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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 Apr 2016 10:50:37 +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/25/t1461577884o5j4grnazob7639.htm/, Retrieved Mon, 06 May 2024 01:14:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294680, Retrieved Mon, 06 May 2024 01:14:54 +0000

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Estimated Impact

110

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [] [2016-04-25 09:50:37] [705d764c18df8303d824462e41ab6988] [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=294680&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=294680&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294680&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	109.12	NA	NA	0.986063	NA
2	109.12	NA	NA	0.980665	NA
3	109.73	NA	NA	0.983461	NA
4	112.59	NA	NA	0.996482	NA
5	112.59	NA	NA	1.01524	NA
6	112.29	NA	NA	1.00491	NA
7	113.8	114.686	111.741	1.02635	0.992275
8	114.16	115.016	111.897	1.02787	0.992558
9	112.29	111.864	112.069	0.998175	1.00381
10	112.29	112.945	112.232	1.00635	0.994202
11	110.99	111.579	112.371	0.992946	0.994725
12	110.99	110.447	112.53	0.981487	1.00492
13	110.99	111.119	112.69	0.986063	0.998838
14	110.99	110.63	112.811	0.980665	1.00325
15	111.98	111.093	112.961	0.983461	1.00799
16	114.26	112.835	113.233	0.996482	1.01263
17	114.26	115.339	113.608	1.01524	0.990645
18	114.44	114.542	113.983	1.00491	0.999108
19	115.47	117.345	114.332	1.02635	0.984021
20	115.41	117.878	114.681	1.02787	0.979066
21	114.63	114.779	114.989	0.998175	0.998699
22	116.48	115.943	115.211	1.00635	1.00464
23	115.8	114.823	115.639	0.992946	1.00851
24	115.18	114.16	116.313	0.981487	1.00894
25	115.18	115.335	116.965	0.986063	0.998657
26	115.18	115.329	117.602	0.980665	0.998711
27	115.18	116.319	118.275	0.983461	0.990209
28	116.38	118.485	118.903	0.996482	0.982237
29	122.41	121.247	119.427	1.01524	1.00959
30	122.47	120.528	119.94	1.00491	1.01611
31	123.09	123.643	120.468	1.02635	0.995528
32	123.09	124.369	120.997	1.02787	0.989715
33	123.09	121.303	121.525	0.998175	1.01473
34	123.09	122.913	122.137	1.00635	1.00144
35	121.77	121.738	122.602	0.992946	1.00027
36	121.52	120.536	122.81	0.981487	1.00816
37	121.52	121.427	123.143	0.986063	1.00077
38	121.52	121.256	123.647	0.980665	1.00217
39	121.52	122.025	124.077	0.983461	0.995859
40	124.73	124.018	124.455	0.996482	1.00574
41	125.23	126.68	124.779	1.01524	0.988553
42	124.62	125.494	124.881	1.00491	0.993036
43	128.94	128.13	124.84	1.02635	1.00632
44	129.34	128.184	124.708	1.02787	1.00902
45	127.17	124.277	124.505	0.998175	1.02328
46	128.08	124.99	124.201	1.00635	1.02472
