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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 22 May 2015 14:17:05 +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/2015/May/22/t14323013983g0ltbauiqttgy7.htm/, Retrieved Fri, 03 May 2024 07:46:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279225, Retrieved Fri, 03 May 2024 07:46:17 +0000

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-       [Classical Decomposition] [] [2015-05-22 13:17:05] [d41d8cd98f00b204e9800998ecf8427e] [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	'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279225&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279225&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279225&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	96.86	NA	NA	-0.0414583	NA
2	96.89	NA	NA	-0.387827	NA
3	96.9	NA	NA	-0.341518	NA
4	96.94	NA	NA	-0.293304	NA
5	96.88	NA	NA	-0.211399	NA
6	96.89	NA	NA	-0.204732	NA
7	96.89	96.8425	97.0479	-0.205387	0.0474702
8	96.95	97.0556	97.0888	-0.0331845	-0.105565
9	97.03	97.2421	97.1246	0.11753	-0.212113
10	97.29	97.6092	97.1608	0.448363	-0.319196
11	97.37	97.7729	97.2038	0.569196	-0.402946
12	97.41	97.8375	97.2538	0.58372	-0.42747
13	97.41	97.2631	97.3046	-0.0414583	0.146875
14	97.32	96.9684	97.3562	-0.387827	0.351577
15	97.33	97.0689	97.4104	-0.341518	0.261101
16	97.38	97.1704	97.4637	-0.293304	0.209554
17	97.47	97.3032	97.5146	-0.211399	0.166815
18	97.5	97.3611	97.5658	-0.204732	0.138899
19	97.5	97.4121	97.6175	-0.205387	0.0878869
20	97.58	97.636	97.6692	-0.0331845	-0.0559821
21	97.7	97.8454	97.7279	0.11753	-0.145446
22	97.9	98.2429	97.7946	0.448363	-0.342946
23	97.98	98.4338	97.8646	0.569196	-0.45378
24	98.03	98.5229	97.9392	0.58372	-0.492887
25	98.03	97.9748	98.0162	-0.0414583	0.0552083
26	97.94	97.7034	98.0912	-0.387827	0.236577
27	98.12	97.8306	98.1721	-0.341518	0.289435
28	98.19	97.9792	98.2725	-0.293304	0.210804
29	98.34	98.1786	98.39	-0.211399	0.161399
30	98.42	98.3099	98.5146	-0.204732	0.110149
31	98.43	98.4354	98.6408	-0.205387	-0.00544643
32	98.45	98.7251	98.7583	-0.0331845	-0.275149
33	98.77	98.9846	98.8671	0.11753	-0.214613
34	99.24	99.4234	98.975	0.448363	-0.183363
35	99.46	99.6488	99.0796	0.569196	-0.18878
36	99.54	99.7646	99.1808	0.58372	-0.224554
37	99.55	99.2398	99.2812	-0.0414583	0.310208
38	99.24	98.998	99.3858	-0.387827	0.241994
39	99.43	99.1435	99.485	-0.341518	0.286518
40	99.47	99.28	99.5733	-0.293304	0.18997
41	99.57	99.4494	99.6608	-0.211399	0.120565
42	99.62	99.5432	99.7479	-0.204732	0.0768155
43	99.64	99.6279	99.8333	-0.205387	0.0120536
44	99.75	99.8856	99.9188	-0.0331845	-0.135565
45	99.85	100.114	99.9967	0.11753	-0.264196
46	100.28	100.51	100.061	0.448363	-0.229613
47	100.52	100.685	100.115	0.569196	-0.164613
48	100.57	100.747	100.163	0.58372	-0.177054
49	100.57	100.168	100.209	-0.0414583	0.402292
50	100.27	99.8788	100.267	-0.387827	0.391161
51	100.27	99.9951	100.337	-0.341518	0.274851
52	100.18	100.111	100.404	-0.293304	0.0691369
53	100.16	100.252	100.463	-0.211399	-0.0915179
54	100.18	100.309	100.514	-0.204732	-0.129018
