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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 23 Nov 2015 20:13:35 +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/23/t1448309757jusiq695jt9bf1y.htm/, Retrieved Tue, 14 May 2024 06:07:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283970, Retrieved Tue, 14 May 2024 06:07:36 +0000

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-       [Classical Decomposition] [] [2015-11-23 20:13:35] [6e9c8a19a65400226bf8d1f1815bc708] [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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283970&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283970&T=0

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	71.59	NA	NA	0.089401	NA
2	71.65	NA	NA	1.43883	NA
3	71.47	NA	NA	1.62445	NA
4	71.82	NA	NA	-0.138411	NA
5	71.76	NA	NA	-0.165703	NA
6	71.88	NA	NA	-0.278203	NA
7	73.31	72.8825	72.7521	0.130391	0.427526
8	73.22	72.7993	73.1983	-0.399036	0.420703
9	72.74	72.8868	73.6633	-0.776484	-0.146849
10	72.95	73.1926	74.0838	-0.891172	-0.242578
11	73.71	74.0185	74.4417	-0.423203	-0.308464
12	74.45	74.5271	74.7379	-0.210859	-0.0770573
13	76.54	75.0382	74.9488	0.089401	1.50185
14	77.41	76.5388	75.1	1.43883	0.871172
15	76.87	76.8949	75.2704	1.62445	-0.0248698
16	76.51	75.3045	75.4429	-0.138411	1.20549
17	75.66	75.4251	75.5908	-0.165703	0.23487
18	75.09	75.4326	75.7108	-0.278203	-0.34263
19	75.16	75.9137	75.7833	0.130391	-0.753724
20	75	75.6451	76.0442	-0.399036	-0.64513
21	75.05	75.8885	76.665	-0.776484	-0.838516
22	74.78	76.6217	77.5129	-0.891172	-1.84174
23	75.43	78.0797	78.5029	-0.423203	-2.64971
24	75.61	79.4104	79.6212	-0.210859	-3.80039
25	77.12	80.9207	80.8312	0.089401	-3.80065
26	83.09	83.5309	82.0921	1.43883	-0.440911
27	86.09	85.0253	83.4008	1.62445	1.06471
28	87.64	84.6208	84.7592	-0.138411	3.01924
29	88.29	85.9843	86.15	-0.165703	2.3057
30	89.3	87.2718	87.55	-0.278203	2.0282
31	89.99	89.0196	88.8892	0.130391	0.970443
32	90.43	89.4239	89.8229	-0.399036	1.00612
33	91.03	89.4318	90.2083	-0.776484	1.59815
34	91.4	89.2926	90.1838	-0.891172	2.10742
35	92.19	89.423	89.8462	-0.423203	2.76695
36	92.45	89.0991	89.31	-0.210859	3.35086
37	92.42	88.7415	88.6521	0.089401	3.67852
38	90.2	89.4451	88.0063	1.43883	0.754922
39	88.23	88.9832	87.3588	1.62445	-0.753203
40	84.91	86.5162	86.6546	-0.138411	-1.60617
41	82.92	85.7764	85.9421	-0.165703	-2.85638
42	81.8	84.968	85.2462	-0.278203	-3.16805
43	81.7	84.7008	84.5704	0.130391	-3.00081
44	83.22	83.6814	84.0804	-0.399036	-0.46138
45	82.7	83.1239	83.9004	-0.776484	-0.423932
46	82.83	83.1372	84.0283	-0.891172	-0.307161
47	83.66	84.0426	84.4658	-0.423203	-0.38263
48	84.28	84.8696	85.0804	-0.210859	-0.589557
49	84.37	85.8102	85.7208	0.089401	-1.44023
50	86.49	87.6842	86.2454	1.43883	-1.19424
51	87.62	88.3324	86.7079	1.62445	-0.71237
52	88.59	87.0812	87.2196	-0.138411	1.50883
53	89.74	87.5635	87.7292	-0.165703	2.17654
54	89.73	87.9089	88.1871	-0.278203	1.82112
55	89.14	88.7504	88.62	0.130391	0.389609
56	88.37	88.7147	89.1138	-0.399036	-0.344714
57	88.65	88.8927	89.6692	-0.776484	-0.242682
58	89.16	89.3484	90.2396	-0.891172	-0.188411
59	89.56	90.601	91.0242	-0.423203	-1.04096
60	89.37	91.8571	92.0679	-0.210859	-2.48706
61	89.67	93.2602	93.1708	0.089401	-3.59023
62	93.04	95.7342	94.2954	1.43883	-2.69424
63	94.4	97.0378	95.4133	1.62445	-2.63779
64	95.5	96.3299	96.4683	-0.138411	-0.829922
