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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 26 Nov 2015 12:25:13 +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/26/t1448540734vvnmi5ui33o7t4w.htm/, Retrieved Tue, 14 May 2024 23:03:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284205, Retrieved Tue, 14 May 2024 23:03:14 +0000

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111

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-       [Classical Decomposition] [] [2015-11-26 12:25:13] [237b8e3b7b7bc12136ba0893525d9132] [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=284205&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=284205&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284205&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	71.83	NA	NA	2.60271	NA
2	71.39	NA	NA	2.39438	NA
3	73.71	NA	NA	0.948494	NA
4	74.13	NA	NA	-0.0683811	NA
5	74.45	NA	NA	-1.44875	NA
6	74.95	NA	NA	-2.4201	NA
7	75.09	72.5529	75.1158	-2.56291	2.53708
8	75.23	73.7112	75.5433	-1.83213	1.5188
9	76.11	75.1659	75.6025	-0.43661	0.94411
10	76.64	75.079	75.2179	-0.138954	1.56104
11	76.97	75.1763	74.6483	0.527921	1.79375
12	78.23	76.2702	73.8358	2.43433	1.95984
13	77.15	75.4506	72.8479	2.60271	1.69937
14	76.33	74.331	71.9367	2.39438	1.99895
15	70.19	72.0289	71.0804	0.948494	-1.83891
16	68.42	70.2104	70.2788	-0.0683811	-1.79037
17	66.49	68.3729	69.8217	-1.44875	-1.88292
18	63.41	67.3141	69.7342	-2.4201	-3.90407
19	62.92	67.3996	69.9625	-2.56291	-4.47959
20	65.53	68.7437	70.5758	-1.83213	-3.2137
21	65.26	71.3471	71.7837	-0.43661	-6.08714
22	68.25	73.3185	73.4575	-0.138954	-5.06855
23	74.39	75.7917	75.2637	0.527921	-1.40167
24	78.71	79.881	77.4467	2.43433	-1.17099
25	82.15	82.6219	80.0192	2.60271	-0.471879
26	86.05	85.0127	82.6183	2.39438	1.03729
27	89.46	86.4577	85.5092	0.948494	3.00234
28	89.32	88.5516	88.62	-0.0683811	0.768381
29	88.94	89.895	91.3438	-1.44875	-0.955004
30	93.35	91.4882	93.9083	-2.4201	1.86177
31	94.72	93.875	96.4379	-2.56291	0.844996
32	96.11	96.6979	98.53	-1.83213	-0.587869
33	104.06	99.2646	99.7012	-0.43661	4.79536
34	104.11	100.101	100.24	-0.138954	4.00854
35	103.9	101.104	100.576	0.527921	2.79583
36	110.75	102.353	99.9183	2.43433	8.39734
37	110.82	100.995	98.3921	2.60271	9.8252
38	107.59	99.2665	96.8721	2.39438	8.32354
39	96.03	95.8847	94.9362	0.948494	0.145256
40	95.69	92.4766	92.545	-0.0683811	3.21338
41	90.63	88.735	90.1838	-1.44875	1.895
42	75.87	85.1682	87.5883	-2.4201	-9.29823
43	75.57	82.2538	84.8167	-2.56291	-6.68375
44	78.78	80.4487	82.2808	-1.83213	-1.6687
45	74.93	80.0251	80.4617	-0.43661	-5.09506
46	75.85	79.0748	79.2137	-0.138954	-3.2248
47	75.49	78.7367	78.2088	0.527921	-3.24667
48	76.87	80.5293	78.095	2.43433	-3.65933
49	78.18	81.3202	78.7175	2.60271	-3.14021
50	79.37	81.7215	79.3271	2.39438	-2.35146
51	80.59	81.1989	80.2504	0.948494	-0.608911
52	81.18	81.4487	81.5171	-0.0683811	-0.268702
53	81.02	81.3188	82.7675	-1.44875	-0.298754
54	82.75	81.6345	84.0546	-2.4201	1.11552
55	83.63	82.7575	85.3204	-2.56291	0.872496
56	85.35	84.7025	86.5346	-1.83213	0.647548
57	90.52	87.3555	87.7921	-0.43661	3.16453
58	90.66	88.9273	89.0662	-0.138954	1.7327
59	90.69	90.8592	90.3312	0.527921	-0.169171
60	92.56	94.2539	91.8196	2.43433	-1.69391
61	92.87	96.0456	93.4429	2.60271	-3.17563
62	93.82	97.3398	94.9454	2.39438	-3.5198
63	96.32	97.2947	96.3462	0.948494	-0.974744