55	100.18	100.358	100.563	-0.205387	-0.17753
56	100.59	100.577	100.61	-0.0331845	0.0131845
57	100.69	100.778	100.66	0.11753	-0.0879464
58	101.06	101.176	100.728	0.448363	-0.11628
59	101.15	101.384	100.815	0.569196	-0.23378
60	101.16	101.494	100.91	0.58372	-0.33372
61	101.16	100.966	101.007	-0.0414583	0.194375
62	100.81	100.714	101.102	-0.387827	0.095744
63	100.94	100.863	101.205	-0.341518	0.0765179
64	101.13	101.028	101.321	-0.293304	0.10247
65	101.29	101.232	101.443	-0.211399	0.0584821
66	101.34	101.366	101.571	-0.204732	-0.0261012
67	101.35	101.496	101.701	-0.205387	-0.145863
68	101.7	101.791	101.824	-0.0331845	-0.0905655
69	102.05	102.052	101.934	0.11753	-0.00169643
70	102.48	102.488	102.039	0.448363	-0.00752976
71	102.66	102.712	102.142	0.569196	-0.0516964
72	102.72	102.831	102.247	0.58372	-0.110804
73	102.73	102.311	102.353	-0.0414583	0.418542
74	102.18	102.072	102.46	-0.387827	0.107827
75	102.22	102.219	102.561	-0.341518	0.000684524
76	102.37	102.358	102.651	-0.293304	0.0124702
77	102.53	102.526	102.737	-0.211399	0.00431548
78	102.61	102.617	102.822	-0.204732	-0.00735119
79	102.62	102.527	102.732	-0.205387	0.0928869
80	103	102.439	102.472	-0.0331845	0.561101
81	103.17	102.333	102.215	0.11753	0.83747
82	103.52	102.41	101.961	0.448363	1.11039
83	103.69	102.283	101.714	0.569196	1.40705
84	103.73	102.052	101.468	0.58372	1.67795
85	99.57	101.186	101.227	-0.0414583	-1.61604
86	99.09	100.603	100.991	-0.387827	-1.51342
87	99.14	100.418	100.759	-0.341518	-1.27765
88	99.36	100.243	100.536	-0.293304	-0.882946
89	99.6	100.109	100.32	-0.211399	-0.508601
90	99.65	99.9019	100.107	-0.204732	-0.251935
91	99.8	NA	NA	-0.205387	NA
92	100.15	NA	NA	-0.0331845	NA
93	100.45	NA	NA	0.11753	NA
94	100.89	NA	NA	0.448363	NA
95	101.13	NA	NA	0.569196	NA
96	101.17	NA	NA	0.58372	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 96.86 & NA & NA & -0.0414583 & NA \tabularnewline
2 & 96.89 & NA & NA & -0.387827 & NA \tabularnewline
3 & 96.9 & NA & NA & -0.341518 & NA \tabularnewline
4 & 96.94 & NA & NA & -0.293304 & NA \tabularnewline
5 & 96.88 & NA & NA & -0.211399 & NA \tabularnewline
6 & 96.89 & NA & NA & -0.204732 & NA \tabularnewline
7 & 96.89 & 96.8425 & 97.0479 & -0.205387 & 0.0474702 \tabularnewline
8 & 96.95 & 97.0556 & 97.0888 & -0.0331845 & -0.105565 \tabularnewline
9 & 97.03 & 97.2421 & 97.1246 & 0.11753 & -0.212113 \tabularnewline
10 & 97.29 & 97.6092 & 97.1608 & 0.448363 & -0.319196 \tabularnewline
11 & 97.37 & 97.7729 & 97.2038 & 0.569196 & -0.402946 \tabularnewline
12 & 97.41 & 97.8375 & 97.2538 & 0.58372 & -0.42747 \tabularnewline
13 & 97.41 & 97.2631 & 97.3046 & -0.0414583 & 0.146875 \tabularnewline
14 & 97.32 & 96.9684 & 97.3562 & -0.387827 & 0.351577 \tabularnewline
15 & 97.33 & 97.0689 & 97.4104 & -0.341518 & 0.261101 \tabularnewline
16 & 97.38 & 97.1704 & 97.4637 & -0.293304 & 0.209554 \tabularnewline
17 & 97.47 & 97.3032 & 97.5146 & -0.211399 & 0.166815 \tabularnewline
18 & 97.5 & 97.3611 & 97.5658 & -0.204732 & 0.138899 \tabularnewline
19 & 97.5 & 97.4121 & 97.6175 & -0.205387 & 0.0878869 \tabularnewline
20 & 97.58 & 97.636 & 97.6692 & -0.0331845 & -0.0559821 \tabularnewline