65	101.66	97.2972	97.4629	-0.165703	4.36279
66	102.86	98.1385	98.4167	-0.278203	4.72154
67	102.48	99.4612	99.3308	0.130391	3.01878
68	102.02	99.7493	100.148	-0.399036	2.2707
69	101.83	100.055	100.831	-0.776484	1.77523
70	101.3	100.533	101.424	-0.891172	0.767005
71	101.29	101.25	101.673	-0.423203	0.0402865
72	100.53	101.335	101.546	-0.210859	-0.804974
73	100.45	101.451	101.361	0.089401	-1.00065
74	101.88	102.613	101.174	1.43883	-0.732578
75	101.95	102.598	100.973	1.62445	-0.647786
76	102.18	100.653	100.792	-0.138411	1.52674
77	100.95	100.521	100.687	-0.165703	0.429036
78	100.52	100.452	100.73	-0.278203	0.0677865
79	100.39	101.002	100.871	0.130391	-0.611641
80	99.61	100.515	100.914	-0.399036	-0.90513
81	99.43	100.064	100.84	-0.776484	-0.633516
82	99.34	99.8822	100.773	-0.891172	-0.542161
83	100.73	100.287	100.71	-0.423203	0.442786
84	102.14	100.435	100.646	-0.210859	1.70503
85	102.22	100.697	100.607	0.089401	1.5231
86	101.14	101.986	100.547	1.43883	-0.845911
87	100.91	102.077	100.453	1.62445	-1.16737
88	101.62	100.247	100.386	-0.138411	1.37258
89	100	100.126	100.292	-0.165703	-0.12638
90	99.92	99.831	100.109	-0.278203	0.0890365
91	100.07	99.9987	99.8683	0.130391	0.071276
92	98.48	99.3097	99.7087	-0.399036	-0.829714
93	98.3	98.8764	99.6529	-0.776484	-0.576432
94	98.86	98.1009	98.9921	-0.891172	0.759089
95	98.96	97.3168	97.74	-0.423203	1.6432
96	99.52	96.3054	96.5162	-0.210859	3.21461
97	99.06	95.4202	95.3308	0.089401	3.63977
98	100.47	95.6767	94.2379	1.43883	4.79326
99	100.24	94.8499	93.2254	1.62445	5.39013
100	86.43	92.1153	92.2538	-0.138411	-5.68534
101	85.14	91.1547	91.3204	-0.165703	-6.01471
102	85.41	90.1155	90.3938	-0.278203	-4.70555
103	86.13	NA	NA	0.130391	NA
104	86.19	NA	NA	-0.399036	NA
105	86.29	NA	NA	-0.776484	NA
106	87.55	NA	NA	-0.891172	NA
107	87.87	NA	NA	-0.423203	NA
108	88.37	NA	NA	-0.210859	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 71.59 & NA & NA & 0.089401 & NA \tabularnewline
2 & 71.65 & NA & NA & 1.43883 & NA \tabularnewline
3 & 71.47 & NA & NA & 1.62445 & NA \tabularnewline
4 & 71.82 & NA & NA & -0.138411 & NA \tabularnewline
5 & 71.76 & NA & NA & -0.165703 & NA \tabularnewline
6 & 71.88 & NA & NA & -0.278203 & NA \tabularnewline
7 & 73.31 & 72.8825 & 72.7521 & 0.130391 & 0.427526 \tabularnewline
8 & 73.22 & 72.7993 & 73.1983 & -0.399036 & 0.420703 \tabularnewline
9 & 72.74 & 72.8868 & 73.6633 & -0.776484 & -0.146849 \tabularnewline
10 & 72.95 & 73.1926 & 74.0838 & -0.891172 & -0.242578 \tabularnewline
11 & 73.71 & 74.0185 & 74.4417 & -0.423203 & -0.308464 \tabularnewline
12 & 74.45 & 74.5271 & 74.7379 & -0.210859 & -0.0770573 \tabularnewline
13 & 76.54 & 75.0382 & 74.9488 & 0.089401 & 1.50185 \tabularnewline
14 & 77.41 & 76.5388 & 75.1 & 1.43883 & 0.871172 \tabularnewline
15 & 76.87 & 76.8949 & 75.2704 & 1.62445 & -0.0248698 \tabularnewline
16 & 76.51 & 75.3045 & 75.4429 & -0.138411 & 1.20549 \tabularnewline
17 & 75.66 & 75.4251 & 75.5908 & -0.165703 & 0.23487 \tabularnewline
18 & 75.09 & 75.4326 & 75.7108 & -0.278203 & -0.34263 \tabularnewline
19 & 75.16 & 75.9137 & 75.7833 & 0.130391 & -0.753724 \tabularnewline
20 & 75 & 75.6451 & 76.0442 & -0.399036 & -0.64513 \tabularnewline
21 & 75.05 & 75.8885 & 76.665 & -0.776484 & -0.838516 \tabularnewline
22 & 74.78 & 76.6217 & 77.5129 & -0.891172 & -1.84174 \tabularnewline
23 & 75.43 & 78.0797 & 78.5029 & -0.423203 & -2.64971 \tabularnewline
24 & 75.61 & 79.4104 & 79.6212 & -0.210859 & -3.80039 \tabularnewline