47	124.54	123.135	124.01	0.992946	1.01141
48	121.21	121.708	124.003	0.981487	0.995911
49	120.85	122.19	123.917	0.986063	0.989036
50	119.02	121.368	123.761	0.980665	0.980654
51	119.13	121.439	123.481	0.983461	0.98099
52	119.84	122.746	123.18	0.996482	0.976323
53	125.53	124.984	123.108	1.01524	1.00437
54	124.16	124.006	123.4	1.00491	1.00124
55	127.32	127.253	123.986	1.02635	1.00053
56	127.22	128.209	124.732	1.02787	0.992289
57	122.57	125.363	125.592	0.998175	0.977721
58	125.45	127.277	126.474	1.00635	0.985645
59	125.45	126.25	127.147	0.992946	0.993665
60	127.32	125.346	127.71	0.981487	1.01575
61	128.79	126.65	128.44	0.986063	1.0169
62	128.99	126.85	129.351	0.980665	1.01687
63	129.8	127.948	130.1	0.983461	1.01447
64	130.33	130.1	130.559	0.996482	1.00177
65	131.19	132.957	130.962	1.01524	0.986709
66	132.02	131.71	131.067	1.00491	1.00236
67	136.97	134.503	131.049	1.02635	1.01834
68	139.45	134.817	131.161	1.02787	1.03437
69	128.31	131.092	131.331	0.998175	0.978781
70	130.73	132.537	131.7	1.00635	0.986367
71	129.83	131.348	132.281	0.992946	0.988442
72	125.46	130.235	132.692	0.981487	0.963334
73	130.23	131.173	133.027	0.986063	0.992813
74	130.23	130.838	133.418	0.980665	0.995354
75	132.65	131.663	133.878	0.983461	1.00749
76	136.34	133.889	134.362	0.996482	1.01831
77	139.12	136.775	134.722	1.01524	1.01714
78	133.94	135.958	135.294	1.00491	0.985161
79	143.09	NA	NA	1.02635	NA
80	142.71	NA	NA	1.02787	NA
81	136.09	NA	NA	0.998175	NA
82	134.57	NA	NA	1.00635	NA
83	134.65	NA	NA	0.992946	NA
84	134.35	NA	NA	0.981487	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 109.12 & NA & NA & 0.986063 & NA \tabularnewline
2 & 109.12 & NA & NA & 0.980665 & NA \tabularnewline
3 & 109.73 & NA & NA & 0.983461 & NA \tabularnewline
4 & 112.59 & NA & NA & 0.996482 & NA \tabularnewline
5 & 112.59 & NA & NA & 1.01524 & NA \tabularnewline
6 & 112.29 & NA & NA & 1.00491 & NA \tabularnewline
7 & 113.8 & 114.686 & 111.741 & 1.02635 & 0.992275 \tabularnewline
8 & 114.16 & 115.016 & 111.897 & 1.02787 & 0.992558 \tabularnewline
9 & 112.29 & 111.864 & 112.069 & 0.998175 & 1.00381 \tabularnewline
10 & 112.29 & 112.945 & 112.232 & 1.00635 & 0.994202 \tabularnewline
11 & 110.99 & 111.579 & 112.371 & 0.992946 & 0.994725 \tabularnewline
12 & 110.99 & 110.447 & 112.53 & 0.981487 & 1.00492 \tabularnewline
13 & 110.99 & 111.119 & 112.69 & 0.986063 & 0.998838 \tabularnewline
14 & 110.99 & 110.63 & 112.811 & 0.980665 & 1.00325 \tabularnewline
15 & 111.98 & 111.093 & 112.961 & 0.983461 & 1.00799 \tabularnewline
16 & 114.26 & 112.835 & 113.233 & 0.996482 & 1.01263 \tabularnewline
17 & 114.26 & 115.339 & 113.608 & 1.01524 & 0.990645 \tabularnewline
