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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 25 Nov 2015 14:23:54 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Nov/25/t144846158326yxe7jyatnsfjy.htm/, Retrieved Tue, 21 May 2024 19:39:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284131, Retrieved Tue, 21 May 2024 19:39:01 +0000

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Estimated Impact

100

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-       [Classical Decomposition] [] [2015-11-25 14:23:54] [bd97b182bc123d4050d70da6fa7efb72] [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=284131&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=284131&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284131&T=0

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.41	NA	NA	1.00332	NA
2	98.94	NA	NA	1.00471	NA
3	99.09	NA	NA	1.00316	NA
4	100.45	NA	NA	1.00076	NA
5	101.99	NA	NA	1.00307	NA
6	102.35	NA	NA	0.998051	NA
7	102.69	101.358	101.734	0.996306	1.01314
8	102.6	101.709	102.15	0.995678	1.00876
9	102.62	102.182	102.522	0.996685	1.00428
10	102.73	102.552	102.826	0.99734	1.00173
11	102.74	102.83	103.011	0.998245	0.999121
12	103.45	103.403	103.128	1.00267	1.00045
13	103.9	103.571	103.228	1.00332	1.00318
14	103.45	103.812	103.325	1.00471	0.996514
15	103.5	103.747	103.42	1.00316	0.997615
16	103.33	103.608	103.528	1.00076	0.997321
17	103.56	103.983	103.665	1.00307	0.995928
18	103.58	103.582	103.785	0.998051	0.999978
19	103.86	103.476	103.86	0.996306	1.00371
20	103.77	103.507	103.956	0.995678	1.00255
21	103.73	103.737	104.082	0.996685	0.999932
22	104.21	103.962	104.24	0.99734	1.00238
23	104.55	104.275	104.458	0.998245	1.00264
24	104.5	104.966	104.687	1.00267	0.99556
25	104.66	105.26	104.911	1.00332	0.9943
26	104.99	105.645	105.15	1.00471	0.9938
27	104.99	105.727	105.394	1.00316	0.993029
28	105.62	105.695	105.614	1.00076	0.999295
29	106.52	106.141	105.816	1.00307	1.00357
30	106.1	105.814	106.021	0.998051	1.0027
31	106.73	105.834	106.226	0.996306	1.00847
32	106.63	106.007	106.467	0.995678	1.00587
33	106.72	106.381	106.735	0.996685	1.00319
34	106.5	106.683	106.968	0.99734	0.998285
35	107.12	106.986	107.174	0.998245	1.00125
36	106.84	107.723	107.436	1.00267	0.991804
37	107.25	108.071	107.713	1.00332	0.992399
38	108.19	108.472	107.964	1.00471	0.997396
39	108.21	108.539	108.197	1.00316	0.996971
40	107.98	108.47	108.387	1.00076	0.995483
41	109.12	108.778	108.445	1.00307	1.00314
42	109.79	108.225	108.436	0.998051	1.01446
43	109.69	108	108.4	0.996306	1.01565
44	109.69	107.893	108.361	0.995678	1.01666
45	109.24	108.125	108.484	0.996685	1.01032
46	108.55	108.452	108.741	0.99734	1.00091
47	106.47	108.75	108.942	0.998245	0.97903
48	107.27	109.155	108.864	1.00267	0.982734
49	105.95	108.96	108.599	1.00332	0.972373
50	108.55	108.797	108.287	1.00471	0.997731
51	110.81	108.29	107.949	1.00316	1.02327
52	111.54	107.669	107.586	1.00076	1.03596
53	110.38	107.719	107.389	1.00307	1.02471
54	106.67	107.237	107.446	0.998051	0.994714
55	106.45	107.285	107.683	0.996306	0.992216
56	105.44	107.321	107.787	0.995678	0.982471
57	105.37	107.045	107.401	0.996685	0.984354
58	103.72	106.386	106.67	0.99734	0.974938
59	106.57	105.707	105.892	0.998245	1.00817
60	108.54	105.578	105.297	1.00267	1.02805
61	110.36	105.15	104.802	1.00332	1.04955
62	106.64	104.819	104.328	1.00471	1.01737
