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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Tue, 26 Apr 2016 18:58:08 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/26/t1461693510p3t0khad2qny1s1.htm/, Retrieved Fri, 03 May 2024 21:21:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294945, Retrieved Fri, 03 May 2024 21:21:34 +0000

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-     [Exponential Smoothing] [] [2016-04-26 17:44:48] [dfa7ada218158d619493607d1a8bcc6c]
- RMPD    [Classical Decomposition] [] [2016-04-26 17:58:08] [98ac3b2d1325a88ddcc6e107efd9e1d0] [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	'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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294945&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294945&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294945&T=0

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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	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	84.51	NA	NA	-0.327396	NA
2	84.54	NA	NA	-0.152674	NA
3	84.27	NA	NA	-0.682812	NA
4	84.47	NA	NA	-0.667326	NA
5	84.25	NA	NA	-0.296493	NA
6	84.33	NA	NA	-0.0473958	NA
7	84.29	84.9016	84.2042	0.697465	-0.611632
8	84.53	84.9486	84.1396	0.809063	-0.418646
9	84.01	84.7393	84.0762	0.66309	-0.72934
10	84.18	84.3198	83.9771	0.342674	-0.139757
11	84.08	83.9259	83.8521	0.0738542	0.154062
12	83.44	83.3371	83.7492	-0.412049	0.102882
13	83.61	83.5264	83.8538	-0.327396	0.0836458
14	83.89	84.0323	84.185	-0.152674	-0.142326
15	83.4	83.8926	84.5754	-0.682812	-0.492604
16	82.96	84.3098	84.9771	-0.667326	-1.34976
17	82.76	85.1156	85.4121	-0.296493	-2.35559
18	83.35	85.8984	85.9458	-0.0473958	-2.54844
19	87.78	87.3366	86.6392	0.697465	0.443368
20	88.99	88.2166	87.4075	0.809063	0.773438
21	88.92	88.8502	88.1871	0.66309	0.0698264
22	88.91	89.4548	89.1121	0.342674	-0.544757
23	89.79	90.4584	90.3846	0.0738542	-0.668437
24	90.54	91.5763	91.9883	-0.412049	-1.03628
25	93.15	93.1859	93.5133	-0.327396	-0.0359375
26	92.79	94.6702	94.8229	-0.152674	-1.88024
27	93.21	95.4301	96.1129	-0.682812	-2.2201
28	95.35	96.7814	97.4488	-0.667326	-1.43142
29	100.91	98.4606	98.7571	-0.296493	2.44941
30	103.69	99.9355	99.9829	-0.0473958	3.75448
31	104.04	101.765	101.068	0.697465	2.27462
32	104.16	102.877	102.068	0.809063	1.2826
33	104.71	103.717	103.054	0.66309	0.99316
34	105.18	104.199	103.856	0.342674	0.981493
35	104.92	104.324	104.25	0.0738542	0.595729
36	104.83	103.797	104.209	-0.412049	1.03288
37	104.9	103.655	103.982	-0.327396	1.24531
38	105.05	103.635	103.787	-0.152674	1.41517
39	104.6	102.942	103.625	-0.682812	1.65823
40	103.21	102.757	103.425	-0.667326	0.452743
41	102.52	102.886	103.182	-0.296493	-0.366007