64	96.03	97.6175	97.6858	-0.0683811	-1.58745
65	96.53	97.5675	99.0162	-1.44875	-1.0375
66	102.96	97.9303	100.35	-2.4201	5.02968
67	102.38	99.1138	101.677	-2.56291	3.26625
68	102.66	101.199	103.031	-1.83213	1.46088
69	106.83	103.892	104.328	-0.43661	2.93828
70	106.5	105.398	105.537	-0.138954	1.10187
71	106.78	107.235	106.707	0.527921	-0.454588
72	108.49	109.976	107.542	2.43433	-1.48599
73	108.77	110.692	108.089	2.60271	-1.92188
74	110.43	111.025	108.631	2.39438	-0.595213
75	110.84	109.906	108.958	0.948494	0.933589
76	110.52	109.02	109.089	-0.0683811	1.49963
77	110.11	107.776	109.225	-1.44875	2.33375
78	109.42	106.844	109.264	-2.4201	2.57635
79	109.06	106.566	109.129	-2.56291	2.49375
80	108.98	106.803	108.635	-1.83213	2.17713
81	108.36	107.39	107.826	-0.43661	0.97036
82	108.11	106.871	107.01	-0.138954	1.23937
83	108.44	106.69	106.162	0.527921	1.74958
84	107.76	107.728	105.294	2.43433	0.0319227
85	106.27	107.067	104.465	2.60271	-0.797296
86	101.07	105.998	103.603	2.39438	-4.92771
87	100.79	103.676	102.727	0.948494	-2.88558
88	100.97	101.833	101.901	-0.0683811	-0.862869
89	99.33	99.6579	101.107	-1.44875	-0.327921
90	99.35	97.9362	100.356	-2.4201	1.41385
91	99.23	97.1375	99.7004	-2.56291	2.0925
92	98.14	97.5304	99.3625	-1.83213	0.609631
93	98.17	98.8567	99.2933	-0.43661	-0.686723
94	98.48	98.8865	99.0254	-0.138954	-0.406463
95	99	99.1233	98.5954	0.527921	-0.123338
96	99.19	100.625	98.1908	2.43433	-1.43516
97	99.1	100.174	97.5712	2.60271	-1.07396
98	100.13	99.1519	96.7575	2.39438	0.978121
99	100.07	96.8993	95.9508	0.948494	3.17067
100	95.26	95.2883	95.3567	-0.0683811	-0.0282856
101	94.72	93.5029	94.9517	-1.44875	1.21708
102	94.25	92.1012	94.5212	-2.4201	2.14885
103	89.46	NA	NA	-2.56291	NA
104	88.38	NA	NA	-1.83213	NA
105	88.57	NA	NA	-0.43661	NA
106	93.82	NA	NA	-0.138954	NA
107	93.94	NA	NA	0.527921	NA
108	93.92	NA	NA	2.43433	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 71.83 & NA & NA & 2.60271 & NA \tabularnewline
2 & 71.39 & NA & NA & 2.39438 & NA \tabularnewline
3 & 73.71 & NA & NA & 0.948494 & NA \tabularnewline
4 & 74.13 & NA & NA & -0.0683811 & NA \tabularnewline
5 & 74.45 & NA & NA & -1.44875 & NA \tabularnewline
6 & 74.95 & NA & NA & -2.4201 & NA \tabularnewline
7 & 75.09 & 72.5529 & 75.1158 & -2.56291 & 2.53708 \tabularnewline
8 & 75.23 & 73.7112 & 75.5433 & -1.83213 & 1.5188 \tabularnewline
9 & 76.11 & 75.1659 & 75.6025 & -0.43661 & 0.94411 \tabularnewline
10 & 76.64 & 75.079 & 75.2179 & -0.138954 & 1.56104 \tabularnewline
11 & 76.97 & 75.1763 & 74.6483 & 0.527921 & 1.79375 \tabularnewline
12 & 78.23 & 76.2702 & 73.8358 & 2.43433 & 1.95984 \tabularnewline
13 & 77.15 & 75.4506 & 72.8479 & 2.60271 & 1.69937 \tabularnewline
14 & 76.33 & 74.331 & 71.9367 & 2.39438 & 1.99895 \tabularnewline
15 & 70.19 & 72.0289 & 71.0804 & 0.948494 & -1.83891 \tabularnewline
16 & 68.42 & 70.2104 & 70.2788 & -0.0683811 & -1.79037 \tabularnewline
17 & 66.49 & 68.3729 & 69.8217 & -1.44875 & -1.88292 \tabularnewline
18 & 63.41 & 67.3141 & 69.7342 & -2.4201 & -3.90407 \tabularnewline
19 & 62.92 & 67.3996 & 69.9625 & -2.56291 & -4.47959 \tabularnewline
20 & 65.53 & 68.7437 & 70.5758 & -1.83213 & -3.2137 \tabularnewline
21 & 65.26 & 71.3471 & 71.7837 & -0.43661 & -6.08714 \tabularnewline
22 & 68.25 & 73.3185 & 73.4575 & -0.138954 & -5.06855 \tabularnewline
23 & 74.39 & 75.7917 & 75.2637 & 0.527921 & -1.40167 \tabularnewline
