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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 May 2015 09:57:13 +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/25/t1432545139gfv6cpnqcbstqym.htm/, Retrieved Tue, 07 May 2024 06:16:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279328, Retrieved Tue, 07 May 2024 06:16:43 +0000

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-       [Classical Decomposition] [consumentenprijze...] [2015-05-25 08:57:13] [0793dda36b6d92f80d1980fc1d00d6bd] [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=279328&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=279328&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279328&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.68	NA	NA	0.991283	NA
2	99.06	NA	NA	0.996464	NA
3	99.84	NA	NA	1.00563	NA
4	100.3	NA	NA	1.00749	NA
5	100.38	NA	NA	1.00657	NA
6	100.02	NA	NA	1.001	NA
7	99.83	99.9175	100.057	0.998601	0.999124
8	100.36	100.109	100.177	0.999315	1.00251
9	100.74	100.553	100.314	1.00239	1.00186
10	100.49	100.59	100.464	1.00126	0.999003
11	100.33	100.388	100.615	0.997743	0.999419
12	99.96	99.9839	100.764	0.992261	0.99976
13	100.08	100.018	100.898	0.991283	1.00062
14	100.54	100.647	101.005	0.996464	0.998933
15	101.63	101.675	101.106	1.00563	0.999554
16	102.12	101.987	101.229	1.00749	1.0013
17	102.19	102.044	101.377	1.00657	1.00143
18	101.77	101.637	101.535	1.001	1.00131
19	101.29	101.556	101.698	0.998601	0.997384
20	101.47	101.807	101.877	0.999315	0.996691
21	102.07	102.306	102.062	1.00239	0.997696
22	102.11	102.368	102.24	1.00126	0.997476
23	102.26	102.195	102.426	0.997743	1.00064
24	101.83	101.839	102.634	0.992261	0.999907
25	102.11	101.981	102.878	0.991283	1.00126
26	102.8	102.785	103.15	0.996464	1.00015
27	103.82	103.998	103.416	1.00563	0.998289
28	104.2	104.44	103.664	1.00749	0.997698
29	104.57	104.562	103.879	1.00657	1.00008
30	104.38	104.162	104.058	1.001	1.0021
31	104.54	104.076	104.222	0.998601	1.00446
32	104.74	104.316	104.388	0.999315	1.00406
33	105.19	104.806	104.557	1.00239	1.00366
34	104.95	104.852	104.721	1.00126	1.00093
35	104.57	104.633	104.87	0.997743	0.999399
36	103.81	104.189	105.001	0.992261	0.996366
37	104.08	104.156	105.072	0.991283	0.999273
38	104.81	104.72	105.092	0.996464	1.00086
39	105.86	105.713	105.121	1.00563	1.0014
40	106.1	105.956	105.168	1.00749	1.00136
41	106.24	105.933	105.241	1.00657	1.0029
42	105.87	105.437	105.331	1.001	1.00411
43	104.74	105.267	105.415	0.998601	0.994992
44	105.03	105.414	105.486	0.999315	0.996358
45	105.59	105.819	105.567	1.00239	0.997835
46	105.69	105.794	105.661	1.00126	0.999018
47	105.58	105.514	105.753	0.997743	1.00062
48	104.96	105.012	105.831	0.992261	0.999503
49	104.93	105.015	105.938	0.991283	0.999192
50	105.68	105.699	106.075	0.996464	0.999816
51	106.93	106.807	106.21	1.00563	1.00115
52	107.29	107.145	106.348	1.00749	1.00136
53	107.25	107.186	106.486	1.00657	1.0006
54	106.74	106.745	106.639	1.001	0.99995
55	106.44	106.655	106.804	0.998601	0.997986