63	103.45	104.192	103.864	1.00316	0.992877
64	101.36	103.523	103.444	1.00076	0.979103
65	101.9	103.278	102.962	1.00307	0.986658
66	100.86	102.073	102.272	0.998051	0.988119
67	100.37	101.057	101.431	0.996306	0.993206
68	100.16	100.255	100.69	0.995678	0.99905
69	99.5	99.9214	100.254	0.996685	0.995783
70	99.52	99.7801	100.046	0.99734	0.997393
71	99.2	99.7284	99.9038	0.998245	0.994702
72	99.35	100.042	99.7762	1.00267	0.993078
73	99.37	100.018	99.6871	1.00332	0.993516
74	99.85	100.074	99.605	1.00471	0.997762
75	99.76	99.9011	99.5862	1.00316	0.998587
76	100.07	99.6816	99.6054	1.00076	1.0039
77	99.77	99.9244	99.6187	1.00307	0.998455
78	99.93	99.4375	99.6317	0.998051	1.00495
79	99.16	99.2657	99.6338	0.996306	0.998935
80	99.4	99.1779	99.6083	0.995678	1.00224
81	99.81	99.2329	99.5629	0.996685	1.00582
82	99.67	99.1929	99.4575	0.99734	1.00481
83	99.37	99.1744	99.3488	0.998245	1.00197
84	99.49	99.5503	99.2854	1.00267	0.999394
85	99.28	99.506	99.1762	1.00332	0.997729
86	99.33	99.5301	99.0637	1.00471	0.997989
87	99.19	99.359	99.0458	1.00316	0.998299
88	98.11	99.2896	99.2138	1.00076	0.988119
89	99.12	99.819	99.5138	1.00307	0.992997
90	99.06	99.6392	99.8338	0.998051	0.994187
91	97.41	99.7767	100.147	0.996306	0.97628
92	98.45	100.05	100.485	0.995678	0.984005
93	100.33	100.538	100.872	0.996685	0.997934
94	103.18	101.043	101.312	0.99734	1.02115
95	103.06	101.565	101.743	0.998245	1.01472
96	103.48	102.402	102.13	1.00267	1.01053
97	102.8	102.948	102.607	1.00332	0.998564
98	103.92	103.605	103.119	1.00471	1.00304
99	103.9	103.801	103.474	1.00316	1.00095
100	103.96	103.708	103.629	1.00076	1.00243
101	103.62	104.021	103.703	1.00307	0.996145
102	103.83	103.572	103.774	0.998051	1.00249
103	104.09	NA	NA	0.996306	NA
104	104.07	NA	NA	0.995678	NA
105	103.22	NA	NA	0.996685	NA
106	104.01	NA	NA	0.99734	NA
107	104.01	NA	NA	0.998245	NA
108	104.24	NA	NA	1.00267	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 98.41 & NA & NA & 1.00332 & NA \tabularnewline
2 & 98.94 & NA & NA & 1.00471 & NA \tabularnewline
3 & 99.09 & NA & NA & 1.00316 & NA \tabularnewline
4 & 100.45 & NA & NA & 1.00076 & NA \tabularnewline
5 & 101.99 & NA & NA & 1.00307 & NA \tabularnewline
6 & 102.35 & NA & NA & 0.998051 & NA \tabularnewline
7 & 102.69 & 101.358 & 101.734 & 0.996306 & 1.01314 \tabularnewline
8 & 102.6 & 101.709 & 102.15 & 0.995678 & 1.00876 \tabularnewline
9 & 102.62 & 102.182 & 102.522 & 0.996685 & 1.00428 \tabularnewline
10 & 102.73 & 102.552 & 102.826 & 0.99734 & 1.00173 \tabularnewline
11 & 102.74 & 102.83 & 103.011 & 0.998245 & 0.999121 \tabularnewline
12 & 103.45 & 103.403 & 103.128 & 1.00267 & 1.00045 \tabularnewline
13 & 103.9 & 103.571 & 103.228 & 1.00332 & 1.00318 \tabularnewline
14 & 103.45 & 103.812 & 103.325 & 1.00471 & 0.996514 \tabularnewline
15 & 103.5 & 103.747 & 103.42 & 1.00316 & 0.997615 \tabularnewline
16 & 103.33 & 103.608 & 103.528 & 1.00076 & 0.997321 \tabularnewline
17 & 103.56 & 103.983 & 103.665 & 1.00307 & 0.995928 \tabularnewline
18 & 103.58 & 103.582 & 103.785 & 0.998051 & 0.999978 \tabularnewline
19 & 103.86 & 103.476 & 103.86 & 0.996306 & 1.00371 \tabularnewline
20 & 103.77 & 103.507 & 103.956 & 0.995678 & 1.00255 \tabularnewline
21 & 103.73 & 103.737 & 104.082 & 0.996685 & 0.999932 \tabularnewline
22 & 104.21 & 103.962 & 104.24 & 0.99734 & 1.00238 \tabularnewline
23 & 104.55 & 104.275 & 104.458 & 0.998245 & 1.00264 \tabularnewline