42	101.09	102.882	102.93	-0.0473958	-1.79219
43	101.19	103.363	102.666	0.697465	-2.1733
44	102.34	103.207	102.398	0.809063	-0.866979
45	102.62	102.793	102.13	0.66309	-0.172674
46	102.47	102.215	101.872	0.342674	0.255243
47	101.82	101.721	101.648	0.0738542	0.0986458
48	101.86	101.08	101.492	-0.412049	0.779965
49	101.54	101.067	101.395	-0.327396	0.472813
50	101.98	101.045	101.197	-0.152674	0.935174
51	101.23	100.219	100.902	-0.682812	1.01073
52	100.4	99.9614	100.629	-0.667326	0.438576
53	99.94	100.097	100.393	-0.296493	-0.15684
54	99.94	100.095	100.142	-0.0473958	-0.154688
55	100	100.514	99.8167	0.697465	-0.514132
56	98.8	100.23	99.4212	0.809063	-1.43031
57	99.07	99.6589	98.9958	0.66309	-0.588924
58	99.46	98.9898	98.6471	0.342674	0.470243
59	99.18	98.4555	98.3817	0.0738542	0.724479
60	98.47	97.7217	98.1337	-0.412049	0.748299
61	97.12	97.6851	98.0125	-0.327396	-0.565104
62	96.91	97.929	98.0817	-0.152674	-1.01899
63	96.09	97.5459	98.2287	-0.682812	-1.45594
64	97.17	97.6498	98.3171	-0.667326	-0.479757
65	96.8	98.0877	98.3842	-0.296493	-1.28767
66	97.13	98.4559	98.5033	-0.0473958	-1.32594
67	99.9	99.4425	98.745	0.697465	0.457535
68	100.56	100.024	99.2146	0.809063	0.536354
69	100.84	100.536	99.8725	0.66309	0.30441
70	99.81	100.956	100.613	0.342674	-1.14601
71	100.44	101.468	101.394	0.0738542	-1.02802
72	100.07	101.821	102.233	-0.412049	-1.75128
73	101.32	102.644	102.972	-0.327396	-1.32427
74	103.98	103.412	103.565	-0.152674	0.567674
75	104.81	103.434	104.117	-0.682812	1.37615
76	106.23	103.984	104.651	-0.667326	2.24608
77	106.48	104.887	105.183	-0.296493	1.59316
78	107.59	105.647	105.694	-0.0473958	1.94323
79	107.16	NA	NA	0.697465	NA
80	107.54	NA	NA	0.809063	NA
81	107.1	NA	NA	0.66309	NA
82	106.38	NA	NA	0.342674	NA
83	106.64	NA	NA	0.0738542	NA
84	106.13	NA	NA	-0.412049	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 84.51 & NA & NA & -0.327396 & NA \tabularnewline
2 & 84.54 & NA & NA & -0.152674 & NA \tabularnewline
3 & 84.27 & NA & NA & -0.682812 & NA \tabularnewline
4 & 84.47 & NA & NA & -0.667326 & NA \tabularnewline
5 & 84.25 & NA & NA & -0.296493 & NA \tabularnewline
6 & 84.33 & NA & NA & -0.0473958 & NA \tabularnewline
7 & 84.29 & 84.9016 & 84.2042 & 0.697465 & -0.611632 \tabularnewline
8 & 84.53 & 84.9486 & 84.1396 & 0.809063 & -0.418646 \tabularnewline
9 & 84.01 & 84.7393 & 84.0762 & 0.66309 & -0.72934 \tabularnewline
10 & 84.18 & 84.3198 & 83.9771 & 0.342674 & -0.139757 \tabularnewline
11 & 84.08 & 83.9259 & 83.8521 & 0.0738542 & 0.154062 \tabularnewline
12 & 83.44 & 83.3371 & 83.7492 & -0.412049 & 0.102882 \tabularnewline
13 & 83.61 & 83.5264 & 83.8538 & -0.327396 & 0.0836458 \tabularnewline
14 & 83.89 & 84.0323 & 84.185 & -0.152674 & -0.142326 \tabularnewline
