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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 23 Nov 2015 13:28:42 +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/t1448285362wahrorgmufr7ryt.htm/, Retrieved Mon, 13 May 2024 22:49:28 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283926, Retrieved Mon, 13 May 2024 22:49:28 +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] [classical decompo...] [2015-11-23 13:28:42] [f80e7d2207e498094c9e16c0f447e302] [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=283926&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=283926&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283926&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	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	78.25	NA	NA	0.100829	NA
2	77.24	NA	NA	0.64536	NA
3	76.68	NA	NA	0.850933	NA
4	76.29	NA	NA	0.342496	NA
5	76.1	NA	NA	-0.0670356	NA
6	75.77	NA	NA	-0.248963	NA
7	75.6	75.6563	76.4783	-0.822036	-0.0562977
8	75.57	76.1512	76.6633	-0.51214	-0.581194
9	75.89	77.0527	77.0275	0.025204	-1.1627
10	76.04	77.6855	77.4846	0.200881	-1.64546
11	76.89	77.9647	77.9321	0.0325998	-1.07468
12	77	77.8573	78.4054	-0.548129	-0.857287
13	79.09	79.0404	78.9396	0.100829	0.0495877
14	80.84	80.1358	79.4904	0.64536	0.704223
15	81.82	80.9134	80.0625	0.850933	0.906567
16	82.12	80.9592	80.6167	0.342496	1.16084
17	81.01	81.0863	81.1533	-0.0670356	-0.0762977
18	82.22	81.4765	81.7254	-0.248963	0.743546
19	81.97	81.55	82.3721	-0.822036	0.419952
20	82.42	82.6283	83.1404	-0.51214	-0.208277
21	82.77	84.0777	84.0525	0.025204	-1.3077
22	82.46	85.2459	85.045	0.200881	-2.78588
23	83.35	86.1622	86.1296	0.0325998	-2.81218
24	84.27	86.714	87.2621	-0.548129	-2.44395
25	87.34	88.5233	88.4225	0.100829	-1.18333
26	91.03	90.3274	89.6821	0.64536	0.702556
27	93.52	92.0226	91.1717	0.850933	1.4974
28	94.24	93.2542	92.9117	0.342496	0.985838
29	94.92	94.5863	94.6533	-0.0670356	0.333702
30	95.49	96.0369	96.2858	-0.248963	-0.546871
31	96.55	96.948	97.77	-0.822036	-0.397964
32	98.07	98.4762	98.9883	-0.51214	-0.406194
33	102.87	99.9531	99.9279	0.025204	2.91688
34	104.12	100.899	100.698	0.200881	3.2212
35	103.49	101.425	101.392	0.0325998	2.0649
36	103.31	101.511	102.06	-0.548129	1.79855
37	103.92	102.742	102.641	0.100829	1.17834
38	103.69	103.731	103.085	0.64536	-0.0407769
39	103.41	104.103	103.252	0.850933	-0.693016
40	102.83	103.492	103.15	0.342496	-0.662496
41	103	102.966	103.033	-0.0670356	0.0341189
42	103.42	102.669	102.918	-0.248963	0.751046
43	102.57	101.902	102.724	-0.822036	0.667869
44	102.72	101.996	102.508	-0.51214	0.723806
45	102.22	102.327	102.302	0.025204	-0.107287
46	102.32	102.264	102.063	0.200881	0.0562023
47	102.48	101.833	101.8	0.0325998	0.6474
48	101.56	100.94	101.488	-0.548129	0.620213
49	101.02	101.267	101.167	0.100829	-0.247496
50	101.41	101.542	100.896	0.64536	-0.13161
51	100.74	101.503	100.653	0.850933	-0.763433
52	99.76	100.772	100.43	0.342496	-1.01208
53	99.76	100.142	100.209	-0.0670356	-0.382131
54	99.17	99.7277	99.9767	-0.248963	-0.557704
55	99.11	98.9221	99.7442	-0.822036	0.187869
56	99.69	98.9462	99.4583	-0.51214	0.743806
57	99.4	99.1456	99.1204	0.025204	0.254379
58	99.79	99.005	98.8042	0.200881	0.784952
59	99.72	98.5276	98.495	0.0325998	1.1924
60	98.74	97.6602	98.2083	-0.548129	1.0798
61	98.26	98.0379	97.9371	0.100829	0.222088
62	97.31	98.2224	97.5771	0.64536	-0.912444
63	96.73	98.0005	97.1496	0.850933	-1.27052