25 & 77.12 & 80.9207 & 80.8312 & 0.089401 & -3.80065 \tabularnewline
26 & 83.09 & 83.5309 & 82.0921 & 1.43883 & -0.440911 \tabularnewline
27 & 86.09 & 85.0253 & 83.4008 & 1.62445 & 1.06471 \tabularnewline
28 & 87.64 & 84.6208 & 84.7592 & -0.138411 & 3.01924 \tabularnewline
29 & 88.29 & 85.9843 & 86.15 & -0.165703 & 2.3057 \tabularnewline
30 & 89.3 & 87.2718 & 87.55 & -0.278203 & 2.0282 \tabularnewline
31 & 89.99 & 89.0196 & 88.8892 & 0.130391 & 0.970443 \tabularnewline
32 & 90.43 & 89.4239 & 89.8229 & -0.399036 & 1.00612 \tabularnewline
33 & 91.03 & 89.4318 & 90.2083 & -0.776484 & 1.59815 \tabularnewline
34 & 91.4 & 89.2926 & 90.1838 & -0.891172 & 2.10742 \tabularnewline
35 & 92.19 & 89.423 & 89.8462 & -0.423203 & 2.76695 \tabularnewline
36 & 92.45 & 89.0991 & 89.31 & -0.210859 & 3.35086 \tabularnewline
37 & 92.42 & 88.7415 & 88.6521 & 0.089401 & 3.67852 \tabularnewline
38 & 90.2 & 89.4451 & 88.0063 & 1.43883 & 0.754922 \tabularnewline
39 & 88.23 & 88.9832 & 87.3588 & 1.62445 & -0.753203 \tabularnewline
40 & 84.91 & 86.5162 & 86.6546 & -0.138411 & -1.60617 \tabularnewline
41 & 82.92 & 85.7764 & 85.9421 & -0.165703 & -2.85638 \tabularnewline
42 & 81.8 & 84.968 & 85.2462 & -0.278203 & -3.16805 \tabularnewline
43 & 81.7 & 84.7008 & 84.5704 & 0.130391 & -3.00081 \tabularnewline
44 & 83.22 & 83.6814 & 84.0804 & -0.399036 & -0.46138 \tabularnewline
45 & 82.7 & 83.1239 & 83.9004 & -0.776484 & -0.423932 \tabularnewline
46 & 82.83 & 83.1372 & 84.0283 & -0.891172 & -0.307161 \tabularnewline
47 & 83.66 & 84.0426 & 84.4658 & -0.423203 & -0.38263 \tabularnewline
48 & 84.28 & 84.8696 & 85.0804 & -0.210859 & -0.589557 \tabularnewline
49 & 84.37 & 85.8102 & 85.7208 & 0.089401 & -1.44023 \tabularnewline
50 & 86.49 & 87.6842 & 86.2454 & 1.43883 & -1.19424 \tabularnewline
51 & 87.62 & 88.3324 & 86.7079 & 1.62445 & -0.71237 \tabularnewline
52 & 88.59 & 87.0812 & 87.2196 & -0.138411 & 1.50883 \tabularnewline
53 & 89.74 & 87.5635 & 87.7292 & -0.165703 & 2.17654 \tabularnewline
54 & 89.73 & 87.9089 & 88.1871 & -0.278203 & 1.82112 \tabularnewline
55 & 89.14 & 88.7504 & 88.62 & 0.130391 & 0.389609 \tabularnewline
56 & 88.37 & 88.7147 & 89.1138 & -0.399036 & -0.344714 \tabularnewline
57 & 88.65 & 88.8927 & 89.6692 & -0.776484 & -0.242682 \tabularnewline
58 & 89.16 & 89.3484 & 90.2396 & -0.891172 & -0.188411 \tabularnewline
59 & 89.56 & 90.601 & 91.0242 & -0.423203 & -1.04096 \tabularnewline
60 & 89.37 & 91.8571 & 92.0679 & -0.210859 & -2.48706 \tabularnewline
61 & 89.67 & 93.2602 & 93.1708 & 0.089401 & -3.59023 \tabularnewline
62 & 93.04 & 95.7342 & 94.2954 & 1.43883 & -2.69424 \tabularnewline
63 & 94.4 & 97.0378 & 95.4133 & 1.62445 & -2.63779 \tabularnewline
64 & 95.5 & 96.3299 & 96.4683 & -0.138411 & -0.829922 \tabularnewline
65 & 101.66 & 97.2972 & 97.4629 & -0.165703 & 4.36279 \tabularnewline
66 & 102.86 & 98.1385 & 98.4167 & -0.278203 & 4.72154 \tabularnewline
67 & 102.48 & 99.4612 & 99.3308 & 0.130391 & 3.01878 \tabularnewline
68 & 102.02 & 99.7493 & 100.148 & -0.399036 & 2.2707 \tabularnewline
69 & 101.83 & 100.055 & 100.831 & -0.776484 & 1.77523 \tabularnewline
70 & 101.3 & 100.533 & 101.424 & -0.891172 & 0.767005 \tabularnewline
71 & 101.29 & 101.25 & 101.673 & -0.423203 & 0.0402865 \tabularnewline
72 & 100.53 & 101.335 & 101.546 & -0.210859 & -0.804974 \tabularnewline
73 & 100.45 & 101.451 & 101.361 & 0.089401 & -1.00065 \tabularnewline