24 & 78.71 & 79.881 & 77.4467 & 2.43433 & -1.17099 \tabularnewline
25 & 82.15 & 82.6219 & 80.0192 & 2.60271 & -0.471879 \tabularnewline
26 & 86.05 & 85.0127 & 82.6183 & 2.39438 & 1.03729 \tabularnewline
27 & 89.46 & 86.4577 & 85.5092 & 0.948494 & 3.00234 \tabularnewline
28 & 89.32 & 88.5516 & 88.62 & -0.0683811 & 0.768381 \tabularnewline
29 & 88.94 & 89.895 & 91.3438 & -1.44875 & -0.955004 \tabularnewline
30 & 93.35 & 91.4882 & 93.9083 & -2.4201 & 1.86177 \tabularnewline
31 & 94.72 & 93.875 & 96.4379 & -2.56291 & 0.844996 \tabularnewline
32 & 96.11 & 96.6979 & 98.53 & -1.83213 & -0.587869 \tabularnewline
33 & 104.06 & 99.2646 & 99.7012 & -0.43661 & 4.79536 \tabularnewline
34 & 104.11 & 100.101 & 100.24 & -0.138954 & 4.00854 \tabularnewline
35 & 103.9 & 101.104 & 100.576 & 0.527921 & 2.79583 \tabularnewline
36 & 110.75 & 102.353 & 99.9183 & 2.43433 & 8.39734 \tabularnewline
37 & 110.82 & 100.995 & 98.3921 & 2.60271 & 9.8252 \tabularnewline
38 & 107.59 & 99.2665 & 96.8721 & 2.39438 & 8.32354 \tabularnewline
39 & 96.03 & 95.8847 & 94.9362 & 0.948494 & 0.145256 \tabularnewline
40 & 95.69 & 92.4766 & 92.545 & -0.0683811 & 3.21338 \tabularnewline
41 & 90.63 & 88.735 & 90.1838 & -1.44875 & 1.895 \tabularnewline
42 & 75.87 & 85.1682 & 87.5883 & -2.4201 & -9.29823 \tabularnewline
43 & 75.57 & 82.2538 & 84.8167 & -2.56291 & -6.68375 \tabularnewline
44 & 78.78 & 80.4487 & 82.2808 & -1.83213 & -1.6687 \tabularnewline
45 & 74.93 & 80.0251 & 80.4617 & -0.43661 & -5.09506 \tabularnewline
46 & 75.85 & 79.0748 & 79.2137 & -0.138954 & -3.2248 \tabularnewline
47 & 75.49 & 78.7367 & 78.2088 & 0.527921 & -3.24667 \tabularnewline
48 & 76.87 & 80.5293 & 78.095 & 2.43433 & -3.65933 \tabularnewline
49 & 78.18 & 81.3202 & 78.7175 & 2.60271 & -3.14021 \tabularnewline
50 & 79.37 & 81.7215 & 79.3271 & 2.39438 & -2.35146 \tabularnewline
51 & 80.59 & 81.1989 & 80.2504 & 0.948494 & -0.608911 \tabularnewline
52 & 81.18 & 81.4487 & 81.5171 & -0.0683811 & -0.268702 \tabularnewline
53 & 81.02 & 81.3188 & 82.7675 & -1.44875 & -0.298754 \tabularnewline
54 & 82.75 & 81.6345 & 84.0546 & -2.4201 & 1.11552 \tabularnewline
55 & 83.63 & 82.7575 & 85.3204 & -2.56291 & 0.872496 \tabularnewline
56 & 85.35 & 84.7025 & 86.5346 & -1.83213 & 0.647548 \tabularnewline
57 & 90.52 & 87.3555 & 87.7921 & -0.43661 & 3.16453 \tabularnewline
58 & 90.66 & 88.9273 & 89.0662 & -0.138954 & 1.7327 \tabularnewline
59 & 90.69 & 90.8592 & 90.3312 & 0.527921 & -0.169171 \tabularnewline
60 & 92.56 & 94.2539 & 91.8196 & 2.43433 & -1.69391 \tabularnewline
61 & 92.87 & 96.0456 & 93.4429 & 2.60271 & -3.17563 \tabularnewline
62 & 93.82 & 97.3398 & 94.9454 & 2.39438 & -3.5198 \tabularnewline
63 & 96.32 & 97.2947 & 96.3462 & 0.948494 & -0.974744 \tabularnewline
64 & 96.03 & 97.6175 & 97.6858 & -0.0683811 & -1.58745 \tabularnewline
65 & 96.53 & 97.5675 & 99.0162 & -1.44875 & -1.0375 \tabularnewline
66 & 102.96 & 97.9303 & 100.35 & -2.4201 & 5.02968 \tabularnewline
67 & 102.38 & 99.1138 & 101.677 & -2.56291 & 3.26625 \tabularnewline
68 & 102.66 & 101.199 & 103.031 & -1.83213 & 1.46088 \tabularnewline
69 & 106.83 & 103.892 & 104.328 & -0.43661 & 2.93828 \tabularnewline
70 & 106.5 & 105.398 & 105.537 & -0.138954 & 1.10187 \tabularnewline
71 & 106.78 & 107.235 & 106.707 & 0.527921 & -0.454588 \tabularnewline
72 & 108.49 & 109.976 & 107.542 & 2.43433 & -1.48599 \tabularnewline