18 & 114.44 & 114.542 & 113.983 & 1.00491 & 0.999108 \tabularnewline
19 & 115.47 & 117.345 & 114.332 & 1.02635 & 0.984021 \tabularnewline
20 & 115.41 & 117.878 & 114.681 & 1.02787 & 0.979066 \tabularnewline
21 & 114.63 & 114.779 & 114.989 & 0.998175 & 0.998699 \tabularnewline
22 & 116.48 & 115.943 & 115.211 & 1.00635 & 1.00464 \tabularnewline
23 & 115.8 & 114.823 & 115.639 & 0.992946 & 1.00851 \tabularnewline
24 & 115.18 & 114.16 & 116.313 & 0.981487 & 1.00894 \tabularnewline
25 & 115.18 & 115.335 & 116.965 & 0.986063 & 0.998657 \tabularnewline
26 & 115.18 & 115.329 & 117.602 & 0.980665 & 0.998711 \tabularnewline
27 & 115.18 & 116.319 & 118.275 & 0.983461 & 0.990209 \tabularnewline
28 & 116.38 & 118.485 & 118.903 & 0.996482 & 0.982237 \tabularnewline
29 & 122.41 & 121.247 & 119.427 & 1.01524 & 1.00959 \tabularnewline
30 & 122.47 & 120.528 & 119.94 & 1.00491 & 1.01611 \tabularnewline
31 & 123.09 & 123.643 & 120.468 & 1.02635 & 0.995528 \tabularnewline
32 & 123.09 & 124.369 & 120.997 & 1.02787 & 0.989715 \tabularnewline
33 & 123.09 & 121.303 & 121.525 & 0.998175 & 1.01473 \tabularnewline
34 & 123.09 & 122.913 & 122.137 & 1.00635 & 1.00144 \tabularnewline
35 & 121.77 & 121.738 & 122.602 & 0.992946 & 1.00027 \tabularnewline
36 & 121.52 & 120.536 & 122.81 & 0.981487 & 1.00816 \tabularnewline
37 & 121.52 & 121.427 & 123.143 & 0.986063 & 1.00077 \tabularnewline
38 & 121.52 & 121.256 & 123.647 & 0.980665 & 1.00217 \tabularnewline
39 & 121.52 & 122.025 & 124.077 & 0.983461 & 0.995859 \tabularnewline
40 & 124.73 & 124.018 & 124.455 & 0.996482 & 1.00574 \tabularnewline
41 & 125.23 & 126.68 & 124.779 & 1.01524 & 0.988553 \tabularnewline
42 & 124.62 & 125.494 & 124.881 & 1.00491 & 0.993036 \tabularnewline
43 & 128.94 & 128.13 & 124.84 & 1.02635 & 1.00632 \tabularnewline
44 & 129.34 & 128.184 & 124.708 & 1.02787 & 1.00902 \tabularnewline
45 & 127.17 & 124.277 & 124.505 & 0.998175 & 1.02328 \tabularnewline
46 & 128.08 & 124.99 & 124.201 & 1.00635 & 1.02472 \tabularnewline
47 & 124.54 & 123.135 & 124.01 & 0.992946 & 1.01141 \tabularnewline
48 & 121.21 & 121.708 & 124.003 & 0.981487 & 0.995911 \tabularnewline
49 & 120.85 & 122.19 & 123.917 & 0.986063 & 0.989036 \tabularnewline
50 & 119.02 & 121.368 & 123.761 & 0.980665 & 0.980654 \tabularnewline
51 & 119.13 & 121.439 & 123.481 & 0.983461 & 0.98099 \tabularnewline
52 & 119.84 & 122.746 & 123.18 & 0.996482 & 0.976323 \tabularnewline
53 & 125.53 & 124.984 & 123.108 & 1.01524 & 1.00437 \tabularnewline
54 & 124.16 & 124.006 & 123.4 & 1.00491 & 1.00124 \tabularnewline
55 & 127.32 & 127.253 & 123.986 & 1.02635 & 1.00053 \tabularnewline
56 & 127.22 & 128.209 & 124.732 & 1.02787 & 0.992289 \tabularnewline