56	106.6	106.895	106.968	0.999315	0.99724
57	107.26	107.39	107.134	1.00239	0.998794
58	107.35	107.442	107.307	1.00126	0.999145
59	107.22	107.252	107.495	0.997743	0.999698
60	106.99	106.854	107.687	0.992261	1.00128
61	106.87	106.973	107.913	0.991283	0.999041
62	107.68	107.793	108.176	0.996464	0.998949
63	108.9	109.038	108.428	1.00563	0.998733
64	109.48	109.481	108.667	1.00749	0.999993
65	109.57	109.612	108.896	1.00657	0.999619
66	109.03	109.223	109.114	1.001	0.998234
67	109.58	109.179	109.332	0.998601	1.00367
68	109.76	109.479	109.554	0.999315	1.00257
69	110.15	110.04	109.778	1.00239	1.001
70	110.2	110.136	109.998	1.00126	1.00058
71	109.86	109.954	110.203	0.997743	0.999144
72	109.58	109.543	110.397	0.992261	1.00034
73	109.52	109.635	110.599	0.991283	0.998955
74	110.35	110.415	110.807	0.996464	0.999413
75	111.61	111.641	111.016	1.00563	0.999721
76	112.06	112.087	111.254	1.00749	0.999757
77	111.9	112.246	111.512	1.00657	0.996921
78	111.36	111.883	111.771	1.001	0.995329
79	112.09	111.881	112.038	0.998601	1.00187
80	112.24	112.234	112.311	0.999315	1.00005
81	112.7	112.854	112.585	1.00239	0.998637
82	113.36	112.984	112.842	1.00126	1.00333
83	112.9	112.837	113.092	0.997743	1.00056
84	112.74	112.478	113.355	0.992261	1.00233
85	112.77	112.642	113.633	0.991283	1.00113
86	113.66	113.505	113.908	0.996464	1.00136
87	114.87	114.797	114.154	1.00563	1.00064
88	114.97	115.199	114.343	1.00749	0.998011
89	115	115.239	114.486	1.00657	0.99793
90	114.57	114.748	114.633	1.001	0.998449
91	115.54	NA	NA	0.998601	NA
92	115.39	NA	NA	0.999315	NA
93	115.46	NA	NA	1.00239	NA
94	115.13	NA	NA	1.00126	NA
95	114.56	NA	NA	0.997743	NA
96	114.62	NA	NA	0.992261	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 98.68 & NA & NA & 0.991283 & NA \tabularnewline
2 & 99.06 & NA & NA & 0.996464 & NA \tabularnewline
3 & 99.84 & NA & NA & 1.00563 & NA \tabularnewline
4 & 100.3 & NA & NA & 1.00749 & NA \tabularnewline
5 & 100.38 & NA & NA & 1.00657 & NA \tabularnewline
6 & 100.02 & NA & NA & 1.001 & NA \tabularnewline
7 & 99.83 & 99.9175 & 100.057 & 0.998601 & 0.999124 \tabularnewline
8 & 100.36 & 100.109 & 100.177 & 0.999315 & 1.00251 \tabularnewline
9 & 100.74 & 100.553 & 100.314 & 1.00239 & 1.00186 \tabularnewline
10 & 100.49 & 100.59 & 100.464 & 1.00126 & 0.999003 \tabularnewline
11 & 100.33 & 100.388 & 100.615 & 0.997743 & 0.999419 \tabularnewline
12 & 99.96 & 99.9839 & 100.764 & 0.992261 & 0.99976 \tabularnewline
13 & 100.08 & 100.018 & 100.898 & 0.991283 & 1.00062 \tabularnewline
14 & 100.54 & 100.647 & 101.005 & 0.996464 & 0.998933 \tabularnewline
15 & 101.63 & 101.675 & 101.106 & 1.00563 & 0.999554 \tabularnewline
16 & 102.12 & 101.987 & 101.229 & 1.00749 & 1.0013 \tabularnewline
17 & 102.19 & 102.044 & 101.377 & 1.00657 & 1.00143 \tabularnewline
18 & 101.77 & 101.637 & 101.535 & 1.001 & 1.00131 \tabularnewline
19 & 101.29 & 101.556 & 101.698 & 0.998601 & 0.997384 \tabularnewline
20 & 101.47 & 101.807 & 101.877 & 0.999315 & 0.996691 \tabularnewline
21 & 102.07 & 102.306 & 102.062 & 1.00239 & 0.997696 \tabularnewline