15 & 83.4 & 83.8926 & 84.5754 & -0.682812 & -0.492604 \tabularnewline
16 & 82.96 & 84.3098 & 84.9771 & -0.667326 & -1.34976 \tabularnewline
17 & 82.76 & 85.1156 & 85.4121 & -0.296493 & -2.35559 \tabularnewline
18 & 83.35 & 85.8984 & 85.9458 & -0.0473958 & -2.54844 \tabularnewline
19 & 87.78 & 87.3366 & 86.6392 & 0.697465 & 0.443368 \tabularnewline
20 & 88.99 & 88.2166 & 87.4075 & 0.809063 & 0.773438 \tabularnewline
21 & 88.92 & 88.8502 & 88.1871 & 0.66309 & 0.0698264 \tabularnewline
22 & 88.91 & 89.4548 & 89.1121 & 0.342674 & -0.544757 \tabularnewline
23 & 89.79 & 90.4584 & 90.3846 & 0.0738542 & -0.668437 \tabularnewline
24 & 90.54 & 91.5763 & 91.9883 & -0.412049 & -1.03628 \tabularnewline
25 & 93.15 & 93.1859 & 93.5133 & -0.327396 & -0.0359375 \tabularnewline
26 & 92.79 & 94.6702 & 94.8229 & -0.152674 & -1.88024 \tabularnewline
27 & 93.21 & 95.4301 & 96.1129 & -0.682812 & -2.2201 \tabularnewline
28 & 95.35 & 96.7814 & 97.4488 & -0.667326 & -1.43142 \tabularnewline
29 & 100.91 & 98.4606 & 98.7571 & -0.296493 & 2.44941 \tabularnewline
30 & 103.69 & 99.9355 & 99.9829 & -0.0473958 & 3.75448 \tabularnewline
31 & 104.04 & 101.765 & 101.068 & 0.697465 & 2.27462 \tabularnewline
32 & 104.16 & 102.877 & 102.068 & 0.809063 & 1.2826 \tabularnewline
33 & 104.71 & 103.717 & 103.054 & 0.66309 & 0.99316 \tabularnewline
34 & 105.18 & 104.199 & 103.856 & 0.342674 & 0.981493 \tabularnewline
35 & 104.92 & 104.324 & 104.25 & 0.0738542 & 0.595729 \tabularnewline
36 & 104.83 & 103.797 & 104.209 & -0.412049 & 1.03288 \tabularnewline
37 & 104.9 & 103.655 & 103.982 & -0.327396 & 1.24531 \tabularnewline
38 & 105.05 & 103.635 & 103.787 & -0.152674 & 1.41517 \tabularnewline
39 & 104.6 & 102.942 & 103.625 & -0.682812 & 1.65823 \tabularnewline
40 & 103.21 & 102.757 & 103.425 & -0.667326 & 0.452743 \tabularnewline
41 & 102.52 & 102.886 & 103.182 & -0.296493 & -0.366007 \tabularnewline
42 & 101.09 & 102.882 & 102.93 & -0.0473958 & -1.79219 \tabularnewline
43 & 101.19 & 103.363 & 102.666 & 0.697465 & -2.1733 \tabularnewline
44 & 102.34 & 103.207 & 102.398 & 0.809063 & -0.866979 \tabularnewline
45 & 102.62 & 102.793 & 102.13 & 0.66309 & -0.172674 \tabularnewline
46 & 102.47 & 102.215 & 101.872 & 0.342674 & 0.255243 \tabularnewline
47 & 101.82 & 101.721 & 101.648 & 0.0738542 & 0.0986458 \tabularnewline
48 & 101.86 & 101.08 & 101.492 & -0.412049 & 0.779965 \tabularnewline
49 & 101.54 & 101.067 & 101.395 & -0.327396 & 0.472813 \tabularnewline
50 & 101.98 & 101.045 & 101.197 & -0.152674 & 0.935174 \tabularnewline
51 & 101.23 & 100.219 & 100.902 & -0.682812 & 1.01073 \tabularnewline
52 & 100.4 & 99.9614 & 100.629 & -0.667326 & 0.438576 \tabularnewline
53 & 99.94 & 100.097 & 100.393 & -0.296493 & -0.15684 \tabularnewline