24 & 104.5 & 104.966 & 104.687 & 1.00267 & 0.99556 \tabularnewline
25 & 104.66 & 105.26 & 104.911 & 1.00332 & 0.9943 \tabularnewline
26 & 104.99 & 105.645 & 105.15 & 1.00471 & 0.9938 \tabularnewline
27 & 104.99 & 105.727 & 105.394 & 1.00316 & 0.993029 \tabularnewline
28 & 105.62 & 105.695 & 105.614 & 1.00076 & 0.999295 \tabularnewline
29 & 106.52 & 106.141 & 105.816 & 1.00307 & 1.00357 \tabularnewline
30 & 106.1 & 105.814 & 106.021 & 0.998051 & 1.0027 \tabularnewline
31 & 106.73 & 105.834 & 106.226 & 0.996306 & 1.00847 \tabularnewline
32 & 106.63 & 106.007 & 106.467 & 0.995678 & 1.00587 \tabularnewline
33 & 106.72 & 106.381 & 106.735 & 0.996685 & 1.00319 \tabularnewline
34 & 106.5 & 106.683 & 106.968 & 0.99734 & 0.998285 \tabularnewline
35 & 107.12 & 106.986 & 107.174 & 0.998245 & 1.00125 \tabularnewline
36 & 106.84 & 107.723 & 107.436 & 1.00267 & 0.991804 \tabularnewline
37 & 107.25 & 108.071 & 107.713 & 1.00332 & 0.992399 \tabularnewline
38 & 108.19 & 108.472 & 107.964 & 1.00471 & 0.997396 \tabularnewline
39 & 108.21 & 108.539 & 108.197 & 1.00316 & 0.996971 \tabularnewline
40 & 107.98 & 108.47 & 108.387 & 1.00076 & 0.995483 \tabularnewline
41 & 109.12 & 108.778 & 108.445 & 1.00307 & 1.00314 \tabularnewline
42 & 109.79 & 108.225 & 108.436 & 0.998051 & 1.01446 \tabularnewline
43 & 109.69 & 108 & 108.4 & 0.996306 & 1.01565 \tabularnewline
44 & 109.69 & 107.893 & 108.361 & 0.995678 & 1.01666 \tabularnewline
45 & 109.24 & 108.125 & 108.484 & 0.996685 & 1.01032 \tabularnewline
46 & 108.55 & 108.452 & 108.741 & 0.99734 & 1.00091 \tabularnewline
47 & 106.47 & 108.75 & 108.942 & 0.998245 & 0.97903 \tabularnewline
48 & 107.27 & 109.155 & 108.864 & 1.00267 & 0.982734 \tabularnewline
49 & 105.95 & 108.96 & 108.599 & 1.00332 & 0.972373 \tabularnewline
50 & 108.55 & 108.797 & 108.287 & 1.00471 & 0.997731 \tabularnewline
51 & 110.81 & 108.29 & 107.949 & 1.00316 & 1.02327 \tabularnewline
52 & 111.54 & 107.669 & 107.586 & 1.00076 & 1.03596 \tabularnewline
53 & 110.38 & 107.719 & 107.389 & 1.00307 & 1.02471 \tabularnewline
54 & 106.67 & 107.237 & 107.446 & 0.998051 & 0.994714 \tabularnewline
55 & 106.45 & 107.285 & 107.683 & 0.996306 & 0.992216 \tabularnewline
56 & 105.44 & 107.321 & 107.787 & 0.995678 & 0.982471 \tabularnewline
57 & 105.37 & 107.045 & 107.401 & 0.996685 & 0.984354 \tabularnewline
58 & 103.72 & 106.386 & 106.67 & 0.99734 & 0.974938 \tabularnewline
59 & 106.57 & 105.707 & 105.892 & 0.998245 & 1.00817 \tabularnewline
60 & 108.54 & 105.578 & 105.297 & 1.00267 & 1.02805 \tabularnewline
61 & 110.36 & 105.15 & 104.802 & 1.00332 & 1.04955 \tabularnewline
62 & 106.64 & 104.819 & 104.328 & 1.00471 & 1.01737 \tabularnewline
63 & 103.45 & 104.192 & 103.864 & 1.00316 & 0.992877 \tabularnewline
64 & 101.36 & 103.523 & 103.444 & 1.00076 & 0.979103 \tabularnewline
65 & 101.9 & 103.278 & 102.962 & 1.00307 & 0.986658 \tabularnewline
66 & 100.86 & 102.073 & 102.272 & 0.998051 & 0.988119 \tabularnewline
67 & 100.37 & 101.057 & 101.431 & 0.996306 & 0.993206 \tabularnewline
68 & 100.16 & 100.255 & 100.69 & 0.995678 & 0.99905 \tabularnewline
69 & 99.5 & 99.9214 & 100.254 & 0.996685 & 0.995783 \tabularnewline
70 & 99.52 & 99.7801 & 100.046 & 0.99734 & 0.997393 \tabularnewline
71 & 99.2 & 99.7284 & 99.9038 & 0.998245 & 0.994702 \tabularnewline
72 & 99.35 & 100.042 & 99.7762 & 1.00267 & 0.993078 \tabularnewline