22 & 102.11 & 102.368 & 102.24 & 1.00126 & 0.997476 \tabularnewline
23 & 102.26 & 102.195 & 102.426 & 0.997743 & 1.00064 \tabularnewline
24 & 101.83 & 101.839 & 102.634 & 0.992261 & 0.999907 \tabularnewline
25 & 102.11 & 101.981 & 102.878 & 0.991283 & 1.00126 \tabularnewline
26 & 102.8 & 102.785 & 103.15 & 0.996464 & 1.00015 \tabularnewline
27 & 103.82 & 103.998 & 103.416 & 1.00563 & 0.998289 \tabularnewline
28 & 104.2 & 104.44 & 103.664 & 1.00749 & 0.997698 \tabularnewline
29 & 104.57 & 104.562 & 103.879 & 1.00657 & 1.00008 \tabularnewline
30 & 104.38 & 104.162 & 104.058 & 1.001 & 1.0021 \tabularnewline
31 & 104.54 & 104.076 & 104.222 & 0.998601 & 1.00446 \tabularnewline
32 & 104.74 & 104.316 & 104.388 & 0.999315 & 1.00406 \tabularnewline
33 & 105.19 & 104.806 & 104.557 & 1.00239 & 1.00366 \tabularnewline
34 & 104.95 & 104.852 & 104.721 & 1.00126 & 1.00093 \tabularnewline
35 & 104.57 & 104.633 & 104.87 & 0.997743 & 0.999399 \tabularnewline
36 & 103.81 & 104.189 & 105.001 & 0.992261 & 0.996366 \tabularnewline
37 & 104.08 & 104.156 & 105.072 & 0.991283 & 0.999273 \tabularnewline
38 & 104.81 & 104.72 & 105.092 & 0.996464 & 1.00086 \tabularnewline
39 & 105.86 & 105.713 & 105.121 & 1.00563 & 1.0014 \tabularnewline
40 & 106.1 & 105.956 & 105.168 & 1.00749 & 1.00136 \tabularnewline
41 & 106.24 & 105.933 & 105.241 & 1.00657 & 1.0029 \tabularnewline
42 & 105.87 & 105.437 & 105.331 & 1.001 & 1.00411 \tabularnewline
43 & 104.74 & 105.267 & 105.415 & 0.998601 & 0.994992 \tabularnewline
44 & 105.03 & 105.414 & 105.486 & 0.999315 & 0.996358 \tabularnewline
45 & 105.59 & 105.819 & 105.567 & 1.00239 & 0.997835 \tabularnewline
46 & 105.69 & 105.794 & 105.661 & 1.00126 & 0.999018 \tabularnewline
47 & 105.58 & 105.514 & 105.753 & 0.997743 & 1.00062 \tabularnewline
48 & 104.96 & 105.012 & 105.831 & 0.992261 & 0.999503 \tabularnewline
49 & 104.93 & 105.015 & 105.938 & 0.991283 & 0.999192 \tabularnewline
50 & 105.68 & 105.699 & 106.075 & 0.996464 & 0.999816 \tabularnewline
51 & 106.93 & 106.807 & 106.21 & 1.00563 & 1.00115 \tabularnewline
52 & 107.29 & 107.145 & 106.348 & 1.00749 & 1.00136 \tabularnewline
53 & 107.25 & 107.186 & 106.486 & 1.00657 & 1.0006 \tabularnewline
54 & 106.74 & 106.745 & 106.639 & 1.001 & 0.99995 \tabularnewline
55 & 106.44 & 106.655 & 106.804 & 0.998601 & 0.997986 \tabularnewline
56 & 106.6 & 106.895 & 106.968 & 0.999315 & 0.99724 \tabularnewline
57 & 107.26 & 107.39 & 107.134 & 1.00239 & 0.998794 \tabularnewline
58 & 107.35 & 107.442 & 107.307 & 1.00126 & 0.999145 \tabularnewline
59 & 107.22 & 107.252 & 107.495 & 0.997743 & 0.999698 \tabularnewline
60 & 106.99 & 106.854 & 107.687 & 0.992261 & 1.00128 \tabularnewline
61 & 106.87 & 106.973 & 107.913 & 0.991283 & 0.999041 \tabularnewline
62 & 107.68 & 107.793 & 108.176 & 0.996464 & 0.998949 \tabularnewline
63 & 108.9 & 109.038 & 108.428 & 1.00563 & 0.998733 \tabularnewline
64 & 109.48 & 109.481 & 108.667 & 1.00749 & 0.999993 \tabularnewline