54 & 99.94 & 100.095 & 100.142 & -0.0473958 & -0.154688 \tabularnewline
55 & 100 & 100.514 & 99.8167 & 0.697465 & -0.514132 \tabularnewline
56 & 98.8 & 100.23 & 99.4212 & 0.809063 & -1.43031 \tabularnewline
57 & 99.07 & 99.6589 & 98.9958 & 0.66309 & -0.588924 \tabularnewline
58 & 99.46 & 98.9898 & 98.6471 & 0.342674 & 0.470243 \tabularnewline
59 & 99.18 & 98.4555 & 98.3817 & 0.0738542 & 0.724479 \tabularnewline
60 & 98.47 & 97.7217 & 98.1337 & -0.412049 & 0.748299 \tabularnewline
61 & 97.12 & 97.6851 & 98.0125 & -0.327396 & -0.565104 \tabularnewline
62 & 96.91 & 97.929 & 98.0817 & -0.152674 & -1.01899 \tabularnewline
63 & 96.09 & 97.5459 & 98.2287 & -0.682812 & -1.45594 \tabularnewline
64 & 97.17 & 97.6498 & 98.3171 & -0.667326 & -0.479757 \tabularnewline
65 & 96.8 & 98.0877 & 98.3842 & -0.296493 & -1.28767 \tabularnewline
66 & 97.13 & 98.4559 & 98.5033 & -0.0473958 & -1.32594 \tabularnewline
67 & 99.9 & 99.4425 & 98.745 & 0.697465 & 0.457535 \tabularnewline
68 & 100.56 & 100.024 & 99.2146 & 0.809063 & 0.536354 \tabularnewline
69 & 100.84 & 100.536 & 99.8725 & 0.66309 & 0.30441 \tabularnewline
70 & 99.81 & 100.956 & 100.613 & 0.342674 & -1.14601 \tabularnewline
71 & 100.44 & 101.468 & 101.394 & 0.0738542 & -1.02802 \tabularnewline
72 & 100.07 & 101.821 & 102.233 & -0.412049 & -1.75128 \tabularnewline
73 & 101.32 & 102.644 & 102.972 & -0.327396 & -1.32427 \tabularnewline
74 & 103.98 & 103.412 & 103.565 & -0.152674 & 0.567674 \tabularnewline
75 & 104.81 & 103.434 & 104.117 & -0.682812 & 1.37615 \tabularnewline
76 & 106.23 & 103.984 & 104.651 & -0.667326 & 2.24608 \tabularnewline
77 & 106.48 & 104.887 & 105.183 & -0.296493 & 1.59316 \tabularnewline
78 & 107.59 & 105.647 & 105.694 & -0.0473958 & 1.94323 \tabularnewline
79 & 107.16 & NA & NA & 0.697465 & NA \tabularnewline
80 & 107.54 & NA & NA & 0.809063 & NA \tabularnewline
81 & 107.1 & NA & NA & 0.66309 & NA \tabularnewline
82 & 106.38 & NA & NA & 0.342674 & NA \tabularnewline
83 & 106.64 & NA & NA & 0.0738542 & NA \tabularnewline
84 & 106.13 & NA & NA & -0.412049 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294945&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]84.51[/C][C]NA[/C][C]NA[/C][C]-0.327396[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]84.54[/C][C]NA[/C][C]NA[/C][C]-0.152674[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]84.27[/C][C]NA[/C][C]NA[/C][C]-0.682812[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]84.47[/C][C]NA[/C][C]NA[/C][C]-0.667326[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]84.25[/C][C]NA[/C][C]NA[/C][C]-0.296493[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]84.33[/C][C]NA[/C][C]NA[/C][C]-0.0473958[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]84.29[/C][C]84.9016[/C][C]84.2042[/C][C]0.697465[/C][C]-0.611632[/C][/ROW]