74 & 101.88 & 102.613 & 101.174 & 1.43883 & -0.732578 \tabularnewline
75 & 101.95 & 102.598 & 100.973 & 1.62445 & -0.647786 \tabularnewline
76 & 102.18 & 100.653 & 100.792 & -0.138411 & 1.52674 \tabularnewline
77 & 100.95 & 100.521 & 100.687 & -0.165703 & 0.429036 \tabularnewline
78 & 100.52 & 100.452 & 100.73 & -0.278203 & 0.0677865 \tabularnewline
79 & 100.39 & 101.002 & 100.871 & 0.130391 & -0.611641 \tabularnewline
80 & 99.61 & 100.515 & 100.914 & -0.399036 & -0.90513 \tabularnewline
81 & 99.43 & 100.064 & 100.84 & -0.776484 & -0.633516 \tabularnewline
82 & 99.34 & 99.8822 & 100.773 & -0.891172 & -0.542161 \tabularnewline
83 & 100.73 & 100.287 & 100.71 & -0.423203 & 0.442786 \tabularnewline
84 & 102.14 & 100.435 & 100.646 & -0.210859 & 1.70503 \tabularnewline
85 & 102.22 & 100.697 & 100.607 & 0.089401 & 1.5231 \tabularnewline
86 & 101.14 & 101.986 & 100.547 & 1.43883 & -0.845911 \tabularnewline
87 & 100.91 & 102.077 & 100.453 & 1.62445 & -1.16737 \tabularnewline
88 & 101.62 & 100.247 & 100.386 & -0.138411 & 1.37258 \tabularnewline
89 & 100 & 100.126 & 100.292 & -0.165703 & -0.12638 \tabularnewline
90 & 99.92 & 99.831 & 100.109 & -0.278203 & 0.0890365 \tabularnewline
91 & 100.07 & 99.9987 & 99.8683 & 0.130391 & 0.071276 \tabularnewline
92 & 98.48 & 99.3097 & 99.7087 & -0.399036 & -0.829714 \tabularnewline
93 & 98.3 & 98.8764 & 99.6529 & -0.776484 & -0.576432 \tabularnewline
94 & 98.86 & 98.1009 & 98.9921 & -0.891172 & 0.759089 \tabularnewline
95 & 98.96 & 97.3168 & 97.74 & -0.423203 & 1.6432 \tabularnewline
96 & 99.52 & 96.3054 & 96.5162 & -0.210859 & 3.21461 \tabularnewline
97 & 99.06 & 95.4202 & 95.3308 & 0.089401 & 3.63977 \tabularnewline
98 & 100.47 & 95.6767 & 94.2379 & 1.43883 & 4.79326 \tabularnewline
99 & 100.24 & 94.8499 & 93.2254 & 1.62445 & 5.39013 \tabularnewline
100 & 86.43 & 92.1153 & 92.2538 & -0.138411 & -5.68534 \tabularnewline
101 & 85.14 & 91.1547 & 91.3204 & -0.165703 & -6.01471 \tabularnewline
102 & 85.41 & 90.1155 & 90.3938 & -0.278203 & -4.70555 \tabularnewline
103 & 86.13 & NA & NA & 0.130391 & NA \tabularnewline
104 & 86.19 & NA & NA & -0.399036 & NA \tabularnewline
105 & 86.29 & NA & NA & -0.776484 & NA \tabularnewline
106 & 87.55 & NA & NA & -0.891172 & NA \tabularnewline
107 & 87.87 & NA & NA & -0.423203 & NA \tabularnewline
108 & 88.37 & NA & NA & -0.210859 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283970&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]71.59[/C][C]NA[/C][C]NA[/C][C]0.089401[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]71.65[/C][C]NA[/C][C]NA[/C][C]1.43883[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]71.47[/C][C]NA[/C][C]NA[/C][C]1.62445[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]71.82[/C][C]NA[/C][C]NA[/C][C]-0.138411[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]71.76[/C][C]NA[/C][C]NA[/C][C]-0.165703[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]71.88[/C][C]NA[/C][C]NA[/C][C]-0.278203[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]73.31[/C][C]72.8825[/C][C]72.7521[/C][C]0.130391[/C][C]0.427526[/C][/ROW]
[ROW][C]8[/C][C]73.22[/C][C]72.7993[/C][C]73.1983[/C][C]-0.399036[/C][C]0.420703[/C][/ROW]
[ROW][C]9[/C][C]72.74[/C][C]72.8868[/C][C]73.6633[/C][C]-0.776484[/C][C]-0.146849[/C][/ROW]
[ROW][C]10[/C][C]72.95[/C][C]73.1926[/C][C]74.0838[/C][C]-0.891172[/C][C]-0.242578[/C][/ROW]
[ROW][C]11[/C][C]73.71[/C][C]74.0185[/C][C]74.4417[/C][C]-0.423203[/C][C]-0.308464[/C][/ROW]