65 & 109.57 & 109.612 & 108.896 & 1.00657 & 0.999619 \tabularnewline
66 & 109.03 & 109.223 & 109.114 & 1.001 & 0.998234 \tabularnewline
67 & 109.58 & 109.179 & 109.332 & 0.998601 & 1.00367 \tabularnewline
68 & 109.76 & 109.479 & 109.554 & 0.999315 & 1.00257 \tabularnewline
69 & 110.15 & 110.04 & 109.778 & 1.00239 & 1.001 \tabularnewline
70 & 110.2 & 110.136 & 109.998 & 1.00126 & 1.00058 \tabularnewline
71 & 109.86 & 109.954 & 110.203 & 0.997743 & 0.999144 \tabularnewline
72 & 109.58 & 109.543 & 110.397 & 0.992261 & 1.00034 \tabularnewline
73 & 109.52 & 109.635 & 110.599 & 0.991283 & 0.998955 \tabularnewline
74 & 110.35 & 110.415 & 110.807 & 0.996464 & 0.999413 \tabularnewline
75 & 111.61 & 111.641 & 111.016 & 1.00563 & 0.999721 \tabularnewline
76 & 112.06 & 112.087 & 111.254 & 1.00749 & 0.999757 \tabularnewline
77 & 111.9 & 112.246 & 111.512 & 1.00657 & 0.996921 \tabularnewline
78 & 111.36 & 111.883 & 111.771 & 1.001 & 0.995329 \tabularnewline
79 & 112.09 & 111.881 & 112.038 & 0.998601 & 1.00187 \tabularnewline
80 & 112.24 & 112.234 & 112.311 & 0.999315 & 1.00005 \tabularnewline
81 & 112.7 & 112.854 & 112.585 & 1.00239 & 0.998637 \tabularnewline
82 & 113.36 & 112.984 & 112.842 & 1.00126 & 1.00333 \tabularnewline
83 & 112.9 & 112.837 & 113.092 & 0.997743 & 1.00056 \tabularnewline
84 & 112.74 & 112.478 & 113.355 & 0.992261 & 1.00233 \tabularnewline
85 & 112.77 & 112.642 & 113.633 & 0.991283 & 1.00113 \tabularnewline
86 & 113.66 & 113.505 & 113.908 & 0.996464 & 1.00136 \tabularnewline
87 & 114.87 & 114.797 & 114.154 & 1.00563 & 1.00064 \tabularnewline
88 & 114.97 & 115.199 & 114.343 & 1.00749 & 0.998011 \tabularnewline
89 & 115 & 115.239 & 114.486 & 1.00657 & 0.99793 \tabularnewline
90 & 114.57 & 114.748 & 114.633 & 1.001 & 0.998449 \tabularnewline
91 & 115.54 & NA & NA & 0.998601 & NA \tabularnewline
92 & 115.39 & NA & NA & 0.999315 & NA \tabularnewline
93 & 115.46 & NA & NA & 1.00239 & NA \tabularnewline
94 & 115.13 & NA & NA & 1.00126 & NA \tabularnewline
95 & 114.56 & NA & NA & 0.997743 & NA \tabularnewline
96 & 114.62 & NA & NA & 0.992261 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279328&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]98.68[/C][C]NA[/C][C]NA[/C][C]0.991283[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]99.06[/C][C]NA[/C][C]NA[/C][C]0.996464[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]99.84[/C][C]NA[/C][C]NA[/C][C]1.00563[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]100.3[/C][C]NA[/C][C]NA[/C][C]1.00749[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]100.38[/C][C]NA[/C][C]NA[/C][C]1.00657[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]100.02[/C][C]NA[/C][C]NA[/C][C]1.001[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]99.83[/C][C]99.9175[/C][C]100.057[/C][C]0.998601[/C][C]0.999124[/C][/ROW]
[ROW][C]8[/C][C]100.36[/C][C]100.109[/C][C]100.177[/C][C]0.999315[/C][C]1.00251[/C][/ROW]
[ROW][C]9[/C][C]100.74[/C][C]100.553[/C][C]100.314[/C][C]1.00239[/C][C]1.00186[/C][/ROW]