73 & 108.77 & 110.692 & 108.089 & 2.60271 & -1.92188 \tabularnewline
74 & 110.43 & 111.025 & 108.631 & 2.39438 & -0.595213 \tabularnewline
75 & 110.84 & 109.906 & 108.958 & 0.948494 & 0.933589 \tabularnewline
76 & 110.52 & 109.02 & 109.089 & -0.0683811 & 1.49963 \tabularnewline
77 & 110.11 & 107.776 & 109.225 & -1.44875 & 2.33375 \tabularnewline
78 & 109.42 & 106.844 & 109.264 & -2.4201 & 2.57635 \tabularnewline
79 & 109.06 & 106.566 & 109.129 & -2.56291 & 2.49375 \tabularnewline
80 & 108.98 & 106.803 & 108.635 & -1.83213 & 2.17713 \tabularnewline
81 & 108.36 & 107.39 & 107.826 & -0.43661 & 0.97036 \tabularnewline
82 & 108.11 & 106.871 & 107.01 & -0.138954 & 1.23937 \tabularnewline
83 & 108.44 & 106.69 & 106.162 & 0.527921 & 1.74958 \tabularnewline
84 & 107.76 & 107.728 & 105.294 & 2.43433 & 0.0319227 \tabularnewline
85 & 106.27 & 107.067 & 104.465 & 2.60271 & -0.797296 \tabularnewline
86 & 101.07 & 105.998 & 103.603 & 2.39438 & -4.92771 \tabularnewline
87 & 100.79 & 103.676 & 102.727 & 0.948494 & -2.88558 \tabularnewline
88 & 100.97 & 101.833 & 101.901 & -0.0683811 & -0.862869 \tabularnewline
89 & 99.33 & 99.6579 & 101.107 & -1.44875 & -0.327921 \tabularnewline
90 & 99.35 & 97.9362 & 100.356 & -2.4201 & 1.41385 \tabularnewline
91 & 99.23 & 97.1375 & 99.7004 & -2.56291 & 2.0925 \tabularnewline
92 & 98.14 & 97.5304 & 99.3625 & -1.83213 & 0.609631 \tabularnewline
93 & 98.17 & 98.8567 & 99.2933 & -0.43661 & -0.686723 \tabularnewline
94 & 98.48 & 98.8865 & 99.0254 & -0.138954 & -0.406463 \tabularnewline
95 & 99 & 99.1233 & 98.5954 & 0.527921 & -0.123338 \tabularnewline
96 & 99.19 & 100.625 & 98.1908 & 2.43433 & -1.43516 \tabularnewline
97 & 99.1 & 100.174 & 97.5712 & 2.60271 & -1.07396 \tabularnewline
98 & 100.13 & 99.1519 & 96.7575 & 2.39438 & 0.978121 \tabularnewline
99 & 100.07 & 96.8993 & 95.9508 & 0.948494 & 3.17067 \tabularnewline
100 & 95.26 & 95.2883 & 95.3567 & -0.0683811 & -0.0282856 \tabularnewline
101 & 94.72 & 93.5029 & 94.9517 & -1.44875 & 1.21708 \tabularnewline
102 & 94.25 & 92.1012 & 94.5212 & -2.4201 & 2.14885 \tabularnewline
103 & 89.46 & NA & NA & -2.56291 & NA \tabularnewline
104 & 88.38 & NA & NA & -1.83213 & NA \tabularnewline
105 & 88.57 & NA & NA & -0.43661 & NA \tabularnewline
106 & 93.82 & NA & NA & -0.138954 & NA \tabularnewline
107 & 93.94 & NA & NA & 0.527921 & NA \tabularnewline
108 & 93.92 & NA & NA & 2.43433 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284205&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]71.83[/C][C]NA[/C][C]NA[/C][C]2.60271[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]71.39[/C][C]NA[/C][C]NA[/C][C]2.39438[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]73.71[/C][C]NA[/C][C]NA[/C][C]0.948494[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]74.13[/C][C]NA[/C][C]NA[/C][C]-0.0683811[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]74.45[/C][C]NA[/C][C]NA[/C][C]-1.44875[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]74.95[/C][C]NA[/C][C]NA[/C][C]-2.4201[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]75.09[/C][C]72.5529[/C][C]75.1158[/C][C]-2.56291[/C][C]2.53708[/C][/ROW]
[ROW][C]8[/C][C]75.23[/C][C]73.7112[/C][C]75.5433[/C][C]-1.83213[/C][C]1.5188[/C][/ROW]
[ROW][C]9[/C][C]76.11[/C][C]75.1659[/C][C]75.6025[/C][C]-0.43661[/C][C]0.94411[/C][/ROW]
[ROW][C]10[/C][C]76.64[/C][C]75.079[/C][C]75.2179[/C][C]-0.138954[/C][C]1.56104[/C][/ROW]