73 & 99.37 & 100.018 & 99.6871 & 1.00332 & 0.993516 \tabularnewline
74 & 99.85 & 100.074 & 99.605 & 1.00471 & 0.997762 \tabularnewline
75 & 99.76 & 99.9011 & 99.5862 & 1.00316 & 0.998587 \tabularnewline
76 & 100.07 & 99.6816 & 99.6054 & 1.00076 & 1.0039 \tabularnewline
77 & 99.77 & 99.9244 & 99.6187 & 1.00307 & 0.998455 \tabularnewline
78 & 99.93 & 99.4375 & 99.6317 & 0.998051 & 1.00495 \tabularnewline
79 & 99.16 & 99.2657 & 99.6338 & 0.996306 & 0.998935 \tabularnewline
80 & 99.4 & 99.1779 & 99.6083 & 0.995678 & 1.00224 \tabularnewline
81 & 99.81 & 99.2329 & 99.5629 & 0.996685 & 1.00582 \tabularnewline
82 & 99.67 & 99.1929 & 99.4575 & 0.99734 & 1.00481 \tabularnewline
83 & 99.37 & 99.1744 & 99.3488 & 0.998245 & 1.00197 \tabularnewline
84 & 99.49 & 99.5503 & 99.2854 & 1.00267 & 0.999394 \tabularnewline
85 & 99.28 & 99.506 & 99.1762 & 1.00332 & 0.997729 \tabularnewline
86 & 99.33 & 99.5301 & 99.0637 & 1.00471 & 0.997989 \tabularnewline
87 & 99.19 & 99.359 & 99.0458 & 1.00316 & 0.998299 \tabularnewline
88 & 98.11 & 99.2896 & 99.2138 & 1.00076 & 0.988119 \tabularnewline
89 & 99.12 & 99.819 & 99.5138 & 1.00307 & 0.992997 \tabularnewline
90 & 99.06 & 99.6392 & 99.8338 & 0.998051 & 0.994187 \tabularnewline
91 & 97.41 & 99.7767 & 100.147 & 0.996306 & 0.97628 \tabularnewline
92 & 98.45 & 100.05 & 100.485 & 0.995678 & 0.984005 \tabularnewline
93 & 100.33 & 100.538 & 100.872 & 0.996685 & 0.997934 \tabularnewline
94 & 103.18 & 101.043 & 101.312 & 0.99734 & 1.02115 \tabularnewline
95 & 103.06 & 101.565 & 101.743 & 0.998245 & 1.01472 \tabularnewline
96 & 103.48 & 102.402 & 102.13 & 1.00267 & 1.01053 \tabularnewline
97 & 102.8 & 102.948 & 102.607 & 1.00332 & 0.998564 \tabularnewline
98 & 103.92 & 103.605 & 103.119 & 1.00471 & 1.00304 \tabularnewline
99 & 103.9 & 103.801 & 103.474 & 1.00316 & 1.00095 \tabularnewline
100 & 103.96 & 103.708 & 103.629 & 1.00076 & 1.00243 \tabularnewline
101 & 103.62 & 104.021 & 103.703 & 1.00307 & 0.996145 \tabularnewline
102 & 103.83 & 103.572 & 103.774 & 0.998051 & 1.00249 \tabularnewline
103 & 104.09 & NA & NA & 0.996306 & NA \tabularnewline
104 & 104.07 & NA & NA & 0.995678 & NA \tabularnewline
105 & 103.22 & NA & NA & 0.996685 & NA \tabularnewline
106 & 104.01 & NA & NA & 0.99734 & NA \tabularnewline
107 & 104.01 & NA & NA & 0.998245 & NA \tabularnewline
108 & 104.24 & NA & NA & 1.00267 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284131&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]98.41[/C][C]NA[/C][C]NA[/C][C]1.00332[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]98.94[/C][C]NA[/C][C]NA[/C][C]1.00471[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]99.09[/C][C]NA[/C][C]NA[/C][C]1.00316[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]100.45[/C][C]NA[/C][C]NA[/C][C]1.00076[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]101.99[/C][C]NA[/C][C]NA[/C][C]1.00307[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]102.35[/C][C]NA[/C][C]NA[/C][C]0.998051[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]102.69[/C][C]101.358[/C][C]101.734[/C][C]0.996306[/C][C]1.01314[/C][/ROW]
[ROW][C]8[/C][C]102.6[/C][C]101.709[/C][C]102.15[/C][C]0.995678[/C][C]1.00876[/C][/ROW]
[ROW][C]9[/C][C]102.62[/C][C]102.182[/C][C]102.522[/C][C]0.996685[/C][C]1.00428[/C][/ROW]
[ROW][C]10[/C][C]102.73[/C][C]102.552[/C][C]102.826[/C][C]0.99734[/C][C]1.00173[/C][/ROW]