[ROW][C]8[/C][C]84.53[/C][C]84.9486[/C][C]84.1396[/C][C]0.809063[/C][C]-0.418646[/C][/ROW]
[ROW][C]9[/C][C]84.01[/C][C]84.7393[/C][C]84.0762[/C][C]0.66309[/C][C]-0.72934[/C][/ROW]
[ROW][C]10[/C][C]84.18[/C][C]84.3198[/C][C]83.9771[/C][C]0.342674[/C][C]-0.139757[/C][/ROW]
[ROW][C]11[/C][C]84.08[/C][C]83.9259[/C][C]83.8521[/C][C]0.0738542[/C][C]0.154062[/C][/ROW]
[ROW][C]12[/C][C]83.44[/C][C]83.3371[/C][C]83.7492[/C][C]-0.412049[/C][C]0.102882[/C][/ROW]
[ROW][C]13[/C][C]83.61[/C][C]83.5264[/C][C]83.8538[/C][C]-0.327396[/C][C]0.0836458[/C][/ROW]
[ROW][C]14[/C][C]83.89[/C][C]84.0323[/C][C]84.185[/C][C]-0.152674[/C][C]-0.142326[/C][/ROW]
[ROW][C]15[/C][C]83.4[/C][C]83.8926[/C][C]84.5754[/C][C]-0.682812[/C][C]-0.492604[/C][/ROW]
[ROW][C]16[/C][C]82.96[/C][C]84.3098[/C][C]84.9771[/C][C]-0.667326[/C][C]-1.34976[/C][/ROW]
[ROW][C]17[/C][C]82.76[/C][C]85.1156[/C][C]85.4121[/C][C]-0.296493[/C][C]-2.35559[/C][/ROW]
[ROW][C]18[/C][C]83.35[/C][C]85.8984[/C][C]85.9458[/C][C]-0.0473958[/C][C]-2.54844[/C][/ROW]
[ROW][C]19[/C][C]87.78[/C][C]87.3366[/C][C]86.6392[/C][C]0.697465[/C][C]0.443368[/C][/ROW]
[ROW][C]20[/C][C]88.99[/C][C]88.2166[/C][C]87.4075[/C][C]0.809063[/C][C]0.773438[/C][/ROW]
[ROW][C]21[/C][C]88.92[/C][C]88.8502[/C][C]88.1871[/C][C]0.66309[/C][C]0.0698264[/C][/ROW]
[ROW][C]22[/C][C]88.91[/C][C]89.4548[/C][C]89.1121[/C][C]0.342674[/C][C]-0.544757[/C][/ROW]
[ROW][C]23[/C][C]89.79[/C][C]90.4584[/C][C]90.3846[/C][C]0.0738542[/C][C]-0.668437[/C][/ROW]
[ROW][C]24[/C][C]90.54[/C][C]91.5763[/C][C]91.9883[/C][C]-0.412049[/C][C]-1.03628[/C][/ROW]
[ROW][C]25[/C][C]93.15[/C][C]93.1859[/C][C]93.5133[/C][C]-0.327396[/C][C]-0.0359375[/C][/ROW]
[ROW][C]26[/C][C]92.79[/C][C]94.6702[/C][C]94.8229[/C][C]-0.152674[/C][C]-1.88024[/C][/ROW]
[ROW][C]27[/C][C]93.21[/C][C]95.4301[/C][C]96.1129[/C][C]-0.682812[/C][C]-2.2201[/C][/ROW]
[ROW][C]28[/C][C]95.35[/C][C]96.7814[/C][C]97.4488[/C][C]-0.667326[/C][C]-1.43142[/C][/ROW]
[ROW][C]29[/C][C]100.91[/C][C]98.4606[/C][C]98.7571[/C][C]-0.296493[/C][C]2.44941[/C][/ROW]
[ROW][C]30[/C][C]103.69[/C][C]99.9355[/C][C]99.9829[/C][C]-0.0473958[/C][C]3.75448[/C][/ROW]
[ROW][C]31[/C][C]104.04[/C][C]101.765[/C][C]101.068[/C][C]0.697465[/C][C]2.27462[/C][/ROW]
[ROW][C]32[/C][C]104.16[/C][C]102.877[/C][C]102.068[/C][C]0.809063[/C][C]1.2826[/C][/ROW]
[ROW][C]33[/C][C]104.71[/C][C]103.717[/C][C]103.054[/C][C]0.66309[/C][C]0.99316[/C][/ROW]
[ROW][C]34[/C][C]105.18[/C][C]104.199[/C][C]103.856[/C][C]0.342674[/C][C]0.981493[/C][/ROW]
[ROW][C]35[/C][C]104.92[/C][C]104.324[/C][C]104.25[/C][C]0.0738542[/C][C]0.595729[/C][/ROW]
[ROW][C]36[/C][C]104.83[/C][C]103.797[/C][C]104.209[/C][C]-0.412049[/C][C]1.03288[/C][/ROW]