21 & 97.7 & 97.8454 & 97.7279 & 0.11753 & -0.145446 \tabularnewline
22 & 97.9 & 98.2429 & 97.7946 & 0.448363 & -0.342946 \tabularnewline
23 & 97.98 & 98.4338 & 97.8646 & 0.569196 & -0.45378 \tabularnewline
24 & 98.03 & 98.5229 & 97.9392 & 0.58372 & -0.492887 \tabularnewline
25 & 98.03 & 97.9748 & 98.0162 & -0.0414583 & 0.0552083 \tabularnewline
26 & 97.94 & 97.7034 & 98.0912 & -0.387827 & 0.236577 \tabularnewline
27 & 98.12 & 97.8306 & 98.1721 & -0.341518 & 0.289435 \tabularnewline
28 & 98.19 & 97.9792 & 98.2725 & -0.293304 & 0.210804 \tabularnewline
29 & 98.34 & 98.1786 & 98.39 & -0.211399 & 0.161399 \tabularnewline
30 & 98.42 & 98.3099 & 98.5146 & -0.204732 & 0.110149 \tabularnewline
31 & 98.43 & 98.4354 & 98.6408 & -0.205387 & -0.00544643 \tabularnewline
32 & 98.45 & 98.7251 & 98.7583 & -0.0331845 & -0.275149 \tabularnewline
33 & 98.77 & 98.9846 & 98.8671 & 0.11753 & -0.214613 \tabularnewline
34 & 99.24 & 99.4234 & 98.975 & 0.448363 & -0.183363 \tabularnewline
35 & 99.46 & 99.6488 & 99.0796 & 0.569196 & -0.18878 \tabularnewline
36 & 99.54 & 99.7646 & 99.1808 & 0.58372 & -0.224554 \tabularnewline
37 & 99.55 & 99.2398 & 99.2812 & -0.0414583 & 0.310208 \tabularnewline
38 & 99.24 & 98.998 & 99.3858 & -0.387827 & 0.241994 \tabularnewline
39 & 99.43 & 99.1435 & 99.485 & -0.341518 & 0.286518 \tabularnewline
40 & 99.47 & 99.28 & 99.5733 & -0.293304 & 0.18997 \tabularnewline
41 & 99.57 & 99.4494 & 99.6608 & -0.211399 & 0.120565 \tabularnewline
42 & 99.62 & 99.5432 & 99.7479 & -0.204732 & 0.0768155 \tabularnewline
43 & 99.64 & 99.6279 & 99.8333 & -0.205387 & 0.0120536 \tabularnewline
44 & 99.75 & 99.8856 & 99.9188 & -0.0331845 & -0.135565 \tabularnewline
45 & 99.85 & 100.114 & 99.9967 & 0.11753 & -0.264196 \tabularnewline
46 & 100.28 & 100.51 & 100.061 & 0.448363 & -0.229613 \tabularnewline
47 & 100.52 & 100.685 & 100.115 & 0.569196 & -0.164613 \tabularnewline
48 & 100.57 & 100.747 & 100.163 & 0.58372 & -0.177054 \tabularnewline
49 & 100.57 & 100.168 & 100.209 & -0.0414583 & 0.402292 \tabularnewline
50 & 100.27 & 99.8788 & 100.267 & -0.387827 & 0.391161 \tabularnewline
51 & 100.27 & 99.9951 & 100.337 & -0.341518 & 0.274851 \tabularnewline
52 & 100.18 & 100.111 & 100.404 & -0.293304 & 0.0691369 \tabularnewline
53 & 100.16 & 100.252 & 100.463 & -0.211399 & -0.0915179 \tabularnewline
54 & 100.18 & 100.309 & 100.514 & -0.204732 & -0.129018 \tabularnewline
55 & 100.18 & 100.358 & 100.563 & -0.205387 & -0.17753 \tabularnewline
56 & 100.59 & 100.577 & 100.61 & -0.0331845 & 0.0131845 \tabularnewline
57 & 100.69 & 100.778 & 100.66 & 0.11753 & -0.0879464 \tabularnewline
58 & 101.06 & 101.176 & 100.728 & 0.448363 & -0.11628 \tabularnewline
59 & 101.15 & 101.384 & 100.815 & 0.569196 & -0.23378 \tabularnewline
60 & 101.16 & 101.494 & 100.91 & 0.58372 & -0.33372 \tabularnewline
61 & 101.16 & 100.966 & 101.007 & -0.0414583 & 0.194375 \tabularnewline
62 & 100.81 & 100.714 & 101.102 & -0.387827 & 0.095744 \tabularnewline
63 & 100.94 & 100.863 & 101.205 & -0.341518 & 0.0765179 \tabularnewline
64 & 101.13 & 101.028 & 101.321 & -0.293304 & 0.10247 \tabularnewline