[ROW][C]11[/C][C]102.74[/C][C]102.83[/C][C]103.011[/C][C]0.998245[/C][C]0.999121[/C][/ROW]
[ROW][C]12[/C][C]103.45[/C][C]103.403[/C][C]103.128[/C][C]1.00267[/C][C]1.00045[/C][/ROW]
[ROW][C]13[/C][C]103.9[/C][C]103.571[/C][C]103.228[/C][C]1.00332[/C][C]1.00318[/C][/ROW]
[ROW][C]14[/C][C]103.45[/C][C]103.812[/C][C]103.325[/C][C]1.00471[/C][C]0.996514[/C][/ROW]
[ROW][C]15[/C][C]103.5[/C][C]103.747[/C][C]103.42[/C][C]1.00316[/C][C]0.997615[/C][/ROW]
[ROW][C]16[/C][C]103.33[/C][C]103.608[/C][C]103.528[/C][C]1.00076[/C][C]0.997321[/C][/ROW]
[ROW][C]17[/C][C]103.56[/C][C]103.983[/C][C]103.665[/C][C]1.00307[/C][C]0.995928[/C][/ROW]
[ROW][C]18[/C][C]103.58[/C][C]103.582[/C][C]103.785[/C][C]0.998051[/C][C]0.999978[/C][/ROW]
[ROW][C]19[/C][C]103.86[/C][C]103.476[/C][C]103.86[/C][C]0.996306[/C][C]1.00371[/C][/ROW]
[ROW][C]20[/C][C]103.77[/C][C]103.507[/C][C]103.956[/C][C]0.995678[/C][C]1.00255[/C][/ROW]
[ROW][C]21[/C][C]103.73[/C][C]103.737[/C][C]104.082[/C][C]0.996685[/C][C]0.999932[/C][/ROW]
[ROW][C]22[/C][C]104.21[/C][C]103.962[/C][C]104.24[/C][C]0.99734[/C][C]1.00238[/C][/ROW]
[ROW][C]23[/C][C]104.55[/C][C]104.275[/C][C]104.458[/C][C]0.998245[/C][C]1.00264[/C][/ROW]
[ROW][C]24[/C][C]104.5[/C][C]104.966[/C][C]104.687[/C][C]1.00267[/C][C]0.99556[/C][/ROW]
[ROW][C]25[/C][C]104.66[/C][C]105.26[/C][C]104.911[/C][C]1.00332[/C][C]0.9943[/C][/ROW]
[ROW][C]26[/C][C]104.99[/C][C]105.645[/C][C]105.15[/C][C]1.00471[/C][C]0.9938[/C][/ROW]
[ROW][C]27[/C][C]104.99[/C][C]105.727[/C][C]105.394[/C][C]1.00316[/C][C]0.993029[/C][/ROW]
[ROW][C]28[/C][C]105.62[/C][C]105.695[/C][C]105.614[/C][C]1.00076[/C][C]0.999295[/C][/ROW]
[ROW][C]29[/C][C]106.52[/C][C]106.141[/C][C]105.816[/C][C]1.00307[/C][C]1.00357[/C][/ROW]
[ROW][C]30[/C][C]106.1[/C][C]105.814[/C][C]106.021[/C][C]0.998051[/C][C]1.0027[/C][/ROW]
[ROW][C]31[/C][C]106.73[/C][C]105.834[/C][C]106.226[/C][C]0.996306[/C][C]1.00847[/C][/ROW]
[ROW][C]32[/C][C]106.63[/C][C]106.007[/C][C]106.467[/C][C]0.995678[/C][C]1.00587[/C][/ROW]
[ROW][C]33[/C][C]106.72[/C][C]106.381[/C][C]106.735[/C][C]0.996685[/C][C]1.00319[/C][/ROW]
[ROW][C]34[/C][C]106.5[/C][C]106.683[/C][C]106.968[/C][C]0.99734[/C][C]0.998285[/C][/ROW]
[ROW][C]35[/C][C]107.12[/C][C]106.986[/C][C]107.174[/C][C]0.998245[/C][C]1.00125[/C][/ROW]
[ROW][C]36[/C][C]106.84[/C][C]107.723[/C][C]107.436[/C][C]1.00267[/C][C]0.991804[/C][/ROW]
[ROW][C]37[/C][C]107.25[/C][C]108.071[/C][C]107.713[/C][C]1.00332[/C][C]0.992399[/C][/ROW]
[ROW][C]38[/C][C]108.19[/C][C]108.472[/C][C]107.964[/C][C]1.00471[/C][C]0.997396[/C][/ROW]
[ROW][C]39[/C][C]108.21[/C][C]108.539[/C][C]108.197[/C][C]1.00316[/C][C]0.996971[/C][/ROW]
[ROW][C]40[/C][C]107.98[/C][C]108.47[/C][C]108.387[/C][C]1.00076[/C][C]0.995483[/C][/ROW]
[ROW][C]41[/C][C]109.12[/C][C]108.778[/C][C]108.445[/C][C]1.00307[/C][C]1.00314[/C][/ROW]
[ROW][C]42[/C][C]109.79[/C][C]108.225[/C][C]108.436[/C][C]0.998051[/C][C]1.01446[/C][/ROW]
[ROW][C]43[/C][C]109.69[/C][C]108[/C][C]108.4[/C][C]0.996306[/C][C]1.01565[/C][/ROW]
[ROW][C]44[/C][C]109.69[/C][C]107.893[/C][C]108.361[/C][C]0.995678[/C][C]1.01666[/C][/ROW]
[ROW][C]45[/C][C]109.24[/C][C]108.125[/C][C]108.484[/C][C]0.996685[/C][C]1.01032[/C][/ROW]
[ROW][C]46[/C][C]108.55[/C][C]108.452[/C][C]108.741[/C][C]0.99734[/C][C]1.00091[/C][/ROW]
[ROW][C]47[/C][C]106.47[/C][C]108.75[/C][C]108.942[/C][C]0.998245[/C][C]0.97903[/C][/ROW]
