
44	1.669	1.67891	1.65013	0.0287826	-0.00990764
45	1.663	1.68581	1.65925	0.0265576	-0.0228076
46	1.624	1.66503	1.67004	-0.00500903	-0.0410326
47	1.621	1.63308	1.67946	-0.0463757	-0.0120826
48	1.607	1.62412	1.68504	-0.0609174	-0.0171243
49	1.671	1.64278	1.69104	-0.048259	0.0282174
50	1.699	1.67796	1.69788	-0.0199174	0.0210424
51	1.751	1.72367	1.708	0.0156743	0.0273257
52	1.821	1.76195	1.72312	0.0388243	0.0590507
53	1.77	1.76278	1.73792	0.024866	0.00721736
54	1.734	1.77234	1.75021	0.0221326	-0.038341
55	1.703	1.78239	1.75875	0.023641	-0.079391
56	1.752	1.79287	1.76408	0.0287826	-0.040866
57	1.823	1.79506	1.7685	0.0265576	0.0279424
58	1.827	1.76316	1.76817	-0.00500903	0.0638424
59	1.773	1.71737	1.76375	-0.0463757	0.0556257
60	1.75	1.70046	1.76138	-0.0609174	0.0495424
61	1.733	1.71424	1.7625	-0.048259	0.018759
62	1.765	1.74437	1.76429	-0.0199174	0.0206257
63	1.791	1.77872	1.76304	0.0156743	0.012284
64	1.773	1.79499	1.75617	0.0388243	-0.021991
65	1.712	1.77216	1.74729	0.024866	-0.0601576
66	1.735	1.76301	1.74088	0.0221326	-0.0280076
67	1.729	NA	NA	0.023641	NA
68	1.769	NA	NA	0.0287826	NA
69	1.776	NA	NA	0.0265576	NA
70	1.709	NA	NA	-0.00500903	NA
71	1.678	NA	NA	-0.0463757	NA
72	1.691	NA	NA	-0.0609174	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