[ROW][C]37[/C][C]104.9[/C][C]103.655[/C][C]103.982[/C][C]-0.327396[/C][C]1.24531[/C][/ROW]
[ROW][C]38[/C][C]105.05[/C][C]103.635[/C][C]103.787[/C][C]-0.152674[/C][C]1.41517[/C][/ROW]
[ROW][C]39[/C][C]104.6[/C][C]102.942[/C][C]103.625[/C][C]-0.682812[/C][C]1.65823[/C][/ROW]
[ROW][C]40[/C][C]103.21[/C][C]102.757[/C][C]103.425[/C][C]-0.667326[/C][C]0.452743[/C][/ROW]
[ROW][C]41[/C][C]102.52[/C][C]102.886[/C][C]103.182[/C][C]-0.296493[/C][C]-0.366007[/C][/ROW]
[ROW][C]42[/C][C]101.09[/C][C]102.882[/C][C]102.93[/C][C]-0.0473958[/C][C]-1.79219[/C][/ROW]
[ROW][C]43[/C][C]101.19[/C][C]103.363[/C][C]102.666[/C][C]0.697465[/C][C]-2.1733[/C][/ROW]
[ROW][C]44[/C][C]102.34[/C][C]103.207[/C][C]102.398[/C][C]0.809063[/C][C]-0.866979[/C][/ROW]
[ROW][C]45[/C][C]102.62[/C][C]102.793[/C][C]102.13[/C][C]0.66309[/C][C]-0.172674[/C][/ROW]
[ROW][C]46[/C][C]102.47[/C][C]102.215[/C][C]101.872[/C][C]0.342674[/C][C]0.255243[/C][/ROW]
[ROW][C]47[/C][C]101.82[/C][C]101.721[/C][C]101.648[/C][C]0.0738542[/C][C]0.0986458[/C][/ROW]
[ROW][C]48[/C][C]101.86[/C][C]101.08[/C][C]101.492[/C][C]-0.412049[/C][C]0.779965[/C][/ROW]
[ROW][C]49[/C][C]101.54[/C][C]101.067[/C][C]101.395[/C][C]-0.327396[/C][C]0.472813[/C][/ROW]
[ROW][C]50[/C][C]101.98[/C][C]101.045[/C][C]101.197[/C][C]-0.152674[/C][C]0.935174[/C][/ROW]
[ROW][C]51[/C][C]101.23[/C][C]100.219[/C][C]100.902[/C][C]-0.682812[/C][C]1.01073[/C][/ROW]
[ROW][C]52[/C][C]100.4[/C][C]99.9614[/C][C]100.629[/C][C]-0.667326[/C][C]0.438576[/C][/ROW]
[ROW][C]53[/C][C]99.94[/C][C]100.097[/C][C]100.393[/C][C]-0.296493[/C][C]-0.15684[/C][/ROW]
[ROW][C]54[/C][C]99.94[/C][C]100.095[/C][C]100.142[/C][C]-0.0473958[/C][C]-0.154688[/C][/ROW]
[ROW][C]55[/C][C]100[/C][C]100.514[/C][C]99.8167[/C][C]0.697465[/C][C]-0.514132[/C][/ROW]
[ROW][C]56[/C][C]98.8[/C][C]100.23[/C][C]99.4212[/C][C]0.809063[/C][C]-1.43031[/C][/ROW]
[ROW][C]57[/C][C]99.07[/C][C]99.6589[/C][C]98.9958[/C][C]0.66309[/C][C]-0.588924[/C][/ROW]
[ROW][C]58[/C][C]99.46[/C][C]98.9898[/C][C]98.6471[/C][C]0.342674[/C][C]0.470243[/C][/ROW]
[ROW][C]59[/C][C]99.18[/C][C]98.4555[/C][C]98.3817[/C][C]0.0738542[/C][C]0.724479[/C][/ROW]
[ROW][C]60[/C][C]98.47[/C][C]97.7217[/C][C]98.1337[/C][C]-0.412049[/C][C]0.748299[/C][/ROW]
[ROW][C]61[/C][C]97.12[/C][C]97.6851[/C][C]98.0125[/C][C]-0.327396[/C][C]-0.565104[/C][/ROW]
[ROW][C]62[/C][C]96.91[/C][C]97.929[/C][C]98.0817[/C][C]-0.152674[/C][C]-1.01899[/C][/ROW]
[ROW][C]63[/C][C]96.09[/C][C]97.5459[/C][C]98.2287[/C][C]-0.682812[/C][C]-1.45594[/C][/ROW]
[ROW][C]64[/C][C]97.17[/C][C]97.6498[/C][C]98.3171[/C][C]-0.667326[/C][C]-0.479757[/C][/ROW]
[ROW][C]65[/C][C]96.8[/C][C]98.0877[/C][C]98.3842[/C][C]-0.296493[/C][C]-1.28767[/C][/ROW]
[ROW][C]66[/C][C]97.13[/C][C]98.4559[/C][C]98.5033[/C][C]-0.0473958[/C][C]-1.32594[/C][/ROW]