65 & 101.29 & 101.232 & 101.443 & -0.211399 & 0.0584821 \tabularnewline
66 & 101.34 & 101.366 & 101.571 & -0.204732 & -0.0261012 \tabularnewline
67 & 101.35 & 101.496 & 101.701 & -0.205387 & -0.145863 \tabularnewline
68 & 101.7 & 101.791 & 101.824 & -0.0331845 & -0.0905655 \tabularnewline
69 & 102.05 & 102.052 & 101.934 & 0.11753 & -0.00169643 \tabularnewline
70 & 102.48 & 102.488 & 102.039 & 0.448363 & -0.00752976 \tabularnewline
71 & 102.66 & 102.712 & 102.142 & 0.569196 & -0.0516964 \tabularnewline
72 & 102.72 & 102.831 & 102.247 & 0.58372 & -0.110804 \tabularnewline
73 & 102.73 & 102.311 & 102.353 & -0.0414583 & 0.418542 \tabularnewline
74 & 102.18 & 102.072 & 102.46 & -0.387827 & 0.107827 \tabularnewline
75 & 102.22 & 102.219 & 102.561 & -0.341518 & 0.000684524 \tabularnewline
76 & 102.37 & 102.358 & 102.651 & -0.293304 & 0.0124702 \tabularnewline
77 & 102.53 & 102.526 & 102.737 & -0.211399 & 0.00431548 \tabularnewline
78 & 102.61 & 102.617 & 102.822 & -0.204732 & -0.00735119 \tabularnewline
79 & 102.62 & 102.527 & 102.732 & -0.205387 & 0.0928869 \tabularnewline
80 & 103 & 102.439 & 102.472 & -0.0331845 & 0.561101 \tabularnewline
81 & 103.17 & 102.333 & 102.215 & 0.11753 & 0.83747 \tabularnewline
82 & 103.52 & 102.41 & 101.961 & 0.448363 & 1.11039 \tabularnewline
83 & 103.69 & 102.283 & 101.714 & 0.569196 & 1.40705 \tabularnewline
84 & 103.73 & 102.052 & 101.468 & 0.58372 & 1.67795 \tabularnewline
85 & 99.57 & 101.186 & 101.227 & -0.0414583 & -1.61604 \tabularnewline
86 & 99.09 & 100.603 & 100.991 & -0.387827 & -1.51342 \tabularnewline
87 & 99.14 & 100.418 & 100.759 & -0.341518 & -1.27765 \tabularnewline
88 & 99.36 & 100.243 & 100.536 & -0.293304 & -0.882946 \tabularnewline
89 & 99.6 & 100.109 & 100.32 & -0.211399 & -0.508601 \tabularnewline
90 & 99.65 & 99.9019 & 100.107 & -0.204732 & -0.251935 \tabularnewline
91 & 99.8 & NA & NA & -0.205387 & NA \tabularnewline
92 & 100.15 & NA & NA & -0.0331845 & NA \tabularnewline
93 & 100.45 & NA & NA & 0.11753 & NA \tabularnewline
94 & 100.89 & NA & NA & 0.448363 & NA \tabularnewline
95 & 101.13 & NA & NA & 0.569196 & NA \tabularnewline
96 & 101.17 & NA & NA & 0.58372 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279225&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]96.86[/C][C]NA[/C][C]NA[/C][C]-0.0414583[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]96.89[/C][C]NA[/C][C]NA[/C][C]-0.387827[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]96.9[/C][C]NA[/C][C]NA[/C][C]-0.341518[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]96.94[/C][C]NA[/C][C]NA[/C][C]-0.293304[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]96.88[/C][C]NA[/C][C]NA[/C][C]-0.211399[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]96.89[/C][C]NA[/C][C]NA[/C][C]-0.204732[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]96.89[/C][C]96.8425[/C][C]97.0479[/C][C]-0.205387[/C][C]0.0474702[/C][/ROW]
[ROW][C]8[/C][C]96.95[/C][C]97.0556[/C][C]97.0888[/C][C]-0.0331845[/C][C]-0.105565[/C][/ROW]
[ROW][C]9[/C][C]97.03[/C][C]97.2421[/C][C]97.1246[/C][C]0.11753[/C][C]-0.212113[/C][/ROW]