[ROW][C]48[/C][C]107.27[/C][C]109.155[/C][C]108.864[/C][C]1.00267[/C][C]0.982734[/C][/ROW]
[ROW][C]49[/C][C]105.95[/C][C]108.96[/C][C]108.599[/C][C]1.00332[/C][C]0.972373[/C][/ROW]
[ROW][C]50[/C][C]108.55[/C][C]108.797[/C][C]108.287[/C][C]1.00471[/C][C]0.997731[/C][/ROW]
[ROW][C]51[/C][C]110.81[/C][C]108.29[/C][C]107.949[/C][C]1.00316[/C][C]1.02327[/C][/ROW]
[ROW][C]52[/C][C]111.54[/C][C]107.669[/C][C]107.586[/C][C]1.00076[/C][C]1.03596[/C][/ROW]
[ROW][C]53[/C][C]110.38[/C][C]107.719[/C][C]107.389[/C][C]1.00307[/C][C]1.02471[/C][/ROW]
[ROW][C]54[/C][C]106.67[/C][C]107.237[/C][C]107.446[/C][C]0.998051[/C][C]0.994714[/C][/ROW]
[ROW][C]55[/C][C]106.45[/C][C]107.285[/C][C]107.683[/C][C]0.996306[/C][C]0.992216[/C][/ROW]
[ROW][C]56[/C][C]105.44[/C][C]107.321[/C][C]107.787[/C][C]0.995678[/C][C]0.982471[/C][/ROW]
[ROW][C]57[/C][C]105.37[/C][C]107.045[/C][C]107.401[/C][C]0.996685[/C][C]0.984354[/C][/ROW]
[ROW][C]58[/C][C]103.72[/C][C]106.386[/C][C]106.67[/C][C]0.99734[/C][C]0.974938[/C][/ROW]
[ROW][C]59[/C][C]106.57[/C][C]105.707[/C][C]105.892[/C][C]0.998245[/C][C]1.00817[/C][/ROW]
[ROW][C]60[/C][C]108.54[/C][C]105.578[/C][C]105.297[/C][C]1.00267[/C][C]1.02805[/C][/ROW]
[ROW][C]61[/C][C]110.36[/C][C]105.15[/C][C]104.802[/C][C]1.00332[/C][C]1.04955[/C][/ROW]
[ROW][C]62[/C][C]106.64[/C][C]104.819[/C][C]104.328[/C][C]1.00471[/C][C]1.01737[/C][/ROW]
[ROW][C]63[/C][C]103.45[/C][C]104.192[/C][C]103.864[/C][C]1.00316[/C][C]0.992877[/C][/ROW]
[ROW][C]64[/C][C]101.36[/C][C]103.523[/C][C]103.444[/C][C]1.00076[/C][C]0.979103[/C][/ROW]
[ROW][C]65[/C][C]101.9[/C][C]103.278[/C][C]102.962[/C][C]1.00307[/C][C]0.986658[/C][/ROW]
[ROW][C]66[/C][C]100.86[/C][C]102.073[/C][C]102.272[/C][C]0.998051[/C][C]0.988119[/C][/ROW]
[ROW][C]67[/C][C]100.37[/C][C]101.057[/C][C]101.431[/C][C]0.996306[/C][C]0.993206[/C][/ROW]
[ROW][C]68[/C][C]100.16[/C][C]100.255[/C][C]100.69[/C][C]0.995678[/C][C]0.99905[/C][/ROW]
[ROW][C]69[/C][C]99.5[/C][C]99.9214[/C][C]100.254[/C][C]0.996685[/C][C]0.995783[/C][/ROW]
[ROW][C]70[/C][C]99.52[/C][C]99.7801[/C][C]100.046[/C][C]0.99734[/C][C]0.997393[/C][/ROW]
[ROW][C]71[/C][C]99.2[/C][C]99.7284[/C][C]99.9038[/C][C]0.998245[/C][C]0.994702[/C][/ROW]
[ROW][C]72[/C][C]99.35[/C][C]100.042[/C][C]99.7762[/C][C]1.00267[/C][C]0.993078[/C][/ROW]
[ROW][C]73[/C][C]99.37[/C][C]100.018[/C][C]99.6871[/C][C]1.00332[/C][C]0.993516[/C][/ROW]
[ROW][C]74[/C][C]99.85[/C][C]100.074[/C][C]99.605[/C][C]1.00471[/C][C]0.997762[/C][/ROW]
[ROW][C]75[/C][C]99.76[/C][C]99.9011[/C][C]99.5862[/C][C]1.00316[/C][C]0.998587[/C][/ROW]
[ROW][C]76[/C][C]100.07[/C][C]99.6816[/C][C]99.6054[/C][C]1.00076[/C][C]1.0039[/C][/ROW]
[ROW][C]77[/C][C]99.77[/C][C]99.9244[/C][C]99.6187[/C][C]1.00307[/C][C]0.998455[/C][/ROW]
[ROW][C]78[/C][C]99.93[/C][C]99.4375[/C][C]99.6317[/C][C]0.998051[/C][C]1.00495[/C][/ROW]
[ROW][C]79[/C][C]99.16[/C][C]99.2657[/C][C]99.6338[/C][C]0.996306[/C][C]0.998935[/C][/ROW]
[ROW][C]80[/C][C]99.4[/C][C]99.1779[/C][C]99.6083[/C][C]0.995678[/C][C]1.00224[/C][/ROW]
[ROW][C]81[/C][C]99.81[/C][C]99.2329[/C][C]99.5629[/C][C]0.996685[/C][C]1.00582[/C][/ROW]
[ROW][C]82[/C][C]99.67[/C][C]99.1929[/C][C]99.4575[/C][C]0.99734[/C][C]1.00481[/C][/ROW]
[ROW][C]83[/C][C]99.37[/C][C]99.1744[/C][C]99.3488[/C][C]0.998245[/C][C]1.00197[/C][/ROW]
[ROW][C]84[/C][C]99.49[/C][C]99.5503[/C][C]99.2854[/C][C]1.00267[/C][C]0.999394[/C][/ROW]