[ROW][C]67[/C][C]99.9[/C][C]99.4425[/C][C]98.745[/C][C]0.697465[/C][C]0.457535[/C][/ROW]
[ROW][C]68[/C][C]100.56[/C][C]100.024[/C][C]99.2146[/C][C]0.809063[/C][C]0.536354[/C][/ROW]
[ROW][C]69[/C][C]100.84[/C][C]100.536[/C][C]99.8725[/C][C]0.66309[/C][C]0.30441[/C][/ROW]
[ROW][C]70[/C][C]99.81[/C][C]100.956[/C][C]100.613[/C][C]0.342674[/C][C]-1.14601[/C][/ROW]
[ROW][C]71[/C][C]100.44[/C][C]101.468[/C][C]101.394[/C][C]0.0738542[/C][C]-1.02802[/C][/ROW]
[ROW][C]72[/C][C]100.07[/C][C]101.821[/C][C]102.233[/C][C]-0.412049[/C][C]-1.75128[/C][/ROW]
[ROW][C]73[/C][C]101.32[/C][C]102.644[/C][C]102.972[/C][C]-0.327396[/C][C]-1.32427[/C][/ROW]
[ROW][C]74[/C][C]103.98[/C][C]103.412[/C][C]103.565[/C][C]-0.152674[/C][C]0.567674[/C][/ROW]
[ROW][C]75[/C][C]104.81[/C][C]103.434[/C][C]104.117[/C][C]-0.682812[/C][C]1.37615[/C][/ROW]
[ROW][C]76[/C][C]106.23[/C][C]103.984[/C][C]104.651[/C][C]-0.667326[/C][C]2.24608[/C][/ROW]
[ROW][C]77[/C][C]106.48[/C][C]104.887[/C][C]105.183[/C][C]-0.296493[/C][C]1.59316[/C][/ROW]
[ROW][C]78[/C][C]107.59[/C][C]105.647[/C][C]105.694[/C][C]-0.0473958[/C][C]1.94323[/C][/ROW]
[ROW][C]79[/C][C]107.16[/C][C]NA[/C][C]NA[/C][C]0.697465[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]107.54[/C][C]NA[/C][C]NA[/C][C]0.809063[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]107.1[/C][C]NA[/C][C]NA[/C][C]0.66309[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]106.38[/C][C]NA[/C][C]NA[/C][C]0.342674[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]106.64[/C][C]NA[/C][C]NA[/C][C]0.0738542[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]106.13[/C][C]NA[/C][C]NA[/C][C]-0.412049[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294945&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294945&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	84.51	NA	NA	-0.327396	NA
2	84.54	NA	NA	-0.152674	NA
3	84.27	NA	NA	-0.682812	NA
4	84.47	NA	NA	-0.667326	NA
5	84.25	NA	NA	-0.296493	NA
6	84.33	NA	NA	-0.0473958	NA
7	84.29	84.9016	84.2042	0.697465	-0.611632
8	84.53	84.9486	84.1396	0.809063	-0.418646
9	84.01	84.7393	84.0762	0.66309	-0.72934
10	84.18	84.3198	83.9771	0.342674	-0.139757
11	84.08	83.9259	83.8521	0.0738542	0.154062
12	83.44	83.3371	83.7492	-0.412049	0.102882
13	83.61	83.5264	83.8538	-0.327396	0.0836458
14	83.89	84.0323	84.185	-0.152674	-0.142326
15	83.4	83.8926	84.5754	-0.682812	-0.492604
16	82.96	84.3098	84.9771	-0.667326	-1.34976
17	82.76	85.1156	85.4121	-0.296493	-2.35559
18	83.35	85.8984	85.9458	-0.0473958	-2.54844
19	87.78	87.3366	86.6392	0.697465	0.443368
20	88.99	88.2166	87.4075	0.809063	0.773438
21	88.92	88.8502	88.1871	0.66309	0.0698264
22	88.91	89.4548	89.1121	0.342674	-0.544757
23	89.79	90.4584	90.3846	0.0738542	-0.668437