[ROW][C]12[/C][C]74.45[/C][C]74.5271[/C][C]74.7379[/C][C]-0.210859[/C][C]-0.0770573[/C][/ROW]
[ROW][C]13[/C][C]76.54[/C][C]75.0382[/C][C]74.9488[/C][C]0.089401[/C][C]1.50185[/C][/ROW]
[ROW][C]14[/C][C]77.41[/C][C]76.5388[/C][C]75.1[/C][C]1.43883[/C][C]0.871172[/C][/ROW]
[ROW][C]15[/C][C]76.87[/C][C]76.8949[/C][C]75.2704[/C][C]1.62445[/C][C]-0.0248698[/C][/ROW]
[ROW][C]16[/C][C]76.51[/C][C]75.3045[/C][C]75.4429[/C][C]-0.138411[/C][C]1.20549[/C][/ROW]
[ROW][C]17[/C][C]75.66[/C][C]75.4251[/C][C]75.5908[/C][C]-0.165703[/C][C]0.23487[/C][/ROW]
[ROW][C]18[/C][C]75.09[/C][C]75.4326[/C][C]75.7108[/C][C]-0.278203[/C][C]-0.34263[/C][/ROW]
[ROW][C]19[/C][C]75.16[/C][C]75.9137[/C][C]75.7833[/C][C]0.130391[/C][C]-0.753724[/C][/ROW]
[ROW][C]20[/C][C]75[/C][C]75.6451[/C][C]76.0442[/C][C]-0.399036[/C][C]-0.64513[/C][/ROW]
[ROW][C]21[/C][C]75.05[/C][C]75.8885[/C][C]76.665[/C][C]-0.776484[/C][C]-0.838516[/C][/ROW]
[ROW][C]22[/C][C]74.78[/C][C]76.6217[/C][C]77.5129[/C][C]-0.891172[/C][C]-1.84174[/C][/ROW]
[ROW][C]23[/C][C]75.43[/C][C]78.0797[/C][C]78.5029[/C][C]-0.423203[/C][C]-2.64971[/C][/ROW]
[ROW][C]24[/C][C]75.61[/C][C]79.4104[/C][C]79.6212[/C][C]-0.210859[/C][C]-3.80039[/C][/ROW]
[ROW][C]25[/C][C]77.12[/C][C]80.9207[/C][C]80.8312[/C][C]0.089401[/C][C]-3.80065[/C][/ROW]
[ROW][C]26[/C][C]83.09[/C][C]83.5309[/C][C]82.0921[/C][C]1.43883[/C][C]-0.440911[/C][/ROW]
[ROW][C]27[/C][C]86.09[/C][C]85.0253[/C][C]83.4008[/C][C]1.62445[/C][C]1.06471[/C][/ROW]
[ROW][C]28[/C][C]87.64[/C][C]84.6208[/C][C]84.7592[/C][C]-0.138411[/C][C]3.01924[/C][/ROW]
[ROW][C]29[/C][C]88.29[/C][C]85.9843[/C][C]86.15[/C][C]-0.165703[/C][C]2.3057[/C][/ROW]
[ROW][C]30[/C][C]89.3[/C][C]87.2718[/C][C]87.55[/C][C]-0.278203[/C][C]2.0282[/C][/ROW]
[ROW][C]31[/C][C]89.99[/C][C]89.0196[/C][C]88.8892[/C][C]0.130391[/C][C]0.970443[/C][/ROW]
[ROW][C]32[/C][C]90.43[/C][C]89.4239[/C][C]89.8229[/C][C]-0.399036[/C][C]1.00612[/C][/ROW]
[ROW][C]33[/C][C]91.03[/C][C]89.4318[/C][C]90.2083[/C][C]-0.776484[/C][C]1.59815[/C][/ROW]
[ROW][C]34[/C][C]91.4[/C][C]89.2926[/C][C]90.1838[/C][C]-0.891172[/C][C]2.10742[/C][/ROW]
[ROW][C]35[/C][C]92.19[/C][C]89.423[/C][C]89.8462[/C][C]-0.423203[/C][C]2.76695[/C][/ROW]
[ROW][C]36[/C][C]92.45[/C][C]89.0991[/C][C]89.31[/C][C]-0.210859[/C][C]3.35086[/C][/ROW]
[ROW][C]37[/C][C]92.42[/C][C]88.7415[/C][C]88.6521[/C][C]0.089401[/C][C]3.67852[/C][/ROW]
[ROW][C]38[/C][C]90.2[/C][C]89.4451[/C][C]88.0063[/C][C]1.43883[/C][C]0.754922[/C][/ROW]
[ROW][C]39[/C][C]88.23[/C][C]88.9832[/C][C]87.3588[/C][C]1.62445[/C][C]-0.753203[/C][/ROW]
[ROW][C]40[/C][C]84.91[/C][C]86.5162[/C][C]86.6546[/C][C]-0.138411[/C][C]-1.60617[/C][/ROW]
[ROW][C]41[/C][C]82.92[/C][C]85.7764[/C][C]85.9421[/C][C]-0.165703[/C][C]-2.85638[/C][/ROW]
[ROW][C]42[/C][C]81.8[/C][C]84.968[/C][C]85.2462[/C][C]-0.278203[/C][C]-3.16805[/C][/ROW]
[ROW][C]43[/C][C]81.7[/C][C]84.7008[/C][C]84.5704[/C][C]0.130391[/C][C]-3.00081[/C][/ROW]
[ROW][C]44[/C][C]83.22[/C][C]83.6814[/C][C]84.0804[/C][C]-0.399036[/C][C]-0.46138[/C][/ROW]
[ROW][C]45[/C][C]82.7[/C][C]83.1239[/C][C]83.9004[/C][C]-0.776484[/C][C]-0.423932[/C][/ROW]
[ROW][C]46[/C][C]82.83[/C][C]83.1372[/C][C]84.0283[/C][C]-0.891172[/C][C]-0.307161[/C][/ROW]
[ROW][C]47[/C][C]83.66[/C][C]84.0426[/C][C]84.4658[/C][C]-0.423203[/C][C]-0.38263[/C][/ROW]
[ROW][C]48[/C][C]84.28[/C][C]84.8696[/C][C]85.0804[/C][C]-0.210859[/C][C]-0.589557[/C][/ROW]