[ROW][C]10[/C][C]100.49[/C][C]100.59[/C][C]100.464[/C][C]1.00126[/C][C]0.999003[/C][/ROW]
[ROW][C]11[/C][C]100.33[/C][C]100.388[/C][C]100.615[/C][C]0.997743[/C][C]0.999419[/C][/ROW]
[ROW][C]12[/C][C]99.96[/C][C]99.9839[/C][C]100.764[/C][C]0.992261[/C][C]0.99976[/C][/ROW]
[ROW][C]13[/C][C]100.08[/C][C]100.018[/C][C]100.898[/C][C]0.991283[/C][C]1.00062[/C][/ROW]
[ROW][C]14[/C][C]100.54[/C][C]100.647[/C][C]101.005[/C][C]0.996464[/C][C]0.998933[/C][/ROW]
[ROW][C]15[/C][C]101.63[/C][C]101.675[/C][C]101.106[/C][C]1.00563[/C][C]0.999554[/C][/ROW]
[ROW][C]16[/C][C]102.12[/C][C]101.987[/C][C]101.229[/C][C]1.00749[/C][C]1.0013[/C][/ROW]
[ROW][C]17[/C][C]102.19[/C][C]102.044[/C][C]101.377[/C][C]1.00657[/C][C]1.00143[/C][/ROW]
[ROW][C]18[/C][C]101.77[/C][C]101.637[/C][C]101.535[/C][C]1.001[/C][C]1.00131[/C][/ROW]
[ROW][C]19[/C][C]101.29[/C][C]101.556[/C][C]101.698[/C][C]0.998601[/C][C]0.997384[/C][/ROW]
[ROW][C]20[/C][C]101.47[/C][C]101.807[/C][C]101.877[/C][C]0.999315[/C][C]0.996691[/C][/ROW]
[ROW][C]21[/C][C]102.07[/C][C]102.306[/C][C]102.062[/C][C]1.00239[/C][C]0.997696[/C][/ROW]
[ROW][C]22[/C][C]102.11[/C][C]102.368[/C][C]102.24[/C][C]1.00126[/C][C]0.997476[/C][/ROW]
[ROW][C]23[/C][C]102.26[/C][C]102.195[/C][C]102.426[/C][C]0.997743[/C][C]1.00064[/C][/ROW]
[ROW][C]24[/C][C]101.83[/C][C]101.839[/C][C]102.634[/C][C]0.992261[/C][C]0.999907[/C][/ROW]
[ROW][C]25[/C][C]102.11[/C][C]101.981[/C][C]102.878[/C][C]0.991283[/C][C]1.00126[/C][/ROW]
[ROW][C]26[/C][C]102.8[/C][C]102.785[/C][C]103.15[/C][C]0.996464[/C][C]1.00015[/C][/ROW]
[ROW][C]27[/C][C]103.82[/C][C]103.998[/C][C]103.416[/C][C]1.00563[/C][C]0.998289[/C][/ROW]
[ROW][C]28[/C][C]104.2[/C][C]104.44[/C][C]103.664[/C][C]1.00749[/C][C]0.997698[/C][/ROW]
[ROW][C]29[/C][C]104.57[/C][C]104.562[/C][C]103.879[/C][C]1.00657[/C][C]1.00008[/C][/ROW]
[ROW][C]30[/C][C]104.38[/C][C]104.162[/C][C]104.058[/C][C]1.001[/C][C]1.0021[/C][/ROW]
[ROW][C]31[/C][C]104.54[/C][C]104.076[/C][C]104.222[/C][C]0.998601[/C][C]1.00446[/C][/ROW]
[ROW][C]32[/C][C]104.74[/C][C]104.316[/C][C]104.388[/C][C]0.999315[/C][C]1.00406[/C][/ROW]
[ROW][C]33[/C][C]105.19[/C][C]104.806[/C][C]104.557[/C][C]1.00239[/C][C]1.00366[/C][/ROW]
[ROW][C]34[/C][C]104.95[/C][C]104.852[/C][C]104.721[/C][C]1.00126[/C][C]1.00093[/C][/ROW]
[ROW][C]35[/C][C]104.57[/C][C]104.633[/C][C]104.87[/C][C]0.997743[/C][C]0.999399[/C][/ROW]
[ROW][C]36[/C][C]103.81[/C][C]104.189[/C][C]105.001[/C][C]0.992261[/C][C]0.996366[/C][/ROW]
[ROW][C]37[/C][C]104.08[/C][C]104.156[/C][C]105.072[/C][C]0.991283[/C][C]0.999273[/C][/ROW]
[ROW][C]38[/C][C]104.81[/C][C]104.72[/C][C]105.092[/C][C]0.996464[/C][C]1.00086[/C][/ROW]
[ROW][C]39[/C][C]105.86[/C][C]105.713[/C][C]105.121[/C][C]1.00563[/C][C]1.0014[/C][/ROW]
[ROW][C]40[/C][C]106.1[/C][C]105.956[/C][C]105.168[/C][C]1.00749[/C][C]1.00136[/C][/ROW]
[ROW][C]41[/C][C]106.24[/C][C]105.933[/C][C]105.241[/C][C]1.00657[/C][C]1.0029[/C][/ROW]
[ROW][C]42[/C][C]105.87[/C][C]105.437[/C][C]105.331[/C][C]1.001[/C][C]1.00411[/C][/ROW]