64	96.18	97.1242	96.7817	0.342496	-0.944162
65	95.92	96.4109	96.4779	-0.0670356	-0.490881
66	96.13	95.931	96.18	-0.248963	0.198963
67	95.64	95.0875	95.9096	-0.822036	0.552452
68	94.52	95.2433	95.7554	-0.51214	-0.723277
69	94.31	95.7494	95.7242	0.025204	-1.43937
70	96.05	95.9296	95.7288	0.200881	0.120369
71	96.17	95.7668	95.7342	0.0325998	0.403234
72	95.14	95.151	95.6992	-0.548129	-0.0110373
73	95.37	95.7254	95.6246	0.100829	-0.355412
74	96.5	96.3304	95.685	0.64536	0.16964
75	96.79	96.8305	95.9796	0.850933	-0.0405165
76	96.23	96.6996	96.3571	0.342496	-0.469579
77	96	96.633	96.7	-0.0670356	-0.632964
78	95.21	96.8181	97.0671	-0.248963	-1.60812
79	94.77	96.6621	97.4842	-0.822036	-1.89213
80	96.84	97.3729	97.885	-0.51214	-0.53286
81	99.06	98.3194	98.2942	0.025204	0.740629
82	100.36	98.94	98.7392	0.200881	1.41995
83	100.09	99.1955	99.1629	0.0325998	0.894484
84	100.03	99.0506	99.5987	-0.548129	0.979379
85	100.49	100.135	100.034	0.100829	0.355004
86	101	101.02	100.375	0.64536	-0.0199436
87	102.11	101.392	100.541	0.850933	0.718234
88	101.59	100.827	100.484	0.342496	0.763338
89	100.81	100.245	100.312	-0.0670356	0.565369
90	100.86	99.8619	100.111	-0.248963	0.998129
91	99.57	99.1192	99.9413	-0.822036	0.450786
92	100.21	99.2933	99.8054	-0.51214	0.916723
93	99.68	99.6423	99.6171	0.025204	0.0377127
94	98.38	99.6188	99.4179	0.200881	-1.2388
95	97.93	99.313	99.2804	0.0325998	-1.38302
96	97.37	98.6031	99.1512	-0.548129	-1.23312
97	99.08	99.1662	99.0654	0.100829	-0.0862457
98	99.15	99.6891	99.0438	0.64536	-0.53911
99	99.44	99.8622	99.0112	0.850933	-0.422183
100	99.48	99.3692	99.0267	0.342496	0.110838
101	99.62	99.0384	99.1054	-0.0670356	0.581619
102	98.95	98.9965	99.2454	-0.248963	-0.046454
103	99.42	NA	NA	-0.822036	NA
104	99.84	NA	NA	-0.51214	NA
105	99.27	NA	NA	0.025204	NA
106	99.16	NA	NA	0.200881	NA
107	99.04	NA	NA	0.0325998	NA
108	99.62	NA	NA	-0.548129	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 78.25 & NA & NA & 0.100829 & NA \tabularnewline
2 & 77.24 & NA & NA & 0.64536 & NA \tabularnewline
3 & 76.68 & NA & NA & 0.850933 & NA \tabularnewline
4 & 76.29 & NA & NA & 0.342496 & NA \tabularnewline
5 & 76.1 & NA & NA & -0.0670356 & NA \tabularnewline
6 & 75.77 & NA & NA & -0.248963 & NA \tabularnewline
7 & 75.6 & 75.6563 & 76.4783 & -0.822036 & -0.0562977 \tabularnewline
8 & 75.57 & 76.1512 & 76.6633 & -0.51214 & -0.581194 \tabularnewline
9 & 75.89 & 77.0527 & 77.0275 & 0.025204 & -1.1627 \tabularnewline
10 & 76.04 & 77.6855 & 77.4846 & 0.200881 & -1.64546 \tabularnewline
11 & 76.89 & 77.9647 & 77.9321 & 0.0325998 & -1.07468 \tabularnewline
12 & 77 & 77.8573 & 78.4054 & -0.548129 & -0.857287 \tabularnewline
13 & 79.09 & 79.0404 & 78.9396 & 0.100829 & 0.0495877 \tabularnewline
14 & 80.84 & 80.1358 & 79.4904 & 0.64536 & 0.704223 \tabularnewline
15 & 81.82 & 80.9134 & 80.0625 & 0.850933 & 0.906567 \tabularnewline
16 & 82.12 & 80.9592 & 80.6167 & 0.342496 & 1.16084 \tabularnewline
17 & 81.01 & 81.0863 & 81.1533 & -0.0670356 & -0.0762977 \tabularnewline
18 & 82.22 & 81.4765 & 81.7254 & -0.248963 & 0.743546 \tabularnewline
19 & 81.97 & 81.55 & 82.3721 & -0.822036 & 0.419952 \tabularnewline
20 & 82.42 & 82.6283 & 83.1404 & -0.51214 & -0.208277 \tabularnewline
21 & 82.77 & 84.0777 & 84.0525 & 0.025204 & -1.3077 \tabularnewline
22 & 82.46 & 85.2459 & 85.045 & 0.200881 & -2.78588 \tabularnewline
23 & 83.35 & 86.1622 & 86.1296 & 0.0325998 & -2.81218 \tabularnewline