57 & 122.57 & 125.363 & 125.592 & 0.998175 & 0.977721 \tabularnewline
58 & 125.45 & 127.277 & 126.474 & 1.00635 & 0.985645 \tabularnewline
59 & 125.45 & 126.25 & 127.147 & 0.992946 & 0.993665 \tabularnewline
60 & 127.32 & 125.346 & 127.71 & 0.981487 & 1.01575 \tabularnewline
61 & 128.79 & 126.65 & 128.44 & 0.986063 & 1.0169 \tabularnewline
62 & 128.99 & 126.85 & 129.351 & 0.980665 & 1.01687 \tabularnewline
63 & 129.8 & 127.948 & 130.1 & 0.983461 & 1.01447 \tabularnewline
64 & 130.33 & 130.1 & 130.559 & 0.996482 & 1.00177 \tabularnewline
65 & 131.19 & 132.957 & 130.962 & 1.01524 & 0.986709 \tabularnewline
66 & 132.02 & 131.71 & 131.067 & 1.00491 & 1.00236 \tabularnewline
67 & 136.97 & 134.503 & 131.049 & 1.02635 & 1.01834 \tabularnewline
68 & 139.45 & 134.817 & 131.161 & 1.02787 & 1.03437 \tabularnewline
69 & 128.31 & 131.092 & 131.331 & 0.998175 & 0.978781 \tabularnewline
70 & 130.73 & 132.537 & 131.7 & 1.00635 & 0.986367 \tabularnewline
71 & 129.83 & 131.348 & 132.281 & 0.992946 & 0.988442 \tabularnewline
72 & 125.46 & 130.235 & 132.692 & 0.981487 & 0.963334 \tabularnewline
73 & 130.23 & 131.173 & 133.027 & 0.986063 & 0.992813 \tabularnewline
74 & 130.23 & 130.838 & 133.418 & 0.980665 & 0.995354 \tabularnewline
75 & 132.65 & 131.663 & 133.878 & 0.983461 & 1.00749 \tabularnewline
76 & 136.34 & 133.889 & 134.362 & 0.996482 & 1.01831 \tabularnewline
77 & 139.12 & 136.775 & 134.722 & 1.01524 & 1.01714 \tabularnewline
78 & 133.94 & 135.958 & 135.294 & 1.00491 & 0.985161 \tabularnewline
79 & 143.09 & NA & NA & 1.02635 & NA \tabularnewline
80 & 142.71 & NA & NA & 1.02787 & NA \tabularnewline
81 & 136.09 & NA & NA & 0.998175 & NA \tabularnewline
82 & 134.57 & NA & NA & 1.00635 & NA \tabularnewline
83 & 134.65 & NA & NA & 0.992946 & NA \tabularnewline
84 & 134.35 & NA & NA & 0.981487 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294680&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]109.12[/C][C]NA[/C][C]NA[/C][C]0.986063[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]109.12[/C][C]NA[/C][C]NA[/C][C]0.980665[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]109.73[/C][C]NA[/C][C]NA[/C][C]0.983461[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]112.59[/C][C]NA[/C][C]NA[/C][C]0.996482[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]112.59[/C][C]NA[/C][C]NA[/C][C]1.01524[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]112.29[/C][C]NA[/C][C]NA[/C][C]1.00491[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]113.8[/C][C]114.686[/C][C]111.741[/C][C]1.02635[/C][C]0.992275[/C][/ROW]
[ROW][C]8[/C][C]114.16[/C][C]115.016[/C][C]111.897[/C][C]1.02787[/C][C]0.992558[/C][/ROW]