[ROW][C]11[/C][C]76.97[/C][C]75.1763[/C][C]74.6483[/C][C]0.527921[/C][C]1.79375[/C][/ROW]
[ROW][C]12[/C][C]78.23[/C][C]76.2702[/C][C]73.8358[/C][C]2.43433[/C][C]1.95984[/C][/ROW]
[ROW][C]13[/C][C]77.15[/C][C]75.4506[/C][C]72.8479[/C][C]2.60271[/C][C]1.69937[/C][/ROW]
[ROW][C]14[/C][C]76.33[/C][C]74.331[/C][C]71.9367[/C][C]2.39438[/C][C]1.99895[/C][/ROW]
[ROW][C]15[/C][C]70.19[/C][C]72.0289[/C][C]71.0804[/C][C]0.948494[/C][C]-1.83891[/C][/ROW]
[ROW][C]16[/C][C]68.42[/C][C]70.2104[/C][C]70.2788[/C][C]-0.0683811[/C][C]-1.79037[/C][/ROW]
[ROW][C]17[/C][C]66.49[/C][C]68.3729[/C][C]69.8217[/C][C]-1.44875[/C][C]-1.88292[/C][/ROW]
[ROW][C]18[/C][C]63.41[/C][C]67.3141[/C][C]69.7342[/C][C]-2.4201[/C][C]-3.90407[/C][/ROW]
[ROW][C]19[/C][C]62.92[/C][C]67.3996[/C][C]69.9625[/C][C]-2.56291[/C][C]-4.47959[/C][/ROW]
[ROW][C]20[/C][C]65.53[/C][C]68.7437[/C][C]70.5758[/C][C]-1.83213[/C][C]-3.2137[/C][/ROW]
[ROW][C]21[/C][C]65.26[/C][C]71.3471[/C][C]71.7837[/C][C]-0.43661[/C][C]-6.08714[/C][/ROW]
[ROW][C]22[/C][C]68.25[/C][C]73.3185[/C][C]73.4575[/C][C]-0.138954[/C][C]-5.06855[/C][/ROW]
[ROW][C]23[/C][C]74.39[/C][C]75.7917[/C][C]75.2637[/C][C]0.527921[/C][C]-1.40167[/C][/ROW]
[ROW][C]24[/C][C]78.71[/C][C]79.881[/C][C]77.4467[/C][C]2.43433[/C][C]-1.17099[/C][/ROW]
[ROW][C]25[/C][C]82.15[/C][C]82.6219[/C][C]80.0192[/C][C]2.60271[/C][C]-0.471879[/C][/ROW]
[ROW][C]26[/C][C]86.05[/C][C]85.0127[/C][C]82.6183[/C][C]2.39438[/C][C]1.03729[/C][/ROW]
[ROW][C]27[/C][C]89.46[/C][C]86.4577[/C][C]85.5092[/C][C]0.948494[/C][C]3.00234[/C][/ROW]
[ROW][C]28[/C][C]89.32[/C][C]88.5516[/C][C]88.62[/C][C]-0.0683811[/C][C]0.768381[/C][/ROW]
[ROW][C]29[/C][C]88.94[/C][C]89.895[/C][C]91.3438[/C][C]-1.44875[/C][C]-0.955004[/C][/ROW]
[ROW][C]30[/C][C]93.35[/C][C]91.4882[/C][C]93.9083[/C][C]-2.4201[/C][C]1.86177[/C][/ROW]
[ROW][C]31[/C][C]94.72[/C][C]93.875[/C][C]96.4379[/C][C]-2.56291[/C][C]0.844996[/C][/ROW]
[ROW][C]32[/C][C]96.11[/C][C]96.6979[/C][C]98.53[/C][C]-1.83213[/C][C]-0.587869[/C][/ROW]
[ROW][C]33[/C][C]104.06[/C][C]99.2646[/C][C]99.7012[/C][C]-0.43661[/C][C]4.79536[/C][/ROW]
[ROW][C]34[/C][C]104.11[/C][C]100.101[/C][C]100.24[/C][C]-0.138954[/C][C]4.00854[/C][/ROW]
[ROW][C]35[/C][C]103.9[/C][C]101.104[/C][C]100.576[/C][C]0.527921[/C][C]2.79583[/C][/ROW]
[ROW][C]36[/C][C]110.75[/C][C]102.353[/C][C]99.9183[/C][C]2.43433[/C][C]8.39734[/C][/ROW]
[ROW][C]37[/C][C]110.82[/C][C]100.995[/C][C]98.3921[/C][C]2.60271[/C][C]9.8252[/C][/ROW]
[ROW][C]38[/C][C]107.59[/C][C]99.2665[/C][C]96.8721[/C][C]2.39438[/C][C]8.32354[/C][/ROW]
[ROW][C]39[/C][C]96.03[/C][C]95.8847[/C][C]94.9362[/C][C]0.948494[/C][C]0.145256[/C][/ROW]
[ROW][C]40[/C][C]95.69[/C][C]92.4766[/C][C]92.545[/C][C]-0.0683811[/C][C]3.21338[/C][/ROW]
[ROW][C]41[/C][C]90.63[/C][C]88.735[/C][C]90.1838[/C][C]-1.44875[/C][C]1.895[/C][/ROW]
[ROW][C]42[/C][C]75.87[/C][C]85.1682[/C][C]87.5883[/C][C]-2.4201[/C][C]-9.29823[/C][/ROW]
[ROW][C]43[/C][C]75.57[/C][C]82.2538[/C][C]84.8167[/C][C]-2.56291[/C][C]-6.68375[/C][/ROW]
[ROW][C]44[/C][C]78.78[/C][C]80.4487[/C][C]82.2808[/C][C]-1.83213[/C][C]-1.6687[/C][/ROW]
[ROW][C]45[/C][C]74.93[/C][C]80.0251[/C][C]80.4617[/C][C]-0.43661[/C][C]-5.09506[/C][/ROW]
[ROW][C]46[/C][C]75.85[/C][C]79.0748[/C][C]79.2137[/C][C]-0.138954[/C][C]-3.2248[/C][/ROW]
[ROW][C]47[/C][C]75.49[/C][C]78.7367[/C][C]78.2088[/C][C]0.527921[/C][C]-3.24667[/C][/ROW]