[ROW][C]43[/C][C]104.74[/C][C]105.267[/C][C]105.415[/C][C]0.998601[/C][C]0.994992[/C][/ROW]
[ROW][C]44[/C][C]105.03[/C][C]105.414[/C][C]105.486[/C][C]0.999315[/C][C]0.996358[/C][/ROW]
[ROW][C]45[/C][C]105.59[/C][C]105.819[/C][C]105.567[/C][C]1.00239[/C][C]0.997835[/C][/ROW]
[ROW][C]46[/C][C]105.69[/C][C]105.794[/C][C]105.661[/C][C]1.00126[/C][C]0.999018[/C][/ROW]
[ROW][C]47[/C][C]105.58[/C][C]105.514[/C][C]105.753[/C][C]0.997743[/C][C]1.00062[/C][/ROW]
[ROW][C]48[/C][C]104.96[/C][C]105.012[/C][C]105.831[/C][C]0.992261[/C][C]0.999503[/C][/ROW]
[ROW][C]49[/C][C]104.93[/C][C]105.015[/C][C]105.938[/C][C]0.991283[/C][C]0.999192[/C][/ROW]
[ROW][C]50[/C][C]105.68[/C][C]105.699[/C][C]106.075[/C][C]0.996464[/C][C]0.999816[/C][/ROW]
[ROW][C]51[/C][C]106.93[/C][C]106.807[/C][C]106.21[/C][C]1.00563[/C][C]1.00115[/C][/ROW]
[ROW][C]52[/C][C]107.29[/C][C]107.145[/C][C]106.348[/C][C]1.00749[/C][C]1.00136[/C][/ROW]
[ROW][C]53[/C][C]107.25[/C][C]107.186[/C][C]106.486[/C][C]1.00657[/C][C]1.0006[/C][/ROW]
[ROW][C]54[/C][C]106.74[/C][C]106.745[/C][C]106.639[/C][C]1.001[/C][C]0.99995[/C][/ROW]
[ROW][C]55[/C][C]106.44[/C][C]106.655[/C][C]106.804[/C][C]0.998601[/C][C]0.997986[/C][/ROW]
[ROW][C]56[/C][C]106.6[/C][C]106.895[/C][C]106.968[/C][C]0.999315[/C][C]0.99724[/C][/ROW]
[ROW][C]57[/C][C]107.26[/C][C]107.39[/C][C]107.134[/C][C]1.00239[/C][C]0.998794[/C][/ROW]
[ROW][C]58[/C][C]107.35[/C][C]107.442[/C][C]107.307[/C][C]1.00126[/C][C]0.999145[/C][/ROW]
[ROW][C]59[/C][C]107.22[/C][C]107.252[/C][C]107.495[/C][C]0.997743[/C][C]0.999698[/C][/ROW]
[ROW][C]60[/C][C]106.99[/C][C]106.854[/C][C]107.687[/C][C]0.992261[/C][C]1.00128[/C][/ROW]
[ROW][C]61[/C][C]106.87[/C][C]106.973[/C][C]107.913[/C][C]0.991283[/C][C]0.999041[/C][/ROW]
[ROW][C]62[/C][C]107.68[/C][C]107.793[/C][C]108.176[/C][C]0.996464[/C][C]0.998949[/C][/ROW]
[ROW][C]63[/C][C]108.9[/C][C]109.038[/C][C]108.428[/C][C]1.00563[/C][C]0.998733[/C][/ROW]
[ROW][C]64[/C][C]109.48[/C][C]109.481[/C][C]108.667[/C][C]1.00749[/C][C]0.999993[/C][/ROW]
[ROW][C]65[/C][C]109.57[/C][C]109.612[/C][C]108.896[/C][C]1.00657[/C][C]0.999619[/C][/ROW]
[ROW][C]66[/C][C]109.03[/C][C]109.223[/C][C]109.114[/C][C]1.001[/C][C]0.998234[/C][/ROW]
[ROW][C]67[/C][C]109.58[/C][C]109.179[/C][C]109.332[/C][C]0.998601[/C][C]1.00367[/C][/ROW]
[ROW][C]68[/C][C]109.76[/C][C]109.479[/C][C]109.554[/C][C]0.999315[/C][C]1.00257[/C][/ROW]
[ROW][C]69[/C][C]110.15[/C][C]110.04[/C][C]109.778[/C][C]1.00239[/C][C]1.001[/C][/ROW]
[ROW][C]70[/C][C]110.2[/C][C]110.136[/C][C]109.998[/C][C]1.00126[/C][C]1.00058[/C][/ROW]
[ROW][C]71[/C][C]109.86[/C][C]109.954[/C][C]110.203[/C][C]0.997743[/C][C]0.999144[/C][/ROW]
[ROW][C]72[/C][C]109.58[/C][C]109.543[/C][C]110.397[/C][C]0.992261[/C][C]1.00034[/C][/ROW]
[ROW][C]73[/C][C]109.52[/C][C]109.635[/C][C]110.599[/C][C]0.991283[/C][C]0.998955[/C][/ROW]
[ROW][C]74[/C][C]110.35[/C][C]110.415[/C][C]110.807[/C][C]0.996464[/C][C]0.999413[/C][/ROW]
[ROW][C]75[/C][C]111.61[/C][C]111.641[/C][C]111.016[/C][C]1.00563[/C][C]0.999721[/C][/ROW]