[ROW][C]9[/C][C]112.29[/C][C]111.864[/C][C]112.069[/C][C]0.998175[/C][C]1.00381[/C][/ROW]
[ROW][C]10[/C][C]112.29[/C][C]112.945[/C][C]112.232[/C][C]1.00635[/C][C]0.994202[/C][/ROW]
[ROW][C]11[/C][C]110.99[/C][C]111.579[/C][C]112.371[/C][C]0.992946[/C][C]0.994725[/C][/ROW]
[ROW][C]12[/C][C]110.99[/C][C]110.447[/C][C]112.53[/C][C]0.981487[/C][C]1.00492[/C][/ROW]
[ROW][C]13[/C][C]110.99[/C][C]111.119[/C][C]112.69[/C][C]0.986063[/C][C]0.998838[/C][/ROW]
[ROW][C]14[/C][C]110.99[/C][C]110.63[/C][C]112.811[/C][C]0.980665[/C][C]1.00325[/C][/ROW]
[ROW][C]15[/C][C]111.98[/C][C]111.093[/C][C]112.961[/C][C]0.983461[/C][C]1.00799[/C][/ROW]
[ROW][C]16[/C][C]114.26[/C][C]112.835[/C][C]113.233[/C][C]0.996482[/C][C]1.01263[/C][/ROW]
[ROW][C]17[/C][C]114.26[/C][C]115.339[/C][C]113.608[/C][C]1.01524[/C][C]0.990645[/C][/ROW]
[ROW][C]18[/C][C]114.44[/C][C]114.542[/C][C]113.983[/C][C]1.00491[/C][C]0.999108[/C][/ROW]
[ROW][C]19[/C][C]115.47[/C][C]117.345[/C][C]114.332[/C][C]1.02635[/C][C]0.984021[/C][/ROW]
[ROW][C]20[/C][C]115.41[/C][C]117.878[/C][C]114.681[/C][C]1.02787[/C][C]0.979066[/C][/ROW]
[ROW][C]21[/C][C]114.63[/C][C]114.779[/C][C]114.989[/C][C]0.998175[/C][C]0.998699[/C][/ROW]
[ROW][C]22[/C][C]116.48[/C][C]115.943[/C][C]115.211[/C][C]1.00635[/C][C]1.00464[/C][/ROW]
[ROW][C]23[/C][C]115.8[/C][C]114.823[/C][C]115.639[/C][C]0.992946[/C][C]1.00851[/C][/ROW]
[ROW][C]24[/C][C]115.18[/C][C]114.16[/C][C]116.313[/C][C]0.981487[/C][C]1.00894[/C][/ROW]
[ROW][C]25[/C][C]115.18[/C][C]115.335[/C][C]116.965[/C][C]0.986063[/C][C]0.998657[/C][/ROW]
[ROW][C]26[/C][C]115.18[/C][C]115.329[/C][C]117.602[/C][C]0.980665[/C][C]0.998711[/C][/ROW]
[ROW][C]27[/C][C]115.18[/C][C]116.319[/C][C]118.275[/C][C]0.983461[/C][C]0.990209[/C][/ROW]
[ROW][C]28[/C][C]116.38[/C][C]118.485[/C][C]118.903[/C][C]0.996482[/C][C]0.982237[/C][/ROW]
[ROW][C]29[/C][C]122.41[/C][C]121.247[/C][C]119.427[/C][C]1.01524[/C][C]1.00959[/C][/ROW]
[ROW][C]30[/C][C]122.47[/C][C]120.528[/C][C]119.94[/C][C]1.00491[/C][C]1.01611[/C][/ROW]
[ROW][C]31[/C][C]123.09[/C][C]123.643[/C][C]120.468[/C][C]1.02635[/C][C]0.995528[/C][/ROW]
[ROW][C]32[/C][C]123.09[/C][C]124.369[/C][C]120.997[/C][C]1.02787[/C][C]0.989715[/C][/ROW]
[ROW][C]33[/C][C]123.09[/C][C]121.303[/C][C]121.525[/C][C]0.998175[/C][C]1.01473[/C][/ROW]
[ROW][C]34[/C][C]123.09[/C][C]122.913[/C][C]122.137[/C][C]1.00635[/C][C]1.00144[/C][/ROW]
[ROW][C]35[/C][C]121.77[/C][C]121.738[/C][C]122.602[/C][C]0.992946[/C][C]1.00027[/C][/ROW]
[ROW][C]36[/C][C]121.52[/C][C]120.536[/C][C]122.81[/C][C]0.981487[/C][C]1.00816[/C][/ROW]
[ROW][C]37[/C][C]121.52[/C][C]121.427[/C][C]123.143[/C][C]0.986063[/C][C]1.00077[/C][/ROW]