[ROW][C]85[/C][C]99.28[/C][C]99.506[/C][C]99.1762[/C][C]1.00332[/C][C]0.997729[/C][/ROW]
[ROW][C]86[/C][C]99.33[/C][C]99.5301[/C][C]99.0637[/C][C]1.00471[/C][C]0.997989[/C][/ROW]
[ROW][C]87[/C][C]99.19[/C][C]99.359[/C][C]99.0458[/C][C]1.00316[/C][C]0.998299[/C][/ROW]
[ROW][C]88[/C][C]98.11[/C][C]99.2896[/C][C]99.2138[/C][C]1.00076[/C][C]0.988119[/C][/ROW]
[ROW][C]89[/C][C]99.12[/C][C]99.819[/C][C]99.5138[/C][C]1.00307[/C][C]0.992997[/C][/ROW]
[ROW][C]90[/C][C]99.06[/C][C]99.6392[/C][C]99.8338[/C][C]0.998051[/C][C]0.994187[/C][/ROW]
[ROW][C]91[/C][C]97.41[/C][C]99.7767[/C][C]100.147[/C][C]0.996306[/C][C]0.97628[/C][/ROW]
[ROW][C]92[/C][C]98.45[/C][C]100.05[/C][C]100.485[/C][C]0.995678[/C][C]0.984005[/C][/ROW]
[ROW][C]93[/C][C]100.33[/C][C]100.538[/C][C]100.872[/C][C]0.996685[/C][C]0.997934[/C][/ROW]
[ROW][C]94[/C][C]103.18[/C][C]101.043[/C][C]101.312[/C][C]0.99734[/C][C]1.02115[/C][/ROW]
[ROW][C]95[/C][C]103.06[/C][C]101.565[/C][C]101.743[/C][C]0.998245[/C][C]1.01472[/C][/ROW]
[ROW][C]96[/C][C]103.48[/C][C]102.402[/C][C]102.13[/C][C]1.00267[/C][C]1.01053[/C][/ROW]
[ROW][C]97[/C][C]102.8[/C][C]102.948[/C][C]102.607[/C][C]1.00332[/C][C]0.998564[/C][/ROW]
[ROW][C]98[/C][C]103.92[/C][C]103.605[/C][C]103.119[/C][C]1.00471[/C][C]1.00304[/C][/ROW]
[ROW][C]99[/C][C]103.9[/C][C]103.801[/C][C]103.474[/C][C]1.00316[/C][C]1.00095[/C][/ROW]
[ROW][C]100[/C][C]103.96[/C][C]103.708[/C][C]103.629[/C][C]1.00076[/C][C]1.00243[/C][/ROW]
[ROW][C]101[/C][C]103.62[/C][C]104.021[/C][C]103.703[/C][C]1.00307[/C][C]0.996145[/C][/ROW]
[ROW][C]102[/C][C]103.83[/C][C]103.572[/C][C]103.774[/C][C]0.998051[/C][C]1.00249[/C][/ROW]
[ROW][C]103[/C][C]104.09[/C][C]NA[/C][C]NA[/C][C]0.996306[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]104.07[/C][C]NA[/C][C]NA[/C][C]0.995678[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]103.22[/C][C]NA[/C][C]NA[/C][C]0.996685[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]104.01[/C][C]NA[/C][C]NA[/C][C]0.99734[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]104.01[/C][C]NA[/C][C]NA[/C][C]0.998245[/C][C]NA[/C][/ROW]
[ROW][C]108[/C][C]104.24[/C][C]NA[/C][C]NA[/C][C]1.00267[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284131&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284131&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	98.41	NA	NA	1.00332	NA
2	98.94	NA	NA	1.00471	NA
3	99.09	NA	NA	1.00316	NA
4	100.45	NA	NA	1.00076	NA
5	101.99	NA	NA	1.00307	NA
6	102.35	NA	NA	0.998051	NA
7	102.69	101.358	101.734	0.996306	1.01314
8	102.6	101.709	102.15	0.995678	1.00876
9	102.62	102.182	102.522	0.996685	1.00428
10	102.73	102.552	102.826	0.99734	1.00173
11	102.74	102.83	103.011	0.998245	0.999121
12	103.45	103.403	103.128	1.00267	1.00045
13	103.9	103.571	103.228	1.00332	1.00318
14	103.45	103.812	103.325	1.00471	0.996514
15	103.5	103.747	103.42	1.00316	0.997615
16	103.33	103.608	103.528	1.00076	0.997321
17	103.56	103.983	103.665	1.00307	0.995928
18	103.58	103.582	103.785	0.998051	0.999978
19	103.86	103.476	103.86	0.996306	1.00371
20	103.77	103.507	103.956	0.995678	1.00255
21	103.73	103.737	104.082	0.996685	0.999932
22	104.21	103.962	104.24	0.99734	1.00238
23	104.55	104.275	104.458	0.998245	1.00264
24	104.5	104.966	104.687	1.00267	0.99556
25	104.66	105.26	104.911	1.00332	0.9943
26	104.99	105.645	105.15	1.00471	0.9938
27	104.99	105.727	105.394	1.00316	0.993029
28	105.62	105.695	105.614	1.00076	0.999295