[ROW][C]10[/C][C]97.29[/C][C]97.6092[/C][C]97.1608[/C][C]0.448363[/C][C]-0.319196[/C][/ROW]
[ROW][C]11[/C][C]97.37[/C][C]97.7729[/C][C]97.2038[/C][C]0.569196[/C][C]-0.402946[/C][/ROW]
[ROW][C]12[/C][C]97.41[/C][C]97.8375[/C][C]97.2538[/C][C]0.58372[/C][C]-0.42747[/C][/ROW]
[ROW][C]13[/C][C]97.41[/C][C]97.2631[/C][C]97.3046[/C][C]-0.0414583[/C][C]0.146875[/C][/ROW]
[ROW][C]14[/C][C]97.32[/C][C]96.9684[/C][C]97.3562[/C][C]-0.387827[/C][C]0.351577[/C][/ROW]
[ROW][C]15[/C][C]97.33[/C][C]97.0689[/C][C]97.4104[/C][C]-0.341518[/C][C]0.261101[/C][/ROW]
[ROW][C]16[/C][C]97.38[/C][C]97.1704[/C][C]97.4637[/C][C]-0.293304[/C][C]0.209554[/C][/ROW]
[ROW][C]17[/C][C]97.47[/C][C]97.3032[/C][C]97.5146[/C][C]-0.211399[/C][C]0.166815[/C][/ROW]
[ROW][C]18[/C][C]97.5[/C][C]97.3611[/C][C]97.5658[/C][C]-0.204732[/C][C]0.138899[/C][/ROW]
[ROW][C]19[/C][C]97.5[/C][C]97.4121[/C][C]97.6175[/C][C]-0.205387[/C][C]0.0878869[/C][/ROW]
[ROW][C]20[/C][C]97.58[/C][C]97.636[/C][C]97.6692[/C][C]-0.0331845[/C][C]-0.0559821[/C][/ROW]
[ROW][C]21[/C][C]97.7[/C][C]97.8454[/C][C]97.7279[/C][C]0.11753[/C][C]-0.145446[/C][/ROW]
[ROW][C]22[/C][C]97.9[/C][C]98.2429[/C][C]97.7946[/C][C]0.448363[/C][C]-0.342946[/C][/ROW]
[ROW][C]23[/C][C]97.98[/C][C]98.4338[/C][C]97.8646[/C][C]0.569196[/C][C]-0.45378[/C][/ROW]
[ROW][C]24[/C][C]98.03[/C][C]98.5229[/C][C]97.9392[/C][C]0.58372[/C][C]-0.492887[/C][/ROW]
[ROW][C]25[/C][C]98.03[/C][C]97.9748[/C][C]98.0162[/C][C]-0.0414583[/C][C]0.0552083[/C][/ROW]
[ROW][C]26[/C][C]97.94[/C][C]97.7034[/C][C]98.0912[/C][C]-0.387827[/C][C]0.236577[/C][/ROW]
[ROW][C]27[/C][C]98.12[/C][C]97.8306[/C][C]98.1721[/C][C]-0.341518[/C][C]0.289435[/C][/ROW]
[ROW][C]28[/C][C]98.19[/C][C]97.9792[/C][C]98.2725[/C][C]-0.293304[/C][C]0.210804[/C][/ROW]
[ROW][C]29[/C][C]98.34[/C][C]98.1786[/C][C]98.39[/C][C]-0.211399[/C][C]0.161399[/C][/ROW]
[ROW][C]30[/C][C]98.42[/C][C]98.3099[/C][C]98.5146[/C][C]-0.204732[/C][C]0.110149[/C][/ROW]
[ROW][C]31[/C][C]98.43[/C][C]98.4354[/C][C]98.6408[/C][C]-0.205387[/C][C]-0.00544643[/C][/ROW]
[ROW][C]32[/C][C]98.45[/C][C]98.7251[/C][C]98.7583[/C][C]-0.0331845[/C][C]-0.275149[/C][/ROW]
[ROW][C]33[/C][C]98.77[/C][C]98.9846[/C][C]98.8671[/C][C]0.11753[/C][C]-0.214613[/C][/ROW]
[ROW][C]34[/C][C]99.24[/C][C]99.4234[/C][C]98.975[/C][C]0.448363[/C][C]-0.183363[/C][/ROW]
[ROW][C]35[/C][C]99.46[/C][C]99.6488[/C][C]99.0796[/C][C]0.569196[/C][C]-0.18878[/C][/ROW]
[ROW][C]36[/C][C]99.54[/C][C]99.7646[/C][C]99.1808[/C][C]0.58372[/C][C]-0.224554[/C][/ROW]
[ROW][C]37[/C][C]99.55[/C][C]99.2398[/C][C]99.2812[/C][C]-0.0414583[/C][C]0.310208[/C][/ROW]
[ROW][C]38[/C][C]99.24[/C][C]98.998[/C][C]99.3858[/C][C]-0.387827[/C][C]0.241994[/C][/ROW]
[ROW][C]39[/C][C]99.43[/C][C]99.1435[/C][C]99.485[/C][C]-0.341518[/C][C]0.286518[/C][/ROW]
[ROW][C]40[/C][C]99.47[/C][C]99.28[/C][C]99.5733[/C][C]-0.293304[/C][C]0.18997[/C][/ROW]
[ROW][C]41[/C][C]99.57[/C][C]99.4494[/C][C]99.6608[/C][C]-0.211399[/C][C]0.120565[/C][/ROW]
[ROW][C]42[/C][C]99.62[/C][C]99.5432[/C][C]99.7479[/C][C]-0.204732[/C][C]0.0768155[/C][/ROW]
[ROW][C]43[/C][C]99.64[/C][C]99.6279[/C][C]99.8333[/C][C]-0.205387[/C][C]0.0120536[/C][/ROW]