[ROW][C]49[/C][C]84.37[/C][C]85.8102[/C][C]85.7208[/C][C]0.089401[/C][C]-1.44023[/C][/ROW]
[ROW][C]50[/C][C]86.49[/C][C]87.6842[/C][C]86.2454[/C][C]1.43883[/C][C]-1.19424[/C][/ROW]
[ROW][C]51[/C][C]87.62[/C][C]88.3324[/C][C]86.7079[/C][C]1.62445[/C][C]-0.71237[/C][/ROW]
[ROW][C]52[/C][C]88.59[/C][C]87.0812[/C][C]87.2196[/C][C]-0.138411[/C][C]1.50883[/C][/ROW]
[ROW][C]53[/C][C]89.74[/C][C]87.5635[/C][C]87.7292[/C][C]-0.165703[/C][C]2.17654[/C][/ROW]
[ROW][C]54[/C][C]89.73[/C][C]87.9089[/C][C]88.1871[/C][C]-0.278203[/C][C]1.82112[/C][/ROW]
[ROW][C]55[/C][C]89.14[/C][C]88.7504[/C][C]88.62[/C][C]0.130391[/C][C]0.389609[/C][/ROW]
[ROW][C]56[/C][C]88.37[/C][C]88.7147[/C][C]89.1138[/C][C]-0.399036[/C][C]-0.344714[/C][/ROW]
[ROW][C]57[/C][C]88.65[/C][C]88.8927[/C][C]89.6692[/C][C]-0.776484[/C][C]-0.242682[/C][/ROW]
[ROW][C]58[/C][C]89.16[/C][C]89.3484[/C][C]90.2396[/C][C]-0.891172[/C][C]-0.188411[/C][/ROW]
[ROW][C]59[/C][C]89.56[/C][C]90.601[/C][C]91.0242[/C][C]-0.423203[/C][C]-1.04096[/C][/ROW]
[ROW][C]60[/C][C]89.37[/C][C]91.8571[/C][C]92.0679[/C][C]-0.210859[/C][C]-2.48706[/C][/ROW]
[ROW][C]61[/C][C]89.67[/C][C]93.2602[/C][C]93.1708[/C][C]0.089401[/C][C]-3.59023[/C][/ROW]
[ROW][C]62[/C][C]93.04[/C][C]95.7342[/C][C]94.2954[/C][C]1.43883[/C][C]-2.69424[/C][/ROW]
[ROW][C]63[/C][C]94.4[/C][C]97.0378[/C][C]95.4133[/C][C]1.62445[/C][C]-2.63779[/C][/ROW]
[ROW][C]64[/C][C]95.5[/C][C]96.3299[/C][C]96.4683[/C][C]-0.138411[/C][C]-0.829922[/C][/ROW]
[ROW][C]65[/C][C]101.66[/C][C]97.2972[/C][C]97.4629[/C][C]-0.165703[/C][C]4.36279[/C][/ROW]
[ROW][C]66[/C][C]102.86[/C][C]98.1385[/C][C]98.4167[/C][C]-0.278203[/C][C]4.72154[/C][/ROW]
[ROW][C]67[/C][C]102.48[/C][C]99.4612[/C][C]99.3308[/C][C]0.130391[/C][C]3.01878[/C][/ROW]
[ROW][C]68[/C][C]102.02[/C][C]99.7493[/C][C]100.148[/C][C]-0.399036[/C][C]2.2707[/C][/ROW]
[ROW][C]69[/C][C]101.83[/C][C]100.055[/C][C]100.831[/C][C]-0.776484[/C][C]1.77523[/C][/ROW]
[ROW][C]70[/C][C]101.3[/C][C]100.533[/C][C]101.424[/C][C]-0.891172[/C][C]0.767005[/C][/ROW]
[ROW][C]71[/C][C]101.29[/C][C]101.25[/C][C]101.673[/C][C]-0.423203[/C][C]0.0402865[/C][/ROW]
[ROW][C]72[/C][C]100.53[/C][C]101.335[/C][C]101.546[/C][C]-0.210859[/C][C]-0.804974[/C][/ROW]
[ROW][C]73[/C][C]100.45[/C][C]101.451[/C][C]101.361[/C][C]0.089401[/C][C]-1.00065[/C][/ROW]
[ROW][C]74[/C][C]101.88[/C][C]102.613[/C][C]101.174[/C][C]1.43883[/C][C]-0.732578[/C][/ROW]
[ROW][C]75[/C][C]101.95[/C][C]102.598[/C][C]100.973[/C][C]1.62445[/C][C]-0.647786[/C][/ROW]
[ROW][C]76[/C][C]102.18[/C][C]100.653[/C][C]100.792[/C][C]-0.138411[/C][C]1.52674[/C][/ROW]
[ROW][C]77[/C][C]100.95[/C][C]100.521[/C][C]100.687[/C][C]-0.165703[/C][C]0.429036[/C][/ROW]
[ROW][C]78[/C][C]100.52[/C][C]100.452[/C][C]100.73[/C][C]-0.278203[/C][C]0.0677865[/C][/ROW]
[ROW][C]79[/C][C]100.39[/C][C]101.002[/C][C]100.871[/C][C]0.130391[/C][C]-0.611641[/C][/ROW]
[ROW][C]80[/C][C]99.61[/C][C]100.515[/C][C]100.914[/C][C]-0.399036[/C][C]-0.90513[/C][/ROW]
[ROW][C]81[/C][C]99.43[/C][C]100.064[/C][C]100.84[/C][C]-0.776484[/C][C]-0.633516[/C][/ROW]
[ROW][C]82[/C][C]99.34[/C][C]99.8822[/C][C]100.773[/C][C]-0.891172[/C][C]-0.542161[/C][/ROW]
[ROW][C]83[/C][C]100.73[/C][C]100.287[/C][C]100.71[/C][C]-0.423203[/C][C]0.442786[/C][/ROW]
[ROW][C]84[/C][C]102.14[/C][C]100.435[/C][C]100.646[/C][C]-0.210859[/C][C]1.70503[/C][/ROW]
[ROW][C]85[/C][C]102.22[/C][C]100.697[/C][C]100.607[/C][C]0.089401[/C][C]1.5231[/C][/ROW]