[ROW][C]48[/C][C]76.87[/C][C]80.5293[/C][C]78.095[/C][C]2.43433[/C][C]-3.65933[/C][/ROW]
[ROW][C]49[/C][C]78.18[/C][C]81.3202[/C][C]78.7175[/C][C]2.60271[/C][C]-3.14021[/C][/ROW]
[ROW][C]50[/C][C]79.37[/C][C]81.7215[/C][C]79.3271[/C][C]2.39438[/C][C]-2.35146[/C][/ROW]
[ROW][C]51[/C][C]80.59[/C][C]81.1989[/C][C]80.2504[/C][C]0.948494[/C][C]-0.608911[/C][/ROW]
[ROW][C]52[/C][C]81.18[/C][C]81.4487[/C][C]81.5171[/C][C]-0.0683811[/C][C]-0.268702[/C][/ROW]
[ROW][C]53[/C][C]81.02[/C][C]81.3188[/C][C]82.7675[/C][C]-1.44875[/C][C]-0.298754[/C][/ROW]
[ROW][C]54[/C][C]82.75[/C][C]81.6345[/C][C]84.0546[/C][C]-2.4201[/C][C]1.11552[/C][/ROW]
[ROW][C]55[/C][C]83.63[/C][C]82.7575[/C][C]85.3204[/C][C]-2.56291[/C][C]0.872496[/C][/ROW]
[ROW][C]56[/C][C]85.35[/C][C]84.7025[/C][C]86.5346[/C][C]-1.83213[/C][C]0.647548[/C][/ROW]
[ROW][C]57[/C][C]90.52[/C][C]87.3555[/C][C]87.7921[/C][C]-0.43661[/C][C]3.16453[/C][/ROW]
[ROW][C]58[/C][C]90.66[/C][C]88.9273[/C][C]89.0662[/C][C]-0.138954[/C][C]1.7327[/C][/ROW]
[ROW][C]59[/C][C]90.69[/C][C]90.8592[/C][C]90.3312[/C][C]0.527921[/C][C]-0.169171[/C][/ROW]
[ROW][C]60[/C][C]92.56[/C][C]94.2539[/C][C]91.8196[/C][C]2.43433[/C][C]-1.69391[/C][/ROW]
[ROW][C]61[/C][C]92.87[/C][C]96.0456[/C][C]93.4429[/C][C]2.60271[/C][C]-3.17563[/C][/ROW]
[ROW][C]62[/C][C]93.82[/C][C]97.3398[/C][C]94.9454[/C][C]2.39438[/C][C]-3.5198[/C][/ROW]
[ROW][C]63[/C][C]96.32[/C][C]97.2947[/C][C]96.3462[/C][C]0.948494[/C][C]-0.974744[/C][/ROW]
[ROW][C]64[/C][C]96.03[/C][C]97.6175[/C][C]97.6858[/C][C]-0.0683811[/C][C]-1.58745[/C][/ROW]
[ROW][C]65[/C][C]96.53[/C][C]97.5675[/C][C]99.0162[/C][C]-1.44875[/C][C]-1.0375[/C][/ROW]
[ROW][C]66[/C][C]102.96[/C][C]97.9303[/C][C]100.35[/C][C]-2.4201[/C][C]5.02968[/C][/ROW]
[ROW][C]67[/C][C]102.38[/C][C]99.1138[/C][C]101.677[/C][C]-2.56291[/C][C]3.26625[/C][/ROW]
[ROW][C]68[/C][C]102.66[/C][C]101.199[/C][C]103.031[/C][C]-1.83213[/C][C]1.46088[/C][/ROW]
[ROW][C]69[/C][C]106.83[/C][C]103.892[/C][C]104.328[/C][C]-0.43661[/C][C]2.93828[/C][/ROW]
[ROW][C]70[/C][C]106.5[/C][C]105.398[/C][C]105.537[/C][C]-0.138954[/C][C]1.10187[/C][/ROW]
[ROW][C]71[/C][C]106.78[/C][C]107.235[/C][C]106.707[/C][C]0.527921[/C][C]-0.454588[/C][/ROW]
[ROW][C]72[/C][C]108.49[/C][C]109.976[/C][C]107.542[/C][C]2.43433[/C][C]-1.48599[/C][/ROW]
[ROW][C]73[/C][C]108.77[/C][C]110.692[/C][C]108.089[/C][C]2.60271[/C][C]-1.92188[/C][/ROW]
[ROW][C]74[/C][C]110.43[/C][C]111.025[/C][C]108.631[/C][C]2.39438[/C][C]-0.595213[/C][/ROW]
[ROW][C]75[/C][C]110.84[/C][C]109.906[/C][C]108.958[/C][C]0.948494[/C][C]0.933589[/C][/ROW]
[ROW][C]76[/C][C]110.52[/C][C]109.02[/C][C]109.089[/C][C]-0.0683811[/C][C]1.49963[/C][/ROW]
[ROW][C]77[/C][C]110.11[/C][C]107.776[/C][C]109.225[/C][C]-1.44875[/C][C]2.33375[/C][/ROW]
[ROW][C]78[/C][C]109.42[/C][C]106.844[/C][C]109.264[/C][C]-2.4201[/C][C]2.57635[/C][/ROW]
[ROW][C]79[/C][C]109.06[/C][C]106.566[/C][C]109.129[/C][C]-2.56291[/C][C]2.49375[/C][/ROW]
[ROW][C]80[/C][C]108.98[/C][C]106.803[/C][C]108.635[/C][C]-1.83213[/C][C]2.17713[/C][/ROW]
[ROW][C]81[/C][C]108.36[/C][C]107.39[/C][C]107.826[/C][C]-0.43661[/C][C]0.97036[/C][/ROW]
[ROW][C]82[/C][C]108.11[/C][C]106.871[/C][C]107.01[/C][C]-0.138954[/C][C]1.23937[/C][/ROW]
[ROW][C]83[/C][C]108.44[/C][C]106.69[/C][C]106.162[/C][C]0.527921[/C][C]1.74958[/C][/ROW]
[ROW][C]84[/C][C]107.76[/C][C]107.728[/C][C]105.294[/C][C]2.43433[/C][C]0.0319227[/C][/ROW]