[ROW][C]38[/C][C]121.52[/C][C]121.256[/C][C]123.647[/C][C]0.980665[/C][C]1.00217[/C][/ROW]
[ROW][C]39[/C][C]121.52[/C][C]122.025[/C][C]124.077[/C][C]0.983461[/C][C]0.995859[/C][/ROW]
[ROW][C]40[/C][C]124.73[/C][C]124.018[/C][C]124.455[/C][C]0.996482[/C][C]1.00574[/C][/ROW]
[ROW][C]41[/C][C]125.23[/C][C]126.68[/C][C]124.779[/C][C]1.01524[/C][C]0.988553[/C][/ROW]
[ROW][C]42[/C][C]124.62[/C][C]125.494[/C][C]124.881[/C][C]1.00491[/C][C]0.993036[/C][/ROW]
[ROW][C]43[/C][C]128.94[/C][C]128.13[/C][C]124.84[/C][C]1.02635[/C][C]1.00632[/C][/ROW]
[ROW][C]44[/C][C]129.34[/C][C]128.184[/C][C]124.708[/C][C]1.02787[/C][C]1.00902[/C][/ROW]
[ROW][C]45[/C][C]127.17[/C][C]124.277[/C][C]124.505[/C][C]0.998175[/C][C]1.02328[/C][/ROW]
[ROW][C]46[/C][C]128.08[/C][C]124.99[/C][C]124.201[/C][C]1.00635[/C][C]1.02472[/C][/ROW]
[ROW][C]47[/C][C]124.54[/C][C]123.135[/C][C]124.01[/C][C]0.992946[/C][C]1.01141[/C][/ROW]
[ROW][C]48[/C][C]121.21[/C][C]121.708[/C][C]124.003[/C][C]0.981487[/C][C]0.995911[/C][/ROW]
[ROW][C]49[/C][C]120.85[/C][C]122.19[/C][C]123.917[/C][C]0.986063[/C][C]0.989036[/C][/ROW]
[ROW][C]50[/C][C]119.02[/C][C]121.368[/C][C]123.761[/C][C]0.980665[/C][C]0.980654[/C][/ROW]
[ROW][C]51[/C][C]119.13[/C][C]121.439[/C][C]123.481[/C][C]0.983461[/C][C]0.98099[/C][/ROW]
[ROW][C]52[/C][C]119.84[/C][C]122.746[/C][C]123.18[/C][C]0.996482[/C][C]0.976323[/C][/ROW]
[ROW][C]53[/C][C]125.53[/C][C]124.984[/C][C]123.108[/C][C]1.01524[/C][C]1.00437[/C][/ROW]
[ROW][C]54[/C][C]124.16[/C][C]124.006[/C][C]123.4[/C][C]1.00491[/C][C]1.00124[/C][/ROW]
[ROW][C]55[/C][C]127.32[/C][C]127.253[/C][C]123.986[/C][C]1.02635[/C][C]1.00053[/C][/ROW]
[ROW][C]56[/C][C]127.22[/C][C]128.209[/C][C]124.732[/C][C]1.02787[/C][C]0.992289[/C][/ROW]
[ROW][C]57[/C][C]122.57[/C][C]125.363[/C][C]125.592[/C][C]0.998175[/C][C]0.977721[/C][/ROW]
[ROW][C]58[/C][C]125.45[/C][C]127.277[/C][C]126.474[/C][C]1.00635[/C][C]0.985645[/C][/ROW]
[ROW][C]59[/C][C]125.45[/C][C]126.25[/C][C]127.147[/C][C]0.992946[/C][C]0.993665[/C][/ROW]
[ROW][C]60[/C][C]127.32[/C][C]125.346[/C][C]127.71[/C][C]0.981487[/C][C]1.01575[/C][/ROW]
[ROW][C]61[/C][C]128.79[/C][C]126.65[/C][C]128.44[/C][C]0.986063[/C][C]1.0169[/C][/ROW]
[ROW][C]62[/C][C]128.99[/C][C]126.85[/C][C]129.351[/C][C]0.980665[/C][C]1.01687[/C][/ROW]
[ROW][C]63[/C][C]129.8[/C][C]127.948[/C][C]130.1[/C][C]0.983461[/C][C]1.01447[/C][/ROW]
[ROW][C]64[/C][C]130.33[/C][C]130.1[/C][C]130.559[/C][C]0.996482[/C][C]1.00177[/C][/ROW]
[ROW][C]65[/C][C]131.19[/C][C]132.957[/C][C]130.962[/C][C]1.01524[/C][C]0.986709[/C][/ROW]
[ROW][C]66[/C][C]132.02[/C][C]131.71[/C][C]131.067[/C][C]1.00491[/C][C]1.00236[/C][/ROW]