29	106.52	106.141	105.816	1.00307	1.00357
30	106.1	105.814	106.021	0.998051	1.0027
31	106.73	105.834	106.226	0.996306	1.00847
32	106.63	106.007	106.467	0.995678	1.00587
33	106.72	106.381	106.735	0.996685	1.00319
34	106.5	106.683	106.968	0.99734	0.998285
35	107.12	106.986	107.174	0.998245	1.00125
36	106.84	107.723	107.436	1.00267	0.991804
37	107.25	108.071	107.713	1.00332	0.992399
38	108.19	108.472	107.964	1.00471	0.997396
39	108.21	108.539	108.197	1.00316	0.996971
40	107.98	108.47	108.387	1.00076	0.995483
41	109.12	108.778	108.445	1.00307	1.00314
42	109.79	108.225	108.436	0.998051	1.01446
43	109.69	108	108.4	0.996306	1.01565
44	109.69	107.893	108.361	0.995678	1.01666
45	109.24	108.125	108.484	0.996685	1.01032
46	108.55	108.452	108.741	0.99734	1.00091
47	106.47	108.75	108.942	0.998245	0.97903
48	107.27	109.155	108.864	1.00267	0.982734
49	105.95	108.96	108.599	1.00332	0.972373
50	108.55	108.797	108.287	1.00471	0.997731
51	110.81	108.29	107.949	1.00316	1.02327
52	111.54	107.669	107.586	1.00076	1.03596
53	110.38	107.719	107.389	1.00307	1.02471
54	106.67	107.237	107.446	0.998051	0.994714
55	106.45	107.285	107.683	0.996306	0.992216
56	105.44	107.321	107.787	0.995678	0.982471
57	105.37	107.045	107.401	0.996685	0.984354
58	103.72	106.386	106.67	0.99734	0.974938
59	106.57	105.707	105.892	0.998245	1.00817
60	108.54	105.578	105.297	1.00267	1.02805
61	110.36	105.15	104.802	1.00332	1.04955
62	106.64	104.819	104.328	1.00471	1.01737
63	103.45	104.192	103.864	1.00316	0.992877
64	101.36	103.523	103.444	1.00076	0.979103
65	101.9	103.278	102.962	1.00307	0.986658
66	100.86	102.073	102.272	0.998051	0.988119
67	100.37	101.057	101.431	0.996306	0.993206
68	100.16	100.255	100.69	0.995678	0.99905
69	99.5	99.9214	100.254	0.996685	0.995783
70	99.52	99.7801	100.046	0.99734	0.997393
71	99.2	99.7284	99.9038	0.998245	0.994702
72	99.35	100.042	99.7762	1.00267	0.993078
73	99.37	100.018	99.6871	1.00332	0.993516
74	99.85	100.074	99.605	1.00471	0.997762
75	99.76	99.9011	99.5862	1.00316	0.998587
76	100.07	99.6816	99.6054	1.00076	1.0039
77	99.77	99.9244	99.6187	1.00307	0.998455
78	99.93	99.4375	99.6317	0.998051	1.00495
79	99.16	99.2657	99.6338	0.996306	0.998935
80	99.4	99.1779	99.6083	0.995678	1.00224
81	99.81	99.2329	99.5629	0.996685	1.00582
82	99.67	99.1929	99.4575	0.99734	1.00481
83	99.37	99.1744	99.3488	0.998245	1.00197
84	99.49	99.5503	99.2854	1.00267	0.999394
85	99.28	99.506	99.1762	1.00332	0.997729
86	99.33	99.5301	99.0637	1.00471	0.997989
87	99.19	99.359	99.0458	1.00316	0.998299
88	98.11	99.2896	99.2138	1.00076	0.988119
89	99.12	99.819	99.5138	1.00307	0.992997
90	99.06	99.6392	99.8338	0.998051	0.994187
91	97.41	99.7767	100.147	0.996306	0.97628
92	98.45	100.05	100.485	0.995678	0.984005
93	100.33	100.538	100.872	0.996685	0.997934
94	103.18	101.043	101.312	0.99734	1.02115
95	103.06	101.565	101.743	0.998245	1.01472
96	103.48	102.402	102.13	1.00267	1.01053
97	102.8	102.948	102.607	1.00332	0.998564
98	103.92	103.605	103.119	1.00471	1.00304
99	103.9	103.801	103.474	1.00316	1.00095
100	103.96	103.708	103.629	1.00076	1.00243
101	103.62	104.021	103.703	1.00307	0.996145
102	103.83	103.572	103.774	0.998051	1.00249
103	104.09	NA	NA	0.996306	NA
104	104.07	NA	NA	0.995678	NA
105	103.22	NA	NA	0.996685	NA
106	104.01	NA	NA	0.99734	NA
107	104.01	NA	NA	0.998245	NA
108	104.24	NA	NA	1.00267	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