[ROW][C]86[/C][C]101.14[/C][C]101.986[/C][C]100.547[/C][C]1.43883[/C][C]-0.845911[/C][/ROW]
[ROW][C]87[/C][C]100.91[/C][C]102.077[/C][C]100.453[/C][C]1.62445[/C][C]-1.16737[/C][/ROW]
[ROW][C]88[/C][C]101.62[/C][C]100.247[/C][C]100.386[/C][C]-0.138411[/C][C]1.37258[/C][/ROW]
[ROW][C]89[/C][C]100[/C][C]100.126[/C][C]100.292[/C][C]-0.165703[/C][C]-0.12638[/C][/ROW]
[ROW][C]90[/C][C]99.92[/C][C]99.831[/C][C]100.109[/C][C]-0.278203[/C][C]0.0890365[/C][/ROW]
[ROW][C]91[/C][C]100.07[/C][C]99.9987[/C][C]99.8683[/C][C]0.130391[/C][C]0.071276[/C][/ROW]
[ROW][C]92[/C][C]98.48[/C][C]99.3097[/C][C]99.7087[/C][C]-0.399036[/C][C]-0.829714[/C][/ROW]
[ROW][C]93[/C][C]98.3[/C][C]98.8764[/C][C]99.6529[/C][C]-0.776484[/C][C]-0.576432[/C][/ROW]
[ROW][C]94[/C][C]98.86[/C][C]98.1009[/C][C]98.9921[/C][C]-0.891172[/C][C]0.759089[/C][/ROW]
[ROW][C]95[/C][C]98.96[/C][C]97.3168[/C][C]97.74[/C][C]-0.423203[/C][C]1.6432[/C][/ROW]
[ROW][C]96[/C][C]99.52[/C][C]96.3054[/C][C]96.5162[/C][C]-0.210859[/C][C]3.21461[/C][/ROW]
[ROW][C]97[/C][C]99.06[/C][C]95.4202[/C][C]95.3308[/C][C]0.089401[/C][C]3.63977[/C][/ROW]
[ROW][C]98[/C][C]100.47[/C][C]95.6767[/C][C]94.2379[/C][C]1.43883[/C][C]4.79326[/C][/ROW]
[ROW][C]99[/C][C]100.24[/C][C]94.8499[/C][C]93.2254[/C][C]1.62445[/C][C]5.39013[/C][/ROW]
[ROW][C]100[/C][C]86.43[/C][C]92.1153[/C][C]92.2538[/C][C]-0.138411[/C][C]-5.68534[/C][/ROW]
[ROW][C]101[/C][C]85.14[/C][C]91.1547[/C][C]91.3204[/C][C]-0.165703[/C][C]-6.01471[/C][/ROW]
[ROW][C]102[/C][C]85.41[/C][C]90.1155[/C][C]90.3938[/C][C]-0.278203[/C][C]-4.70555[/C][/ROW]
[ROW][C]103[/C][C]86.13[/C][C]NA[/C][C]NA[/C][C]0.130391[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]86.19[/C][C]NA[/C][C]NA[/C][C]-0.399036[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]86.29[/C][C]NA[/C][C]NA[/C][C]-0.776484[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]87.55[/C][C]NA[/C][C]NA[/C][C]-0.891172[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]87.87[/C][C]NA[/C][C]NA[/C][C]-0.423203[/C][C]NA[/C][/ROW]
[ROW][C]108[/C][C]88.37[/C][C]NA[/C][C]NA[/C][C]-0.210859[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283970&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283970&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	71.59	NA	NA	0.089401	NA
2	71.65	NA	NA	1.43883	NA
3	71.47	NA	NA	1.62445	NA
4	71.82	NA	NA	-0.138411	NA
5	71.76	NA	NA	-0.165703	NA
6	71.88	NA	NA	-0.278203	NA
7	73.31	72.8825	72.7521	0.130391	0.427526
8	73.22	72.7993	73.1983	-0.399036	0.420703
9	72.74	72.8868	73.6633	-0.776484	-0.146849
10	72.95	73.1926	74.0838	-0.891172	-0.242578
11	73.71	74.0185	74.4417	-0.423203	-0.308464
12	74.45	74.5271	74.7379	-0.210859	-0.0770573
13	76.54	75.0382	74.9488	0.089401	1.50185
14	77.41	76.5388	75.1	1.43883	0.871172
15	76.87	76.8949	75.2704	1.62445	-0.0248698
16	76.51	75.3045	75.4429	-0.138411	1.20549
17	75.66	75.4251	75.5908	-0.165703	0.23487
18	75.09	75.4326	75.7108	-0.278203	-0.34263
19	75.16	75.9137	75.7833	0.130391	-0.753724
20	75	75.6451	76.0442	-0.399036	-0.64513
21	75.05	75.8885	76.665	-0.776484	-0.838516
22	74.78	76.6217	77.5129	-0.891172	-1.84174
23	75.43	78.0797	78.5029	-0.423203	-2.64971
24	75.61	79.4104	79.6212	-0.210859	-3.80039
25	77.12	80.9207	80.8312	0.089401	-3.80065
26	83.09	83.5309	82.0921	1.43883	-0.440911
27	86.09	85.0253	83.4008	1.62445	1.06471
28	87.64	84.6208	84.7592	-0.138411	3.01924
29	88.29	85.9843	86.15	-0.165703	2.3057
30	89.3	87.2718	87.55	-0.278203	2.0282