24	90.54	91.5763	91.9883	-0.412049	-1.03628
25	93.15	93.1859	93.5133	-0.327396	-0.0359375
26	92.79	94.6702	94.8229	-0.152674	-1.88024
27	93.21	95.4301	96.1129	-0.682812	-2.2201
28	95.35	96.7814	97.4488	-0.667326	-1.43142
29	100.91	98.4606	98.7571	-0.296493	2.44941
30	103.69	99.9355	99.9829	-0.0473958	3.75448
31	104.04	101.765	101.068	0.697465	2.27462
32	104.16	102.877	102.068	0.809063	1.2826
33	104.71	103.717	103.054	0.66309	0.99316
34	105.18	104.199	103.856	0.342674	0.981493
35	104.92	104.324	104.25	0.0738542	0.595729
36	104.83	103.797	104.209	-0.412049	1.03288
37	104.9	103.655	103.982	-0.327396	1.24531
38	105.05	103.635	103.787	-0.152674	1.41517
39	104.6	102.942	103.625	-0.682812	1.65823
40	103.21	102.757	103.425	-0.667326	0.452743
41	102.52	102.886	103.182	-0.296493	-0.366007
42	101.09	102.882	102.93	-0.0473958	-1.79219
43	101.19	103.363	102.666	0.697465	-2.1733
44	102.34	103.207	102.398	0.809063	-0.866979
45	102.62	102.793	102.13	0.66309	-0.172674
46	102.47	102.215	101.872	0.342674	0.255243
47	101.82	101.721	101.648	0.0738542	0.0986458
48	101.86	101.08	101.492	-0.412049	0.779965
49	101.54	101.067	101.395	-0.327396	0.472813
50	101.98	101.045	101.197	-0.152674	0.935174
51	101.23	100.219	100.902	-0.682812	1.01073
52	100.4	99.9614	100.629	-0.667326	0.438576
53	99.94	100.097	100.393	-0.296493	-0.15684
54	99.94	100.095	100.142	-0.0473958	-0.154688
55	100	100.514	99.8167	0.697465	-0.514132
56	98.8	100.23	99.4212	0.809063	-1.43031
57	99.07	99.6589	98.9958	0.66309	-0.588924
58	99.46	98.9898	98.6471	0.342674	0.470243
59	99.18	98.4555	98.3817	0.0738542	0.724479
60	98.47	97.7217	98.1337	-0.412049	0.748299
61	97.12	97.6851	98.0125	-0.327396	-0.565104
62	96.91	97.929	98.0817	-0.152674	-1.01899
63	96.09	97.5459	98.2287	-0.682812	-1.45594
64	97.17	97.6498	98.3171	-0.667326	-0.479757
65	96.8	98.0877	98.3842	-0.296493	-1.28767
66	97.13	98.4559	98.5033	-0.0473958	-1.32594
67	99.9	99.4425	98.745	0.697465	0.457535
68	100.56	100.024	99.2146	0.809063	0.536354
69	100.84	100.536	99.8725	0.66309	0.30441
70	99.81	100.956	100.613	0.342674	-1.14601
71	100.44	101.468	101.394	0.0738542	-1.02802
72	100.07	101.821	102.233	-0.412049	-1.75128
73	101.32	102.644	102.972	-0.327396	-1.32427
74	103.98	103.412	103.565	-0.152674	0.567674
75	104.81	103.434	104.117	-0.682812	1.37615
76	106.23	103.984	104.651	-0.667326	2.24608
77	106.48	104.887	105.183	-0.296493	1.59316
78	107.59	105.647	105.694	-0.0473958	1.94323
79	107.16	NA	NA	0.697465	NA
80	107.54	NA	NA	0.809063	NA
81	107.1	NA	NA	0.66309	NA
82	106.38	NA	NA	0.342674	NA
83	106.64	NA	NA	0.0738542	NA
84	106.13	NA	NA	-0.412049	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 = 12 ; par2 = Double ; par3 = multiplicative ;

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