24 & 84.27 & 86.714 & 87.2621 & -0.548129 & -2.44395 \tabularnewline
25 & 87.34 & 88.5233 & 88.4225 & 0.100829 & -1.18333 \tabularnewline
26 & 91.03 & 90.3274 & 89.6821 & 0.64536 & 0.702556 \tabularnewline
27 & 93.52 & 92.0226 & 91.1717 & 0.850933 & 1.4974 \tabularnewline
28 & 94.24 & 93.2542 & 92.9117 & 0.342496 & 0.985838 \tabularnewline
29 & 94.92 & 94.5863 & 94.6533 & -0.0670356 & 0.333702 \tabularnewline
30 & 95.49 & 96.0369 & 96.2858 & -0.248963 & -0.546871 \tabularnewline
31 & 96.55 & 96.948 & 97.77 & -0.822036 & -0.397964 \tabularnewline
32 & 98.07 & 98.4762 & 98.9883 & -0.51214 & -0.406194 \tabularnewline
33 & 102.87 & 99.9531 & 99.9279 & 0.025204 & 2.91688 \tabularnewline
34 & 104.12 & 100.899 & 100.698 & 0.200881 & 3.2212 \tabularnewline
35 & 103.49 & 101.425 & 101.392 & 0.0325998 & 2.0649 \tabularnewline
36 & 103.31 & 101.511 & 102.06 & -0.548129 & 1.79855 \tabularnewline
37 & 103.92 & 102.742 & 102.641 & 0.100829 & 1.17834 \tabularnewline
38 & 103.69 & 103.731 & 103.085 & 0.64536 & -0.0407769 \tabularnewline
39 & 103.41 & 104.103 & 103.252 & 0.850933 & -0.693016 \tabularnewline
40 & 102.83 & 103.492 & 103.15 & 0.342496 & -0.662496 \tabularnewline
41 & 103 & 102.966 & 103.033 & -0.0670356 & 0.0341189 \tabularnewline
42 & 103.42 & 102.669 & 102.918 & -0.248963 & 0.751046 \tabularnewline
43 & 102.57 & 101.902 & 102.724 & -0.822036 & 0.667869 \tabularnewline
44 & 102.72 & 101.996 & 102.508 & -0.51214 & 0.723806 \tabularnewline
45 & 102.22 & 102.327 & 102.302 & 0.025204 & -0.107287 \tabularnewline
46 & 102.32 & 102.264 & 102.063 & 0.200881 & 0.0562023 \tabularnewline
47 & 102.48 & 101.833 & 101.8 & 0.0325998 & 0.6474 \tabularnewline
48 & 101.56 & 100.94 & 101.488 & -0.548129 & 0.620213 \tabularnewline
49 & 101.02 & 101.267 & 101.167 & 0.100829 & -0.247496 \tabularnewline
50 & 101.41 & 101.542 & 100.896 & 0.64536 & -0.13161 \tabularnewline
51 & 100.74 & 101.503 & 100.653 & 0.850933 & -0.763433 \tabularnewline
52 & 99.76 & 100.772 & 100.43 & 0.342496 & -1.01208 \tabularnewline
53 & 99.76 & 100.142 & 100.209 & -0.0670356 & -0.382131 \tabularnewline
54 & 99.17 & 99.7277 & 99.9767 & -0.248963 & -0.557704 \tabularnewline
55 & 99.11 & 98.9221 & 99.7442 & -0.822036 & 0.187869 \tabularnewline
56 & 99.69 & 98.9462 & 99.4583 & -0.51214 & 0.743806 \tabularnewline
57 & 99.4 & 99.1456 & 99.1204 & 0.025204 & 0.254379 \tabularnewline
58 & 99.79 & 99.005 & 98.8042 & 0.200881 & 0.784952 \tabularnewline
59 & 99.72 & 98.5276 & 98.495 & 0.0325998 & 1.1924 \tabularnewline
60 & 98.74 & 97.6602 & 98.2083 & -0.548129 & 1.0798 \tabularnewline
61 & 98.26 & 98.0379 & 97.9371 & 0.100829 & 0.222088 \tabularnewline
62 & 97.31 & 98.2224 & 97.5771 & 0.64536 & -0.912444 \tabularnewline
63 & 96.73 & 98.0005 & 97.1496 & 0.850933 & -1.27052 \tabularnewline
64 & 96.18 & 97.1242 & 96.7817 & 0.342496 & -0.944162 \tabularnewline
65 & 95.92 & 96.4109 & 96.4779 & -0.0670356 & -0.490881 \tabularnewline
66 & 96.13 & 95.931 & 96.18 & -0.248963 & 0.198963 \tabularnewline
67 & 95.64 & 95.0875 & 95.9096 & -0.822036 & 0.552452 \tabularnewline
68 & 94.52 & 95.2433 & 95.7554 & -0.51214 & -0.723277 \tabularnewline
69 & 94.31 & 95.7494 & 95.7242 & 0.025204 & -1.43937 \tabularnewline
70 & 96.05 & 95.9296 & 95.7288 & 0.200881 & 0.120369 \tabularnewline
71 & 96.17 & 95.7668 & 95.7342 & 0.0325998 & 0.403234 \tabularnewline
72 & 95.14 & 95.151 & 95.6992 & -0.548129 & -0.0110373 \tabularnewline