31	89.99	89.0196	88.8892	0.130391	0.970443
32	90.43	89.4239	89.8229	-0.399036	1.00612
33	91.03	89.4318	90.2083	-0.776484	1.59815
34	91.4	89.2926	90.1838	-0.891172	2.10742
35	92.19	89.423	89.8462	-0.423203	2.76695
36	92.45	89.0991	89.31	-0.210859	3.35086
37	92.42	88.7415	88.6521	0.089401	3.67852
38	90.2	89.4451	88.0063	1.43883	0.754922
39	88.23	88.9832	87.3588	1.62445	-0.753203
40	84.91	86.5162	86.6546	-0.138411	-1.60617
41	82.92	85.7764	85.9421	-0.165703	-2.85638
42	81.8	84.968	85.2462	-0.278203	-3.16805
43	81.7	84.7008	84.5704	0.130391	-3.00081
44	83.22	83.6814	84.0804	-0.399036	-0.46138
45	82.7	83.1239	83.9004	-0.776484	-0.423932
46	82.83	83.1372	84.0283	-0.891172	-0.307161
47	83.66	84.0426	84.4658	-0.423203	-0.38263
48	84.28	84.8696	85.0804	-0.210859	-0.589557
49	84.37	85.8102	85.7208	0.089401	-1.44023
50	86.49	87.6842	86.2454	1.43883	-1.19424
51	87.62	88.3324	86.7079	1.62445	-0.71237
52	88.59	87.0812	87.2196	-0.138411	1.50883
53	89.74	87.5635	87.7292	-0.165703	2.17654
54	89.73	87.9089	88.1871	-0.278203	1.82112
55	89.14	88.7504	88.62	0.130391	0.389609
56	88.37	88.7147	89.1138	-0.399036	-0.344714
57	88.65	88.8927	89.6692	-0.776484	-0.242682
58	89.16	89.3484	90.2396	-0.891172	-0.188411
59	89.56	90.601	91.0242	-0.423203	-1.04096
60	89.37	91.8571	92.0679	-0.210859	-2.48706
61	89.67	93.2602	93.1708	0.089401	-3.59023
62	93.04	95.7342	94.2954	1.43883	-2.69424
63	94.4	97.0378	95.4133	1.62445	-2.63779
64	95.5	96.3299	96.4683	-0.138411	-0.829922
65	101.66	97.2972	97.4629	-0.165703	4.36279
66	102.86	98.1385	98.4167	-0.278203	4.72154
67	102.48	99.4612	99.3308	0.130391	3.01878
68	102.02	99.7493	100.148	-0.399036	2.2707
69	101.83	100.055	100.831	-0.776484	1.77523
70	101.3	100.533	101.424	-0.891172	0.767005
71	101.29	101.25	101.673	-0.423203	0.0402865
72	100.53	101.335	101.546	-0.210859	-0.804974
73	100.45	101.451	101.361	0.089401	-1.00065
74	101.88	102.613	101.174	1.43883	-0.732578
75	101.95	102.598	100.973	1.62445	-0.647786
76	102.18	100.653	100.792	-0.138411	1.52674
77	100.95	100.521	100.687	-0.165703	0.429036
78	100.52	100.452	100.73	-0.278203	0.0677865
79	100.39	101.002	100.871	0.130391	-0.611641
80	99.61	100.515	100.914	-0.399036	-0.90513
81	99.43	100.064	100.84	-0.776484	-0.633516
82	99.34	99.8822	100.773	-0.891172	-0.542161
83	100.73	100.287	100.71	-0.423203	0.442786
84	102.14	100.435	100.646	-0.210859	1.70503
85	102.22	100.697	100.607	0.089401	1.5231
86	101.14	101.986	100.547	1.43883	-0.845911
87	100.91	102.077	100.453	1.62445	-1.16737
88	101.62	100.247	100.386	-0.138411	1.37258
89	100	100.126	100.292	-0.165703	-0.12638
90	99.92	99.831	100.109	-0.278203	0.0890365
91	100.07	99.9987	99.8683	0.130391	0.071276
92	98.48	99.3097	99.7087	-0.399036	-0.829714
93	98.3	98.8764	99.6529	-0.776484	-0.576432
94	98.86	98.1009	98.9921	-0.891172	0.759089
95	98.96	97.3168	97.74	-0.423203	1.6432
96	99.52	96.3054	96.5162	-0.210859	3.21461
97	99.06	95.4202	95.3308	0.089401	3.63977
98	100.47	95.6767	94.2379	1.43883	4.79326
99	100.24	94.8499	93.2254	1.62445	5.39013
100	86.43	92.1153	92.2538	-0.138411	-5.68534
101	85.14	91.1547	91.3204	-0.165703	-6.01471
102	85.41	90.1155	90.3938	-0.278203	-4.70555
103	86.13	NA	NA	0.130391	NA
104	86.19	NA	NA	-0.399036	NA
105	86.29	NA	NA	-0.776484	NA
106	87.55	NA	NA	-0.891172	NA
107	87.87	NA	NA	-0.423203	NA
108	88.37	NA	NA	-0.210859	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 <- 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