[ROW][C]76[/C][C]112.06[/C][C]112.087[/C][C]111.254[/C][C]1.00749[/C][C]0.999757[/C][/ROW]
[ROW][C]77[/C][C]111.9[/C][C]112.246[/C][C]111.512[/C][C]1.00657[/C][C]0.996921[/C][/ROW]
[ROW][C]78[/C][C]111.36[/C][C]111.883[/C][C]111.771[/C][C]1.001[/C][C]0.995329[/C][/ROW]
[ROW][C]79[/C][C]112.09[/C][C]111.881[/C][C]112.038[/C][C]0.998601[/C][C]1.00187[/C][/ROW]
[ROW][C]80[/C][C]112.24[/C][C]112.234[/C][C]112.311[/C][C]0.999315[/C][C]1.00005[/C][/ROW]
[ROW][C]81[/C][C]112.7[/C][C]112.854[/C][C]112.585[/C][C]1.00239[/C][C]0.998637[/C][/ROW]
[ROW][C]82[/C][C]113.36[/C][C]112.984[/C][C]112.842[/C][C]1.00126[/C][C]1.00333[/C][/ROW]
[ROW][C]83[/C][C]112.9[/C][C]112.837[/C][C]113.092[/C][C]0.997743[/C][C]1.00056[/C][/ROW]
[ROW][C]84[/C][C]112.74[/C][C]112.478[/C][C]113.355[/C][C]0.992261[/C][C]1.00233[/C][/ROW]
[ROW][C]85[/C][C]112.77[/C][C]112.642[/C][C]113.633[/C][C]0.991283[/C][C]1.00113[/C][/ROW]
[ROW][C]86[/C][C]113.66[/C][C]113.505[/C][C]113.908[/C][C]0.996464[/C][C]1.00136[/C][/ROW]
[ROW][C]87[/C][C]114.87[/C][C]114.797[/C][C]114.154[/C][C]1.00563[/C][C]1.00064[/C][/ROW]
[ROW][C]88[/C][C]114.97[/C][C]115.199[/C][C]114.343[/C][C]1.00749[/C][C]0.998011[/C][/ROW]
[ROW][C]89[/C][C]115[/C][C]115.239[/C][C]114.486[/C][C]1.00657[/C][C]0.99793[/C][/ROW]
[ROW][C]90[/C][C]114.57[/C][C]114.748[/C][C]114.633[/C][C]1.001[/C][C]0.998449[/C][/ROW]
[ROW][C]91[/C][C]115.54[/C][C]NA[/C][C]NA[/C][C]0.998601[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]115.39[/C][C]NA[/C][C]NA[/C][C]0.999315[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]115.46[/C][C]NA[/C][C]NA[/C][C]1.00239[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]115.13[/C][C]NA[/C][C]NA[/C][C]1.00126[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]114.56[/C][C]NA[/C][C]NA[/C][C]0.997743[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]114.62[/C][C]NA[/C][C]NA[/C][C]0.992261[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279328&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279328&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.68	NA	NA	0.991283	NA
2	99.06	NA	NA	0.996464	NA
3	99.84	NA	NA	1.00563	NA
4	100.3	NA	NA	1.00749	NA
5	100.38	NA	NA	1.00657	NA
6	100.02	NA	NA	1.001	NA
7	99.83	99.9175	100.057	0.998601	0.999124
8	100.36	100.109	100.177	0.999315	1.00251
9	100.74	100.553	100.314	1.00239	1.00186
10	100.49	100.59	100.464	1.00126	0.999003
11	100.33	100.388	100.615	0.997743	0.999419
12	99.96	99.9839	100.764	0.992261	0.99976
13	100.08	100.018	100.898	0.991283	1.00062
14	100.54	100.647	101.005	0.996464	0.998933
15	101.63	101.675	101.106	1.00563	0.999554
16	102.12	101.987	101.229	1.00749	1.0013
17	102.19	102.044	101.377	1.00657	1.00143
18	101.77	101.637	101.535	1.001	1.00131
19	101.29	101.556	101.698	0.998601	0.997384
20	101.47	101.807	101.877	0.999315	0.996691
21	102.07	102.306	102.062	1.00239	0.997696
22	102.11	102.368	102.24	1.00126	0.997476
23	102.26	102.195	102.426	0.997743	1.00064
24	101.83	101.839	102.634	0.992261	0.999907
25	102.11	101.981	102.878	0.991283	1.00126
26	102.8	102.785	103.15	0.996464	1.00015