[ROW][C]85[/C][C]106.27[/C][C]107.067[/C][C]104.465[/C][C]2.60271[/C][C]-0.797296[/C][/ROW]
[ROW][C]86[/C][C]101.07[/C][C]105.998[/C][C]103.603[/C][C]2.39438[/C][C]-4.92771[/C][/ROW]
[ROW][C]87[/C][C]100.79[/C][C]103.676[/C][C]102.727[/C][C]0.948494[/C][C]-2.88558[/C][/ROW]
[ROW][C]88[/C][C]100.97[/C][C]101.833[/C][C]101.901[/C][C]-0.0683811[/C][C]-0.862869[/C][/ROW]
[ROW][C]89[/C][C]99.33[/C][C]99.6579[/C][C]101.107[/C][C]-1.44875[/C][C]-0.327921[/C][/ROW]
[ROW][C]90[/C][C]99.35[/C][C]97.9362[/C][C]100.356[/C][C]-2.4201[/C][C]1.41385[/C][/ROW]
[ROW][C]91[/C][C]99.23[/C][C]97.1375[/C][C]99.7004[/C][C]-2.56291[/C][C]2.0925[/C][/ROW]
[ROW][C]92[/C][C]98.14[/C][C]97.5304[/C][C]99.3625[/C][C]-1.83213[/C][C]0.609631[/C][/ROW]
[ROW][C]93[/C][C]98.17[/C][C]98.8567[/C][C]99.2933[/C][C]-0.43661[/C][C]-0.686723[/C][/ROW]
[ROW][C]94[/C][C]98.48[/C][C]98.8865[/C][C]99.0254[/C][C]-0.138954[/C][C]-0.406463[/C][/ROW]
[ROW][C]95[/C][C]99[/C][C]99.1233[/C][C]98.5954[/C][C]0.527921[/C][C]-0.123338[/C][/ROW]
[ROW][C]96[/C][C]99.19[/C][C]100.625[/C][C]98.1908[/C][C]2.43433[/C][C]-1.43516[/C][/ROW]
[ROW][C]97[/C][C]99.1[/C][C]100.174[/C][C]97.5712[/C][C]2.60271[/C][C]-1.07396[/C][/ROW]
[ROW][C]98[/C][C]100.13[/C][C]99.1519[/C][C]96.7575[/C][C]2.39438[/C][C]0.978121[/C][/ROW]
[ROW][C]99[/C][C]100.07[/C][C]96.8993[/C][C]95.9508[/C][C]0.948494[/C][C]3.17067[/C][/ROW]
[ROW][C]100[/C][C]95.26[/C][C]95.2883[/C][C]95.3567[/C][C]-0.0683811[/C][C]-0.0282856[/C][/ROW]
[ROW][C]101[/C][C]94.72[/C][C]93.5029[/C][C]94.9517[/C][C]-1.44875[/C][C]1.21708[/C][/ROW]
[ROW][C]102[/C][C]94.25[/C][C]92.1012[/C][C]94.5212[/C][C]-2.4201[/C][C]2.14885[/C][/ROW]
[ROW][C]103[/C][C]89.46[/C][C]NA[/C][C]NA[/C][C]-2.56291[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]88.38[/C][C]NA[/C][C]NA[/C][C]-1.83213[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]88.57[/C][C]NA[/C][C]NA[/C][C]-0.43661[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]93.82[/C][C]NA[/C][C]NA[/C][C]-0.138954[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]93.94[/C][C]NA[/C][C]NA[/C][C]0.527921[/C][C]NA[/C][/ROW]
[ROW][C]108[/C][C]93.92[/C][C]NA[/C][C]NA[/C][C]2.43433[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284205&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284205&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	71.83	NA	NA	2.60271	NA
2	71.39	NA	NA	2.39438	NA
3	73.71	NA	NA	0.948494	NA
4	74.13	NA	NA	-0.0683811	NA
5	74.45	NA	NA	-1.44875	NA
6	74.95	NA	NA	-2.4201	NA
7	75.09	72.5529	75.1158	-2.56291	2.53708
8	75.23	73.7112	75.5433	-1.83213	1.5188
9	76.11	75.1659	75.6025	-0.43661	0.94411
10	76.64	75.079	75.2179	-0.138954	1.56104
11	76.97	75.1763	74.6483	0.527921	1.79375
12	78.23	76.2702	73.8358	2.43433	1.95984
13	77.15	75.4506	72.8479	2.60271	1.69937
14	76.33	74.331	71.9367	2.39438	1.99895
15	70.19	72.0289	71.0804	0.948494	-1.83891
16	68.42	70.2104	70.2788	-0.0683811	-1.79037
17	66.49	68.3729	69.8217	-1.44875	-1.88292
18	63.41	67.3141	69.7342	-2.4201	-3.90407
19	62.92	67.3996	69.9625	-2.56291	-4.47959
20	65.53	68.7437	70.5758	-1.83213	-3.2137
21	65.26	71.3471	71.7837	-0.43661	-6.08714
22	68.25	73.3185	73.4575	-0.138954	-5.06855
23	74.39	75.7917	75.2637	0.527921	-1.40167
24	78.71	79.881	77.4467	2.43433	-1.17099
25	82.15	82.6219	80.0192	2.60271	-0.471879
26	86.05	85.0127	82.6183	2.39438	1.03729
27	89.46	86.4577	85.5092	0.948494	3.00234
28	89.32	88.5516	88.62	-0.0683811	0.768381