73 & 95.37 & 95.7254 & 95.6246 & 0.100829 & -0.355412 \tabularnewline
74 & 96.5 & 96.3304 & 95.685 & 0.64536 & 0.16964 \tabularnewline
75 & 96.79 & 96.8305 & 95.9796 & 0.850933 & -0.0405165 \tabularnewline
76 & 96.23 & 96.6996 & 96.3571 & 0.342496 & -0.469579 \tabularnewline
77 & 96 & 96.633 & 96.7 & -0.0670356 & -0.632964 \tabularnewline
78 & 95.21 & 96.8181 & 97.0671 & -0.248963 & -1.60812 \tabularnewline
79 & 94.77 & 96.6621 & 97.4842 & -0.822036 & -1.89213 \tabularnewline
80 & 96.84 & 97.3729 & 97.885 & -0.51214 & -0.53286 \tabularnewline
81 & 99.06 & 98.3194 & 98.2942 & 0.025204 & 0.740629 \tabularnewline
82 & 100.36 & 98.94 & 98.7392 & 0.200881 & 1.41995 \tabularnewline
83 & 100.09 & 99.1955 & 99.1629 & 0.0325998 & 0.894484 \tabularnewline
84 & 100.03 & 99.0506 & 99.5987 & -0.548129 & 0.979379 \tabularnewline
85 & 100.49 & 100.135 & 100.034 & 0.100829 & 0.355004 \tabularnewline
86 & 101 & 101.02 & 100.375 & 0.64536 & -0.0199436 \tabularnewline
87 & 102.11 & 101.392 & 100.541 & 0.850933 & 0.718234 \tabularnewline
88 & 101.59 & 100.827 & 100.484 & 0.342496 & 0.763338 \tabularnewline
89 & 100.81 & 100.245 & 100.312 & -0.0670356 & 0.565369 \tabularnewline
90 & 100.86 & 99.8619 & 100.111 & -0.248963 & 0.998129 \tabularnewline
91 & 99.57 & 99.1192 & 99.9413 & -0.822036 & 0.450786 \tabularnewline
92 & 100.21 & 99.2933 & 99.8054 & -0.51214 & 0.916723 \tabularnewline
93 & 99.68 & 99.6423 & 99.6171 & 0.025204 & 0.0377127 \tabularnewline
94 & 98.38 & 99.6188 & 99.4179 & 0.200881 & -1.2388 \tabularnewline
95 & 97.93 & 99.313 & 99.2804 & 0.0325998 & -1.38302 \tabularnewline
96 & 97.37 & 98.6031 & 99.1512 & -0.548129 & -1.23312 \tabularnewline
97 & 99.08 & 99.1662 & 99.0654 & 0.100829 & -0.0862457 \tabularnewline
98 & 99.15 & 99.6891 & 99.0438 & 0.64536 & -0.53911 \tabularnewline
99 & 99.44 & 99.8622 & 99.0112 & 0.850933 & -0.422183 \tabularnewline
100 & 99.48 & 99.3692 & 99.0267 & 0.342496 & 0.110838 \tabularnewline
101 & 99.62 & 99.0384 & 99.1054 & -0.0670356 & 0.581619 \tabularnewline
102 & 98.95 & 98.9965 & 99.2454 & -0.248963 & -0.046454 \tabularnewline
103 & 99.42 & NA & NA & -0.822036 & NA \tabularnewline
104 & 99.84 & NA & NA & -0.51214 & NA \tabularnewline
105 & 99.27 & NA & NA & 0.025204 & NA \tabularnewline
106 & 99.16 & NA & NA & 0.200881 & NA \tabularnewline
107 & 99.04 & NA & NA & 0.0325998 & NA \tabularnewline
108 & 99.62 & NA & NA & -0.548129 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283926&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]78.25[/C][C]NA[/C][C]NA[/C][C]0.100829[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]77.24[/C][C]NA[/C][C]NA[/C][C]0.64536[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]76.68[/C][C]NA[/C][C]NA[/C][C]0.850933[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]76.29[/C][C]NA[/C][C]NA[/C][C]0.342496[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]76.1[/C][C]NA[/C][C]NA[/C][C]-0.0670356[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]75.77[/C][C]NA[/C][C]NA[/C][C]-0.248963[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]75.6[/C][C]75.6563[/C][C]76.4783[/C][C]-0.822036[/C][C]-0.0562977[/C][/ROW]
[ROW][C]8[/C][C]75.57[/C][C]76.1512[/C][C]76.6633[/C][C]-0.51214[/C][C]-0.581194[/C][/ROW]
[ROW][C]9[/C][C]75.89[/C][C]77.0527[/C][C]77.0275[/C][C]0.025204[/C][C]-1.1627[/C][/ROW]
[ROW][C]10[/C][C]76.04[/C][C]77.6855[/C][C]77.4846[/C][C]0.200881[/C][C]-1.64546[/C][/ROW]