[ROW][C]67[/C][C]136.97[/C][C]134.503[/C][C]131.049[/C][C]1.02635[/C][C]1.01834[/C][/ROW]
[ROW][C]68[/C][C]139.45[/C][C]134.817[/C][C]131.161[/C][C]1.02787[/C][C]1.03437[/C][/ROW]
[ROW][C]69[/C][C]128.31[/C][C]131.092[/C][C]131.331[/C][C]0.998175[/C][C]0.978781[/C][/ROW]
[ROW][C]70[/C][C]130.73[/C][C]132.537[/C][C]131.7[/C][C]1.00635[/C][C]0.986367[/C][/ROW]
[ROW][C]71[/C][C]129.83[/C][C]131.348[/C][C]132.281[/C][C]0.992946[/C][C]0.988442[/C][/ROW]
[ROW][C]72[/C][C]125.46[/C][C]130.235[/C][C]132.692[/C][C]0.981487[/C][C]0.963334[/C][/ROW]
[ROW][C]73[/C][C]130.23[/C][C]131.173[/C][C]133.027[/C][C]0.986063[/C][C]0.992813[/C][/ROW]
[ROW][C]74[/C][C]130.23[/C][C]130.838[/C][C]133.418[/C][C]0.980665[/C][C]0.995354[/C][/ROW]
[ROW][C]75[/C][C]132.65[/C][C]131.663[/C][C]133.878[/C][C]0.983461[/C][C]1.00749[/C][/ROW]
[ROW][C]76[/C][C]136.34[/C][C]133.889[/C][C]134.362[/C][C]0.996482[/C][C]1.01831[/C][/ROW]
[ROW][C]77[/C][C]139.12[/C][C]136.775[/C][C]134.722[/C][C]1.01524[/C][C]1.01714[/C][/ROW]
[ROW][C]78[/C][C]133.94[/C][C]135.958[/C][C]135.294[/C][C]1.00491[/C][C]0.985161[/C][/ROW]
[ROW][C]79[/C][C]143.09[/C][C]NA[/C][C]NA[/C][C]1.02635[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]142.71[/C][C]NA[/C][C]NA[/C][C]1.02787[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]136.09[/C][C]NA[/C][C]NA[/C][C]0.998175[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]134.57[/C][C]NA[/C][C]NA[/C][C]1.00635[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]134.65[/C][C]NA[/C][C]NA[/C][C]0.992946[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]134.35[/C][C]NA[/C][C]NA[/C][C]0.981487[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294680&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294680&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	109.12	NA	NA	0.986063	NA
2	109.12	NA	NA	0.980665	NA
3	109.73	NA	NA	0.983461	NA
4	112.59	NA	NA	0.996482	NA
5	112.59	NA	NA	1.01524	NA
6	112.29	NA	NA	1.00491	NA
7	113.8	114.686	111.741	1.02635	0.992275
8	114.16	115.016	111.897	1.02787	0.992558
9	112.29	111.864	112.069	0.998175	1.00381
10	112.29	112.945	112.232	1.00635	0.994202
11	110.99	111.579	112.371	0.992946	0.994725
12	110.99	110.447	112.53	0.981487	1.00492
13	110.99	111.119	112.69	0.986063	0.998838
14	110.99	110.63	112.811	0.980665	1.00325
15	111.98	111.093	112.961	0.983461	1.00799
16	114.26	112.835	113.233	0.996482	1.01263
17	114.26	115.339	113.608	1.01524	0.990645
18	114.44	114.542	113.983	1.00491	0.999108
19	115.47	117.345	114.332	1.02635	0.984021
20	115.41	117.878	114.681	1.02787	0.979066
21	114.63	114.779	114.989	0.998175	0.998699
22	116.48	115.943	115.211	1.00635	1.00464
23	115.8	114.823	115.639	0.992946	1.00851