29	88.94	89.895	91.3438	-1.44875	-0.955004
30	93.35	91.4882	93.9083	-2.4201	1.86177
31	94.72	93.875	96.4379	-2.56291	0.844996
32	96.11	96.6979	98.53	-1.83213	-0.587869
33	104.06	99.2646	99.7012	-0.43661	4.79536
34	104.11	100.101	100.24	-0.138954	4.00854
35	103.9	101.104	100.576	0.527921	2.79583
36	110.75	102.353	99.9183	2.43433	8.39734
37	110.82	100.995	98.3921	2.60271	9.8252
38	107.59	99.2665	96.8721	2.39438	8.32354
39	96.03	95.8847	94.9362	0.948494	0.145256
40	95.69	92.4766	92.545	-0.0683811	3.21338
41	90.63	88.735	90.1838	-1.44875	1.895
42	75.87	85.1682	87.5883	-2.4201	-9.29823
43	75.57	82.2538	84.8167	-2.56291	-6.68375
44	78.78	80.4487	82.2808	-1.83213	-1.6687
45	74.93	80.0251	80.4617	-0.43661	-5.09506
46	75.85	79.0748	79.2137	-0.138954	-3.2248
47	75.49	78.7367	78.2088	0.527921	-3.24667
48	76.87	80.5293	78.095	2.43433	-3.65933
49	78.18	81.3202	78.7175	2.60271	-3.14021
50	79.37	81.7215	79.3271	2.39438	-2.35146
51	80.59	81.1989	80.2504	0.948494	-0.608911
52	81.18	81.4487	81.5171	-0.0683811	-0.268702
53	81.02	81.3188	82.7675	-1.44875	-0.298754
54	82.75	81.6345	84.0546	-2.4201	1.11552
55	83.63	82.7575	85.3204	-2.56291	0.872496
56	85.35	84.7025	86.5346	-1.83213	0.647548
57	90.52	87.3555	87.7921	-0.43661	3.16453
58	90.66	88.9273	89.0662	-0.138954	1.7327
59	90.69	90.8592	90.3312	0.527921	-0.169171
60	92.56	94.2539	91.8196	2.43433	-1.69391
61	92.87	96.0456	93.4429	2.60271	-3.17563
62	93.82	97.3398	94.9454	2.39438	-3.5198
63	96.32	97.2947	96.3462	0.948494	-0.974744
64	96.03	97.6175	97.6858	-0.0683811	-1.58745
65	96.53	97.5675	99.0162	-1.44875	-1.0375
66	102.96	97.9303	100.35	-2.4201	5.02968
67	102.38	99.1138	101.677	-2.56291	3.26625
68	102.66	101.199	103.031	-1.83213	1.46088
69	106.83	103.892	104.328	-0.43661	2.93828
70	106.5	105.398	105.537	-0.138954	1.10187
71	106.78	107.235	106.707	0.527921	-0.454588
72	108.49	109.976	107.542	2.43433	-1.48599
73	108.77	110.692	108.089	2.60271	-1.92188
74	110.43	111.025	108.631	2.39438	-0.595213
75	110.84	109.906	108.958	0.948494	0.933589
76	110.52	109.02	109.089	-0.0683811	1.49963
77	110.11	107.776	109.225	-1.44875	2.33375
78	109.42	106.844	109.264	-2.4201	2.57635
79	109.06	106.566	109.129	-2.56291	2.49375
80	108.98	106.803	108.635	-1.83213	2.17713
81	108.36	107.39	107.826	-0.43661	0.97036
82	108.11	106.871	107.01	-0.138954	1.23937
83	108.44	106.69	106.162	0.527921	1.74958
84	107.76	107.728	105.294	2.43433	0.0319227
85	106.27	107.067	104.465	2.60271	-0.797296
86	101.07	105.998	103.603	2.39438	-4.92771
87	100.79	103.676	102.727	0.948494	-2.88558
88	100.97	101.833	101.901	-0.0683811	-0.862869
89	99.33	99.6579	101.107	-1.44875	-0.327921
90	99.35	97.9362	100.356	-2.4201	1.41385
91	99.23	97.1375	99.7004	-2.56291	2.0925
92	98.14	97.5304	99.3625	-1.83213	0.609631
93	98.17	98.8567	99.2933	-0.43661	-0.686723
94	98.48	98.8865	99.0254	-0.138954	-0.406463
95	99	99.1233	98.5954	0.527921	-0.123338
96	99.19	100.625	98.1908	2.43433	-1.43516
97	99.1	100.174	97.5712	2.60271	-1.07396
98	100.13	99.1519	96.7575	2.39438	0.978121
99	100.07	96.8993	95.9508	0.948494	3.17067
100	95.26	95.2883	95.3567	-0.0683811	-0.0282856
101	94.72	93.5029	94.9517	-1.44875	1.21708
102	94.25	92.1012	94.5212	-2.4201	2.14885
103	89.46	NA	NA	-2.56291	NA
104	88.38	NA	NA	-1.83213	NA
105	88.57	NA	NA	-0.43661	NA
106	93.82	NA	NA	-0.138954	NA
107	93.94	NA	NA	0.527921	NA
108	93.92	NA	NA	2.43433	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