[ROW][C]11[/C][C]76.89[/C][C]77.9647[/C][C]77.9321[/C][C]0.0325998[/C][C]-1.07468[/C][/ROW]
[ROW][C]12[/C][C]77[/C][C]77.8573[/C][C]78.4054[/C][C]-0.548129[/C][C]-0.857287[/C][/ROW]
[ROW][C]13[/C][C]79.09[/C][C]79.0404[/C][C]78.9396[/C][C]0.100829[/C][C]0.0495877[/C][/ROW]
[ROW][C]14[/C][C]80.84[/C][C]80.1358[/C][C]79.4904[/C][C]0.64536[/C][C]0.704223[/C][/ROW]
[ROW][C]15[/C][C]81.82[/C][C]80.9134[/C][C]80.0625[/C][C]0.850933[/C][C]0.906567[/C][/ROW]
[ROW][C]16[/C][C]82.12[/C][C]80.9592[/C][C]80.6167[/C][C]0.342496[/C][C]1.16084[/C][/ROW]
[ROW][C]17[/C][C]81.01[/C][C]81.0863[/C][C]81.1533[/C][C]-0.0670356[/C][C]-0.0762977[/C][/ROW]
[ROW][C]18[/C][C]82.22[/C][C]81.4765[/C][C]81.7254[/C][C]-0.248963[/C][C]0.743546[/C][/ROW]
[ROW][C]19[/C][C]81.97[/C][C]81.55[/C][C]82.3721[/C][C]-0.822036[/C][C]0.419952[/C][/ROW]
[ROW][C]20[/C][C]82.42[/C][C]82.6283[/C][C]83.1404[/C][C]-0.51214[/C][C]-0.208277[/C][/ROW]
[ROW][C]21[/C][C]82.77[/C][C]84.0777[/C][C]84.0525[/C][C]0.025204[/C][C]-1.3077[/C][/ROW]
[ROW][C]22[/C][C]82.46[/C][C]85.2459[/C][C]85.045[/C][C]0.200881[/C][C]-2.78588[/C][/ROW]
[ROW][C]23[/C][C]83.35[/C][C]86.1622[/C][C]86.1296[/C][C]0.0325998[/C][C]-2.81218[/C][/ROW]
[ROW][C]24[/C][C]84.27[/C][C]86.714[/C][C]87.2621[/C][C]-0.548129[/C][C]-2.44395[/C][/ROW]
[ROW][C]25[/C][C]87.34[/C][C]88.5233[/C][C]88.4225[/C][C]0.100829[/C][C]-1.18333[/C][/ROW]
[ROW][C]26[/C][C]91.03[/C][C]90.3274[/C][C]89.6821[/C][C]0.64536[/C][C]0.702556[/C][/ROW]
[ROW][C]27[/C][C]93.52[/C][C]92.0226[/C][C]91.1717[/C][C]0.850933[/C][C]1.4974[/C][/ROW]
[ROW][C]28[/C][C]94.24[/C][C]93.2542[/C][C]92.9117[/C][C]0.342496[/C][C]0.985838[/C][/ROW]
[ROW][C]29[/C][C]94.92[/C][C]94.5863[/C][C]94.6533[/C][C]-0.0670356[/C][C]0.333702[/C][/ROW]
[ROW][C]30[/C][C]95.49[/C][C]96.0369[/C][C]96.2858[/C][C]-0.248963[/C][C]-0.546871[/C][/ROW]
[ROW][C]31[/C][C]96.55[/C][C]96.948[/C][C]97.77[/C][C]-0.822036[/C][C]-0.397964[/C][/ROW]
[ROW][C]32[/C][C]98.07[/C][C]98.4762[/C][C]98.9883[/C][C]-0.51214[/C][C]-0.406194[/C][/ROW]
[ROW][C]33[/C][C]102.87[/C][C]99.9531[/C][C]99.9279[/C][C]0.025204[/C][C]2.91688[/C][/ROW]
[ROW][C]34[/C][C]104.12[/C][C]100.899[/C][C]100.698[/C][C]0.200881[/C][C]3.2212[/C][/ROW]
[ROW][C]35[/C][C]103.49[/C][C]101.425[/C][C]101.392[/C][C]0.0325998[/C][C]2.0649[/C][/ROW]
[ROW][C]36[/C][C]103.31[/C][C]101.511[/C][C]102.06[/C][C]-0.548129[/C][C]1.79855[/C][/ROW]
[ROW][C]37[/C][C]103.92[/C][C]102.742[/C][C]102.641[/C][C]0.100829[/C][C]1.17834[/C][/ROW]
[ROW][C]38[/C][C]103.69[/C][C]103.731[/C][C]103.085[/C][C]0.64536[/C][C]-0.0407769[/C][/ROW]
[ROW][C]39[/C][C]103.41[/C][C]104.103[/C][C]103.252[/C][C]0.850933[/C][C]-0.693016[/C][/ROW]
[ROW][C]40[/C][C]102.83[/C][C]103.492[/C][C]103.15[/C][C]0.342496[/C][C]-0.662496[/C][/ROW]
[ROW][C]41[/C][C]103[/C][C]102.966[/C][C]103.033[/C][C]-0.0670356[/C][C]0.0341189[/C][/ROW]
[ROW][C]42[/C][C]103.42[/C][C]102.669[/C][C]102.918[/C][C]-0.248963[/C][C]0.751046[/C][/ROW]
[ROW][C]43[/C][C]102.57[/C][C]101.902[/C][C]102.724[/C][C]-0.822036[/C][C]0.667869[/C][/ROW]
[ROW][C]44[/C][C]102.72[/C][C]101.996[/C][C]102.508[/C][C]-0.51214[/C][C]0.723806[/C][/ROW]
[ROW][C]45[/C][C]102.22[/C][C]102.327[/C][C]102.302[/C][C]0.025204[/C][C]-0.107287[/C][/ROW]
[ROW][C]46[/C][C]102.32[/C][C]102.264[/C][C]102.063[/C][C]0.200881[/C][C]0.0562023[/C][/ROW]
[ROW][C]47[/C][C]102.48[/C][C]101.833[/C][C]101.8[/C][C]0.0325998[/C][C]0.6474[/C][/ROW]