24	115.18	114.16	116.313	0.981487	1.00894
25	115.18	115.335	116.965	0.986063	0.998657
26	115.18	115.329	117.602	0.980665	0.998711
27	115.18	116.319	118.275	0.983461	0.990209
28	116.38	118.485	118.903	0.996482	0.982237
29	122.41	121.247	119.427	1.01524	1.00959
30	122.47	120.528	119.94	1.00491	1.01611
31	123.09	123.643	120.468	1.02635	0.995528
32	123.09	124.369	120.997	1.02787	0.989715
33	123.09	121.303	121.525	0.998175	1.01473
34	123.09	122.913	122.137	1.00635	1.00144
35	121.77	121.738	122.602	0.992946	1.00027
36	121.52	120.536	122.81	0.981487	1.00816
37	121.52	121.427	123.143	0.986063	1.00077
38	121.52	121.256	123.647	0.980665	1.00217
39	121.52	122.025	124.077	0.983461	0.995859
40	124.73	124.018	124.455	0.996482	1.00574
41	125.23	126.68	124.779	1.01524	0.988553
42	124.62	125.494	124.881	1.00491	0.993036
43	128.94	128.13	124.84	1.02635	1.00632
44	129.34	128.184	124.708	1.02787	1.00902
45	127.17	124.277	124.505	0.998175	1.02328
46	128.08	124.99	124.201	1.00635	1.02472
47	124.54	123.135	124.01	0.992946	1.01141
48	121.21	121.708	124.003	0.981487	0.995911
49	120.85	122.19	123.917	0.986063	0.989036
50	119.02	121.368	123.761	0.980665	0.980654
51	119.13	121.439	123.481	0.983461	0.98099
52	119.84	122.746	123.18	0.996482	0.976323
53	125.53	124.984	123.108	1.01524	1.00437
54	124.16	124.006	123.4	1.00491	1.00124
55	127.32	127.253	123.986	1.02635	1.00053
56	127.22	128.209	124.732	1.02787	0.992289
57	122.57	125.363	125.592	0.998175	0.977721
58	125.45	127.277	126.474	1.00635	0.985645
59	125.45	126.25	127.147	0.992946	0.993665
60	127.32	125.346	127.71	0.981487	1.01575
61	128.79	126.65	128.44	0.986063	1.0169
62	128.99	126.85	129.351	0.980665	1.01687
63	129.8	127.948	130.1	0.983461	1.01447
64	130.33	130.1	130.559	0.996482	1.00177
65	131.19	132.957	130.962	1.01524	0.986709
66	132.02	131.71	131.067	1.00491	1.00236
67	136.97	134.503	131.049	1.02635	1.01834
68	139.45	134.817	131.161	1.02787	1.03437
69	128.31	131.092	131.331	0.998175	0.978781
70	130.73	132.537	131.7	1.00635	0.986367
71	129.83	131.348	132.281	0.992946	0.988442
72	125.46	130.235	132.692	0.981487	0.963334
73	130.23	131.173	133.027	0.986063	0.992813
74	130.23	130.838	133.418	0.980665	0.995354
75	132.65	131.663	133.878	0.983461	1.00749
76	136.34	133.889	134.362	0.996482	1.01831
77	139.12	136.775	134.722	1.01524	1.01714
78	133.94	135.958	135.294	1.00491	0.985161
79	143.09	NA	NA	1.02635	NA
80	142.71	NA	NA	1.02787	NA
81	136.09	NA	NA	0.998175	NA
82	134.57	NA	NA	1.00635	NA
83	134.65	NA	NA	0.992946	NA
84	134.35	NA	NA	0.981487	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 <- '12'
par1 <- 'multiplicative'
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