[ROW][C]44[/C][C]99.75[/C][C]99.8856[/C][C]99.9188[/C][C]-0.0331845[/C][C]-0.135565[/C][/ROW]
[ROW][C]45[/C][C]99.85[/C][C]100.114[/C][C]99.9967[/C][C]0.11753[/C][C]-0.264196[/C][/ROW]
[ROW][C]46[/C][C]100.28[/C][C]100.51[/C][C]100.061[/C][C]0.448363[/C][C]-0.229613[/C][/ROW]
[ROW][C]47[/C][C]100.52[/C][C]100.685[/C][C]100.115[/C][C]0.569196[/C][C]-0.164613[/C][/ROW]
[ROW][C]48[/C][C]100.57[/C][C]100.747[/C][C]100.163[/C][C]0.58372[/C][C]-0.177054[/C][/ROW]
[ROW][C]49[/C][C]100.57[/C][C]100.168[/C][C]100.209[/C][C]-0.0414583[/C][C]0.402292[/C][/ROW]
[ROW][C]50[/C][C]100.27[/C][C]99.8788[/C][C]100.267[/C][C]-0.387827[/C][C]0.391161[/C][/ROW]
[ROW][C]51[/C][C]100.27[/C][C]99.9951[/C][C]100.337[/C][C]-0.341518[/C][C]0.274851[/C][/ROW]
[ROW][C]52[/C][C]100.18[/C][C]100.111[/C][C]100.404[/C][C]-0.293304[/C][C]0.0691369[/C][/ROW]
[ROW][C]53[/C][C]100.16[/C][C]100.252[/C][C]100.463[/C][C]-0.211399[/C][C]-0.0915179[/C][/ROW]
[ROW][C]54[/C][C]100.18[/C][C]100.309[/C][C]100.514[/C][C]-0.204732[/C][C]-0.129018[/C][/ROW]
[ROW][C]55[/C][C]100.18[/C][C]100.358[/C][C]100.563[/C][C]-0.205387[/C][C]-0.17753[/C][/ROW]
[ROW][C]56[/C][C]100.59[/C][C]100.577[/C][C]100.61[/C][C]-0.0331845[/C][C]0.0131845[/C][/ROW]
[ROW][C]57[/C][C]100.69[/C][C]100.778[/C][C]100.66[/C][C]0.11753[/C][C]-0.0879464[/C][/ROW]
[ROW][C]58[/C][C]101.06[/C][C]101.176[/C][C]100.728[/C][C]0.448363[/C][C]-0.11628[/C][/ROW]
[ROW][C]59[/C][C]101.15[/C][C]101.384[/C][C]100.815[/C][C]0.569196[/C][C]-0.23378[/C][/ROW]
[ROW][C]60[/C][C]101.16[/C][C]101.494[/C][C]100.91[/C][C]0.58372[/C][C]-0.33372[/C][/ROW]
[ROW][C]61[/C][C]101.16[/C][C]100.966[/C][C]101.007[/C][C]-0.0414583[/C][C]0.194375[/C][/ROW]
[ROW][C]62[/C][C]100.81[/C][C]100.714[/C][C]101.102[/C][C]-0.387827[/C][C]0.095744[/C][/ROW]
[ROW][C]63[/C][C]100.94[/C][C]100.863[/C][C]101.205[/C][C]-0.341518[/C][C]0.0765179[/C][/ROW]
[ROW][C]64[/C][C]101.13[/C][C]101.028[/C][C]101.321[/C][C]-0.293304[/C][C]0.10247[/C][/ROW]
[ROW][C]65[/C][C]101.29[/C][C]101.232[/C][C]101.443[/C][C]-0.211399[/C][C]0.0584821[/C][/ROW]
[ROW][C]66[/C][C]101.34[/C][C]101.366[/C][C]101.571[/C][C]-0.204732[/C][C]-0.0261012[/C][/ROW]
[ROW][C]67[/C][C]101.35[/C][C]101.496[/C][C]101.701[/C][C]-0.205387[/C][C]-0.145863[/C][/ROW]
[ROW][C]68[/C][C]101.7[/C][C]101.791[/C][C]101.824[/C][C]-0.0331845[/C][C]-0.0905655[/C][/ROW]
[ROW][C]69[/C][C]102.05[/C][C]102.052[/C][C]101.934[/C][C]0.11753[/C][C]-0.00169643[/C][/ROW]
[ROW][C]70[/C][C]102.48[/C][C]102.488[/C][C]102.039[/C][C]0.448363[/C][C]-0.00752976[/C][/ROW]
[ROW][C]71[/C][C]102.66[/C][C]102.712[/C][C]102.142[/C][C]0.569196[/C][C]-0.0516964[/C][/ROW]
[ROW][C]72[/C][C]102.72[/C][C]102.831[/C][C]102.247[/C][C]0.58372[/C][C]-0.110804[/C][/ROW]
[ROW][C]73[/C][C]102.73[/C][C]102.311[/C][C]102.353[/C][C]-0.0414583[/C][C]0.418542[/C][/ROW]
[ROW][C]74[/C][C]102.18[/C][C]102.072[/C][C]102.46[/C][C]-0.387827[/C][C]0.107827[/C][/ROW]
[ROW][C]75[/C][C]102.22[/C][C]102.219[/C][C]102.561[/C][C]-0.341518[/C][C]0.000684524[/C][/ROW]
[ROW][C]76[/C][C]102.37[/C][C]102.358[/C][C]102.651[/C][C]-0.293304[/C][C]0.0124702[/C][/ROW]