[ROW][C]48[/C][C]101.56[/C][C]100.94[/C][C]101.488[/C][C]-0.548129[/C][C]0.620213[/C][/ROW]
[ROW][C]49[/C][C]101.02[/C][C]101.267[/C][C]101.167[/C][C]0.100829[/C][C]-0.247496[/C][/ROW]
[ROW][C]50[/C][C]101.41[/C][C]101.542[/C][C]100.896[/C][C]0.64536[/C][C]-0.13161[/C][/ROW]
[ROW][C]51[/C][C]100.74[/C][C]101.503[/C][C]100.653[/C][C]0.850933[/C][C]-0.763433[/C][/ROW]
[ROW][C]52[/C][C]99.76[/C][C]100.772[/C][C]100.43[/C][C]0.342496[/C][C]-1.01208[/C][/ROW]
[ROW][C]53[/C][C]99.76[/C][C]100.142[/C][C]100.209[/C][C]-0.0670356[/C][C]-0.382131[/C][/ROW]
[ROW][C]54[/C][C]99.17[/C][C]99.7277[/C][C]99.9767[/C][C]-0.248963[/C][C]-0.557704[/C][/ROW]
[ROW][C]55[/C][C]99.11[/C][C]98.9221[/C][C]99.7442[/C][C]-0.822036[/C][C]0.187869[/C][/ROW]
[ROW][C]56[/C][C]99.69[/C][C]98.9462[/C][C]99.4583[/C][C]-0.51214[/C][C]0.743806[/C][/ROW]
[ROW][C]57[/C][C]99.4[/C][C]99.1456[/C][C]99.1204[/C][C]0.025204[/C][C]0.254379[/C][/ROW]
[ROW][C]58[/C][C]99.79[/C][C]99.005[/C][C]98.8042[/C][C]0.200881[/C][C]0.784952[/C][/ROW]
[ROW][C]59[/C][C]99.72[/C][C]98.5276[/C][C]98.495[/C][C]0.0325998[/C][C]1.1924[/C][/ROW]
[ROW][C]60[/C][C]98.74[/C][C]97.6602[/C][C]98.2083[/C][C]-0.548129[/C][C]1.0798[/C][/ROW]
[ROW][C]61[/C][C]98.26[/C][C]98.0379[/C][C]97.9371[/C][C]0.100829[/C][C]0.222088[/C][/ROW]
[ROW][C]62[/C][C]97.31[/C][C]98.2224[/C][C]97.5771[/C][C]0.64536[/C][C]-0.912444[/C][/ROW]
[ROW][C]63[/C][C]96.73[/C][C]98.0005[/C][C]97.1496[/C][C]0.850933[/C][C]-1.27052[/C][/ROW]
[ROW][C]64[/C][C]96.18[/C][C]97.1242[/C][C]96.7817[/C][C]0.342496[/C][C]-0.944162[/C][/ROW]
[ROW][C]65[/C][C]95.92[/C][C]96.4109[/C][C]96.4779[/C][C]-0.0670356[/C][C]-0.490881[/C][/ROW]
[ROW][C]66[/C][C]96.13[/C][C]95.931[/C][C]96.18[/C][C]-0.248963[/C][C]0.198963[/C][/ROW]
[ROW][C]67[/C][C]95.64[/C][C]95.0875[/C][C]95.9096[/C][C]-0.822036[/C][C]0.552452[/C][/ROW]
[ROW][C]68[/C][C]94.52[/C][C]95.2433[/C][C]95.7554[/C][C]-0.51214[/C][C]-0.723277[/C][/ROW]
[ROW][C]69[/C][C]94.31[/C][C]95.7494[/C][C]95.7242[/C][C]0.025204[/C][C]-1.43937[/C][/ROW]
[ROW][C]70[/C][C]96.05[/C][C]95.9296[/C][C]95.7288[/C][C]0.200881[/C][C]0.120369[/C][/ROW]
[ROW][C]71[/C][C]96.17[/C][C]95.7668[/C][C]95.7342[/C][C]0.0325998[/C][C]0.403234[/C][/ROW]
[ROW][C]72[/C][C]95.14[/C][C]95.151[/C][C]95.6992[/C][C]-0.548129[/C][C]-0.0110373[/C][/ROW]
[ROW][C]73[/C][C]95.37[/C][C]95.7254[/C][C]95.6246[/C][C]0.100829[/C][C]-0.355412[/C][/ROW]
[ROW][C]74[/C][C]96.5[/C][C]96.3304[/C][C]95.685[/C][C]0.64536[/C][C]0.16964[/C][/ROW]
[ROW][C]75[/C][C]96.79[/C][C]96.8305[/C][C]95.9796[/C][C]0.850933[/C][C]-0.0405165[/C][/ROW]
[ROW][C]76[/C][C]96.23[/C][C]96.6996[/C][C]96.3571[/C][C]0.342496[/C][C]-0.469579[/C][/ROW]
[ROW][C]77[/C][C]96[/C][C]96.633[/C][C]96.7[/C][C]-0.0670356[/C][C]-0.632964[/C][/ROW]
[ROW][C]78[/C][C]95.21[/C][C]96.8181[/C][C]97.0671[/C][C]-0.248963[/C][C]-1.60812[/C][/ROW]
[ROW][C]79[/C][C]94.77[/C][C]96.6621[/C][C]97.4842[/C][C]-0.822036[/C][C]-1.89213[/C][/ROW]
[ROW][C]80[/C][C]96.84[/C][C]97.3729[/C][C]97.885[/C][C]-0.51214[/C][C]-0.53286[/C][/ROW]
[ROW][C]81[/C][C]99.06[/C][C]98.3194[/C][C]98.2942[/C][C]0.025204[/C][C]0.740629[/C][/ROW]
[ROW][C]82[/C][C]100.36[/C][C]98.94[/C][C]98.7392[/C][C]0.200881[/C][C]1.41995[/C][/ROW]
[ROW][C]83[/C][C]100.09[/C][C]99.1955[/C][C]99.1629[/C][C]0.0325998[/C][C]0.894484[/C][/ROW]
[ROW][C]84[/C][C]100.03[/C][C]99.0506[/C][C]99.5987[/C][C]-0.548129[/C][C]0.979379[/C][/ROW]
[ROW][C]85[/C][C]100.49[/C][C]100.135[/C][C]100.034[/C][C]0.100829[/C][C]0.355004[/C][/ROW]