27	103.82	103.998	103.416	1.00563	0.998289
28	104.2	104.44	103.664	1.00749	0.997698
29	104.57	104.562	103.879	1.00657	1.00008
30	104.38	104.162	104.058	1.001	1.0021
31	104.54	104.076	104.222	0.998601	1.00446
32	104.74	104.316	104.388	0.999315	1.00406
33	105.19	104.806	104.557	1.00239	1.00366
34	104.95	104.852	104.721	1.00126	1.00093
35	104.57	104.633	104.87	0.997743	0.999399
36	103.81	104.189	105.001	0.992261	0.996366
37	104.08	104.156	105.072	0.991283	0.999273
38	104.81	104.72	105.092	0.996464	1.00086
39	105.86	105.713	105.121	1.00563	1.0014
40	106.1	105.956	105.168	1.00749	1.00136
41	106.24	105.933	105.241	1.00657	1.0029
42	105.87	105.437	105.331	1.001	1.00411
43	104.74	105.267	105.415	0.998601	0.994992
44	105.03	105.414	105.486	0.999315	0.996358
45	105.59	105.819	105.567	1.00239	0.997835
46	105.69	105.794	105.661	1.00126	0.999018
47	105.58	105.514	105.753	0.997743	1.00062
48	104.96	105.012	105.831	0.992261	0.999503
49	104.93	105.015	105.938	0.991283	0.999192
50	105.68	105.699	106.075	0.996464	0.999816
51	106.93	106.807	106.21	1.00563	1.00115
52	107.29	107.145	106.348	1.00749	1.00136
53	107.25	107.186	106.486	1.00657	1.0006
54	106.74	106.745	106.639	1.001	0.99995
55	106.44	106.655	106.804	0.998601	0.997986
56	106.6	106.895	106.968	0.999315	0.99724
57	107.26	107.39	107.134	1.00239	0.998794
58	107.35	107.442	107.307	1.00126	0.999145
59	107.22	107.252	107.495	0.997743	0.999698
60	106.99	106.854	107.687	0.992261	1.00128
61	106.87	106.973	107.913	0.991283	0.999041
62	107.68	107.793	108.176	0.996464	0.998949
63	108.9	109.038	108.428	1.00563	0.998733
64	109.48	109.481	108.667	1.00749	0.999993
65	109.57	109.612	108.896	1.00657	0.999619
66	109.03	109.223	109.114	1.001	0.998234
67	109.58	109.179	109.332	0.998601	1.00367
68	109.76	109.479	109.554	0.999315	1.00257
69	110.15	110.04	109.778	1.00239	1.001
70	110.2	110.136	109.998	1.00126	1.00058
71	109.86	109.954	110.203	0.997743	0.999144
72	109.58	109.543	110.397	0.992261	1.00034
73	109.52	109.635	110.599	0.991283	0.998955
74	110.35	110.415	110.807	0.996464	0.999413
75	111.61	111.641	111.016	1.00563	0.999721
76	112.06	112.087	111.254	1.00749	0.999757
77	111.9	112.246	111.512	1.00657	0.996921
78	111.36	111.883	111.771	1.001	0.995329
79	112.09	111.881	112.038	0.998601	1.00187
80	112.24	112.234	112.311	0.999315	1.00005
81	112.7	112.854	112.585	1.00239	0.998637
82	113.36	112.984	112.842	1.00126	1.00333
83	112.9	112.837	113.092	0.997743	1.00056
84	112.74	112.478	113.355	0.992261	1.00233
85	112.77	112.642	113.633	0.991283	1.00113
86	113.66	113.505	113.908	0.996464	1.00136
87	114.87	114.797	114.154	1.00563	1.00064
88	114.97	115.199	114.343	1.00749	0.998011
89	115	115.239	114.486	1.00657	0.99793
90	114.57	114.748	114.633	1.001	0.998449
91	115.54	NA	NA	0.998601	NA
92	115.39	NA	NA	0.999315	NA
93	115.46	NA	NA	1.00239	NA
94	115.13	NA	NA	1.00126	NA
95	114.56	NA	NA	0.997743	NA
96	114.62	NA	NA	0.992261	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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