[ROW][C]77[/C][C]102.53[/C][C]102.526[/C][C]102.737[/C][C]-0.211399[/C][C]0.00431548[/C][/ROW]
[ROW][C]78[/C][C]102.61[/C][C]102.617[/C][C]102.822[/C][C]-0.204732[/C][C]-0.00735119[/C][/ROW]
[ROW][C]79[/C][C]102.62[/C][C]102.527[/C][C]102.732[/C][C]-0.205387[/C][C]0.0928869[/C][/ROW]
[ROW][C]80[/C][C]103[/C][C]102.439[/C][C]102.472[/C][C]-0.0331845[/C][C]0.561101[/C][/ROW]
[ROW][C]81[/C][C]103.17[/C][C]102.333[/C][C]102.215[/C][C]0.11753[/C][C]0.83747[/C][/ROW]
[ROW][C]82[/C][C]103.52[/C][C]102.41[/C][C]101.961[/C][C]0.448363[/C][C]1.11039[/C][/ROW]
[ROW][C]83[/C][C]103.69[/C][C]102.283[/C][C]101.714[/C][C]0.569196[/C][C]1.40705[/C][/ROW]
[ROW][C]84[/C][C]103.73[/C][C]102.052[/C][C]101.468[/C][C]0.58372[/C][C]1.67795[/C][/ROW]
[ROW][C]85[/C][C]99.57[/C][C]101.186[/C][C]101.227[/C][C]-0.0414583[/C][C]-1.61604[/C][/ROW]
[ROW][C]86[/C][C]99.09[/C][C]100.603[/C][C]100.991[/C][C]-0.387827[/C][C]-1.51342[/C][/ROW]
[ROW][C]87[/C][C]99.14[/C][C]100.418[/C][C]100.759[/C][C]-0.341518[/C][C]-1.27765[/C][/ROW]
[ROW][C]88[/C][C]99.36[/C][C]100.243[/C][C]100.536[/C][C]-0.293304[/C][C]-0.882946[/C][/ROW]
[ROW][C]89[/C][C]99.6[/C][C]100.109[/C][C]100.32[/C][C]-0.211399[/C][C]-0.508601[/C][/ROW]
[ROW][C]90[/C][C]99.65[/C][C]99.9019[/C][C]100.107[/C][C]-0.204732[/C][C]-0.251935[/C][/ROW]
[ROW][C]91[/C][C]99.8[/C][C]NA[/C][C]NA[/C][C]-0.205387[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]100.15[/C][C]NA[/C][C]NA[/C][C]-0.0331845[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]100.45[/C][C]NA[/C][C]NA[/C][C]0.11753[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]100.89[/C][C]NA[/C][C]NA[/C][C]0.448363[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]101.13[/C][C]NA[/C][C]NA[/C][C]0.569196[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]101.17[/C][C]NA[/C][C]NA[/C][C]0.58372[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279225&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279225&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	96.86	NA	NA	-0.0414583	NA
2	96.89	NA	NA	-0.387827	NA
3	96.9	NA	NA	-0.341518	NA
4	96.94	NA	NA	-0.293304	NA
5	96.88	NA	NA	-0.211399	NA
6	96.89	NA	NA	-0.204732	NA
7	96.89	96.8425	97.0479	-0.205387	0.0474702
8	96.95	97.0556	97.0888	-0.0331845	-0.105565
9	97.03	97.2421	97.1246	0.11753	-0.212113
10	97.29	97.6092	97.1608	0.448363	-0.319196
11	97.37	97.7729	97.2038	0.569196	-0.402946
12	97.41	97.8375	97.2538	0.58372	-0.42747
13	97.41	97.2631	97.3046	-0.0414583	0.146875
14	97.32	96.9684	97.3562	-0.387827	0.351577
15	97.33	97.0689	97.4104	-0.341518	0.261101
16	97.38	97.1704	97.4637	-0.293304	0.209554
17	97.47	97.3032	97.5146	-0.211399	0.166815
18	97.5	97.3611	97.5658	-0.204732	0.138899
19	97.5	97.4121	97.6175	-0.205387	0.0878869
20	97.58	97.636	97.6692	-0.0331845	-0.0559821
21	97.7	97.8454	97.7279	0.11753	-0.145446
22	97.9	98.2429	97.7946	0.448363	-0.342946
23	97.98	98.4338	97.8646	0.569196	-0.45378
24	98.03	98.5229	97.9392	0.58372	-0.492887
25	98.03	97.9748	98.0162	-0.0414583	0.0552083
26	97.94	97.7034	98.0912	-0.387827	0.236577
27	98.12	97.8306	98.1721	-0.341518	0.289435