[ROW][C]86[/C][C]101[/C][C]101.02[/C][C]100.375[/C][C]0.64536[/C][C]-0.0199436[/C][/ROW]
[ROW][C]87[/C][C]102.11[/C][C]101.392[/C][C]100.541[/C][C]0.850933[/C][C]0.718234[/C][/ROW]
[ROW][C]88[/C][C]101.59[/C][C]100.827[/C][C]100.484[/C][C]0.342496[/C][C]0.763338[/C][/ROW]
[ROW][C]89[/C][C]100.81[/C][C]100.245[/C][C]100.312[/C][C]-0.0670356[/C][C]0.565369[/C][/ROW]
[ROW][C]90[/C][C]100.86[/C][C]99.8619[/C][C]100.111[/C][C]-0.248963[/C][C]0.998129[/C][/ROW]
[ROW][C]91[/C][C]99.57[/C][C]99.1192[/C][C]99.9413[/C][C]-0.822036[/C][C]0.450786[/C][/ROW]
[ROW][C]92[/C][C]100.21[/C][C]99.2933[/C][C]99.8054[/C][C]-0.51214[/C][C]0.916723[/C][/ROW]
[ROW][C]93[/C][C]99.68[/C][C]99.6423[/C][C]99.6171[/C][C]0.025204[/C][C]0.0377127[/C][/ROW]
[ROW][C]94[/C][C]98.38[/C][C]99.6188[/C][C]99.4179[/C][C]0.200881[/C][C]-1.2388[/C][/ROW]
[ROW][C]95[/C][C]97.93[/C][C]99.313[/C][C]99.2804[/C][C]0.0325998[/C][C]-1.38302[/C][/ROW]
[ROW][C]96[/C][C]97.37[/C][C]98.6031[/C][C]99.1512[/C][C]-0.548129[/C][C]-1.23312[/C][/ROW]
[ROW][C]97[/C][C]99.08[/C][C]99.1662[/C][C]99.0654[/C][C]0.100829[/C][C]-0.0862457[/C][/ROW]
[ROW][C]98[/C][C]99.15[/C][C]99.6891[/C][C]99.0438[/C][C]0.64536[/C][C]-0.53911[/C][/ROW]
[ROW][C]99[/C][C]99.44[/C][C]99.8622[/C][C]99.0112[/C][C]0.850933[/C][C]-0.422183[/C][/ROW]
[ROW][C]100[/C][C]99.48[/C][C]99.3692[/C][C]99.0267[/C][C]0.342496[/C][C]0.110838[/C][/ROW]
[ROW][C]101[/C][C]99.62[/C][C]99.0384[/C][C]99.1054[/C][C]-0.0670356[/C][C]0.581619[/C][/ROW]
[ROW][C]102[/C][C]98.95[/C][C]98.9965[/C][C]99.2454[/C][C]-0.248963[/C][C]-0.046454[/C][/ROW]
[ROW][C]103[/C][C]99.42[/C][C]NA[/C][C]NA[/C][C]-0.822036[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]99.84[/C][C]NA[/C][C]NA[/C][C]-0.51214[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]99.27[/C][C]NA[/C][C]NA[/C][C]0.025204[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]99.16[/C][C]NA[/C][C]NA[/C][C]0.200881[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]99.04[/C][C]NA[/C][C]NA[/C][C]0.0325998[/C][C]NA[/C][/ROW]
[ROW][C]108[/C][C]99.62[/C][C]NA[/C][C]NA[/C][C]-0.548129[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283926&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283926&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	78.25	NA	NA	0.100829	NA
2	77.24	NA	NA	0.64536	NA
3	76.68	NA	NA	0.850933	NA
4	76.29	NA	NA	0.342496	NA
5	76.1	NA	NA	-0.0670356	NA
6	75.77	NA	NA	-0.248963	NA
7	75.6	75.6563	76.4783	-0.822036	-0.0562977
8	75.57	76.1512	76.6633	-0.51214	-0.581194
9	75.89	77.0527	77.0275	0.025204	-1.1627
10	76.04	77.6855	77.4846	0.200881	-1.64546
11	76.89	77.9647	77.9321	0.0325998	-1.07468
12	77	77.8573	78.4054	-0.548129	-0.857287
13	79.09	79.0404	78.9396	0.100829	0.0495877
14	80.84	80.1358	79.4904	0.64536	0.704223
15	81.82	80.9134	80.0625	0.850933	0.906567
16	82.12	80.9592	80.6167	0.342496	1.16084
17	81.01	81.0863	81.1533	-0.0670356	-0.0762977
18	82.22	81.4765	81.7254	-0.248963	0.743546
19	81.97	81.55	82.3721	-0.822036	0.419952
20	82.42	82.6283	83.1404	-0.51214	-0.208277
21	82.77	84.0777	84.0525	0.025204	-1.3077
22	82.46	85.2459	85.045	0.200881	-2.78588
23	83.35	86.1622	86.1296	0.0325998	-2.81218
24	84.27	86.714	87.2621	-0.548129	-2.44395
25	87.34	88.5233	88.4225	0.100829	-1.18333
26	91.03	90.3274	89.6821	0.64536	0.702556
27	93.52	92.0226	91.1717	0.850933	1.4974
28	94.24	93.2542	92.9117	0.342496	0.985838
29	94.92	94.5863	94.6533	-0.0670356	0.333702
30	95.49	96.0369	96.2858	-0.248963	-0.546871
31	96.55	96.948	97.77	-0.822036	-0.397964
32	98.07	98.4762	98.9883	-0.51214	-0.406194
33	102.87	99.9531	99.9279	0.025204	2.91688
34	104.12	100.899	100.698	0.200881	3.2212
35	103.49	101.425	101.392	0.0325998	2.0649
36	103.31	101.511	102.06	-0.548129	1.79855
37	103.92	102.742	102.641	0.100829	1.17834
38	103.69	103.731	103.085	0.64536	-0.0407769
39	103.41	104.103	103.252	0.850933	-0.693016
40	102.83	103.492	103.15	0.342496	-0.662496
41	103	102.966	103.033	-0.0670356	0.0341189
42	103.42	102.669	102.918	-0.248963	0.751046
43	102.57	101.902	102.724	-0.822036	0.667869
44	102.72	101.996	102.508	-0.51214	0.723806
45	102.22	102.327	102.302	0.025204	-0.107287
46	102.32	102.264	102.063	0.200881	0.0562023
47	102.48	101.833	101.8	0.0325998	0.6474
48	101.56	100.94	101.488	-0.548129	0.620213
49	101.02	101.267	101.167	0.100829	-0.247496
50	101.41	101.542	100.896	0.64536	-0.13161
51	100.74	101.503	100.653	0.850933	-0.763433
52	99.76	100.772	100.43	0.342496	-1.01208
53	99.76	100.142	100.209	-0.0670356	-0.382131
54	99.17	99.7277	99.9767	-0.248963	-0.557704
55	99.11	98.9221	99.7442	-0.822036	0.187869
56	99.69	98.9462	99.4583	-0.51214	0.743806
57	99.4	99.1456	99.1204	0.025204	0.254379
58	99.79	99.005	98.8042	0.200881	0.784952
59	99.72	98.5276	98.495	0.0325998	1.1924
60	98.74	97.6602	98.2083	-0.548129	1.0798
61	98.26	98.0379	97.9371	0.100829	0.222088
62	97.31	98.2224	97.5771	0.64536	-0.912444
63	96.73	98.0005	97.1496	0.850933	-1.27052
64	96.18	97.1242	96.7817	0.342496	-0.944162
65	95.92	96.4109	96.4779	-0.0670356	-0.490881
66	96.13	95.931	96.18	-0.248963	0.198963
67	95.64	95.0875	95.9096	-0.822036	0.552452
68	94.52	95.2433	95.7554	-0.51214	-0.723277
69	94.31	95.7494	95.7242	0.025204	-1.43937
70	96.05	95.9296	95.7288	0.200881	0.120369
71	96.17	95.7668	95.7342	0.0325998	0.403234
72	95.14	95.151	95.6992	-0.548129	-0.0110373
73	95.37	95.7254	95.6246	0.100829	-0.355412
74	96.5	96.3304	95.685	0.64536	0.16964
75	96.79	96.8305	95.9796	0.850933	-0.0405165
76	96.23	96.6996	96.3571	0.342496	-0.469579
77	96	96.633	96.7	-0.0670356	-0.632964
78	95.21	96.8181	97.0671	-0.248963	-1.60812
79	94.77	96.6621	97.4842	-0.822036	-1.89213
80	96.84	97.3729	97.885	-0.51214	-0.53286
81	99.06	98.3194	98.2942	0.025204	0.740629
82	100.36	98.94	98.7392	0.200881	1.41995
83	100.09	99.1955	99.1629	0.0325998	0.894484
84	100.03	99.0506	99.5987	-0.548129	0.979379
85	100.49	100.135	100.034	0.100829	0.355004
86	101	101.02	100.375	0.64536	-0.0199436
87	102.11	101.392	100.541	0.850933	0.718234
88	101.59	100.827	100.484	0.342496	0.763338
89	100.81	100.245	100.312	-0.0670356	0.565369
90	100.86	99.8619	100.111	-0.248963	0.998129
91	99.57	99.1192	99.9413	-0.822036	0.450786
92	100.21	99.2933	99.8054	-0.51214	0.916723
93	99.68	99.6423	99.6171	0.025204	0.0377127
94	98.38	99.6188	99.4179	0.200881	-1.2388
95	97.93	99.313	99.2804	0.0325998	-1.38302
96	97.37	98.6031	99.1512	-0.548129	-1.23312
97	99.08	99.1662	99.0654	0.100829	-0.0862457
98	99.15	99.6891	99.0438	0.64536	-0.53911
99	99.44	99.8622	99.0112	0.850933	-0.422183
100	99.48	99.3692	99.0267	0.342496	0.110838
101	99.62	99.0384	99.1054	-0.0670356	0.581619
102	98.95	98.9965	99.2454	-0.248963	-0.046454
103	99.42	NA	NA	-0.822036	NA
104	99.84	NA	NA	-0.51214	NA
105	99.27	NA	NA	0.025204	NA
106	99.16	NA	NA	0.200881	NA
107	99.04	NA	NA	0.0325998	NA
108	99.62	NA	NA	-0.548129	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