28	98.19	97.9792	98.2725	-0.293304	0.210804
29	98.34	98.1786	98.39	-0.211399	0.161399
30	98.42	98.3099	98.5146	-0.204732	0.110149
31	98.43	98.4354	98.6408	-0.205387	-0.00544643
32	98.45	98.7251	98.7583	-0.0331845	-0.275149
33	98.77	98.9846	98.8671	0.11753	-0.214613
34	99.24	99.4234	98.975	0.448363	-0.183363
35	99.46	99.6488	99.0796	0.569196	-0.18878
36	99.54	99.7646	99.1808	0.58372	-0.224554
37	99.55	99.2398	99.2812	-0.0414583	0.310208
38	99.24	98.998	99.3858	-0.387827	0.241994
39	99.43	99.1435	99.485	-0.341518	0.286518
40	99.47	99.28	99.5733	-0.293304	0.18997
41	99.57	99.4494	99.6608	-0.211399	0.120565
42	99.62	99.5432	99.7479	-0.204732	0.0768155
43	99.64	99.6279	99.8333	-0.205387	0.0120536
44	99.75	99.8856	99.9188	-0.0331845	-0.135565
45	99.85	100.114	99.9967	0.11753	-0.264196
46	100.28	100.51	100.061	0.448363	-0.229613
47	100.52	100.685	100.115	0.569196	-0.164613
48	100.57	100.747	100.163	0.58372	-0.177054
49	100.57	100.168	100.209	-0.0414583	0.402292
50	100.27	99.8788	100.267	-0.387827	0.391161
51	100.27	99.9951	100.337	-0.341518	0.274851
52	100.18	100.111	100.404	-0.293304	0.0691369
53	100.16	100.252	100.463	-0.211399	-0.0915179
54	100.18	100.309	100.514	-0.204732	-0.129018
55	100.18	100.358	100.563	-0.205387	-0.17753
56	100.59	100.577	100.61	-0.0331845	0.0131845
57	100.69	100.778	100.66	0.11753	-0.0879464
58	101.06	101.176	100.728	0.448363	-0.11628
59	101.15	101.384	100.815	0.569196	-0.23378
60	101.16	101.494	100.91	0.58372	-0.33372
61	101.16	100.966	101.007	-0.0414583	0.194375
62	100.81	100.714	101.102	-0.387827	0.095744
63	100.94	100.863	101.205	-0.341518	0.0765179
64	101.13	101.028	101.321	-0.293304	0.10247
65	101.29	101.232	101.443	-0.211399	0.0584821
66	101.34	101.366	101.571	-0.204732	-0.0261012
67	101.35	101.496	101.701	-0.205387	-0.145863
68	101.7	101.791	101.824	-0.0331845	-0.0905655
69	102.05	102.052	101.934	0.11753	-0.00169643
70	102.48	102.488	102.039	0.448363	-0.00752976
71	102.66	102.712	102.142	0.569196	-0.0516964
72	102.72	102.831	102.247	0.58372	-0.110804
73	102.73	102.311	102.353	-0.0414583	0.418542
74	102.18	102.072	102.46	-0.387827	0.107827
75	102.22	102.219	102.561	-0.341518	0.000684524
76	102.37	102.358	102.651	-0.293304	0.0124702
77	102.53	102.526	102.737	-0.211399	0.00431548
78	102.61	102.617	102.822	-0.204732	-0.00735119
79	102.62	102.527	102.732	-0.205387	0.0928869
80	103	102.439	102.472	-0.0331845	0.561101
81	103.17	102.333	102.215	0.11753	0.83747
82	103.52	102.41	101.961	0.448363	1.11039
83	103.69	102.283	101.714	0.569196	1.40705
84	103.73	102.052	101.468	0.58372	1.67795
85	99.57	101.186	101.227	-0.0414583	-1.61604
86	99.09	100.603	100.991	-0.387827	-1.51342
87	99.14	100.418	100.759	-0.341518	-1.27765
88	99.36	100.243	100.536	-0.293304	-0.882946
89	99.6	100.109	100.32	-0.211399	-0.508601
90	99.65	99.9019	100.107	-0.204732	-0.251935
91	99.8	NA	NA	-0.205387	NA
92	100.15	NA	NA	-0.0331845	NA
93	100.45	NA	NA	0.11753	NA
94	100.89	NA	NA	0.448363	NA
95	101.13	NA	NA	0.569196	NA
96	101.17	NA	NA	0.58372	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 <- 'additive'
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