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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 17 Dec 2015 13:44:23 +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/Dec/17/t1450359874tfxfbjmo8w9v7gg.htm/, Retrieved Thu, 16 May 2024 17:25:30 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286802, Retrieved Thu, 16 May 2024 17:25:30 +0000

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Estimated Impact

115

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

-     [Univariate Data Series] [] [2015-12-17 13:13:10] [c4d175d45982400f45768592120a8602]
- RMP   [(Partial) Autocorrelation Function] [] [2015-12-17 13:37:49] [c4d175d45982400f45768592120a8602]
- RMPD      [Classical Decomposition] [] [2015-12-17 13:44:23] [0f06e4fdd8087d4b3abca42184bf2a00] [Current]
- RMP         [Exponential Smoothing] [] [2015-12-17 13:51:34] [c4d175d45982400f45768592120a8602] 

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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	3 seconds
R Server	'George Udny Yule' @ yule.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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286802&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286802&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286802&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	3 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	87.29	NA	NA	-9.70994	NA
2	88.19	NA	NA	-8.78577	NA
3	89.1	NA	NA	-9.49588	NA
4	89.1	NA	NA	-8.49046	NA
5	103.65	NA	NA	2.06712	NA
6	127.75	NA	NA	16.4657	NA
7	125.47	121.453	102.077	19.3753	4.01723
8	125.47	114.858	102.002	12.8559	10.6124
9	109.11	109.01	101.85	7.15938	0.100198
10	100.01	98.9988	101.661	-2.66249	1.01124
11	95.01	96.1921	101.434	-5.24202	-1.18215
12	85.01	87.0828	100.62	-13.5368	-2.07277
13	86.83	89.3942	99.1042	-9.70994	-2.56423
14	86.83	88.538	97.3238	-8.78577	-1.70798
15	86.83	86.71	96.2058	-9.49588	0.120042
16	86.83	87.3933	95.8837	-8.49046	-0.563291
17	100.47	97.7617	95.6946	2.06712	2.70829
18	111.38	112.198	95.7325	16.4657	-0.818194
19	105.47	115.43	96.0546	19.3753	-9.95985
20	102.74	109.422	96.5662	12.8559	-6.68215
21	105.01	104.351	97.1917	7.15938	0.658948
22	96.38	95.2871	97.9496	-2.66249	1.09291
23	94.1	93.0676	98.3096	-5.24202	1.03244
24	86.83	85.1136	98.6504	-13.5368	1.7164
25	92.74	90.058	99.7679	-9.70994	2.68202
26	93.2	92.1946	100.98	-8.78577	1.00535
27	95.47	92.6216	102.118	-9.49588	2.84838
28	96.38	94.5554	103.046	-8.49046	1.82463
29	99.56	105.7	103.633	2.06712	-6.14004
30	120.47	120.781	104.315	16.4657	-0.310694
31	123.2	124.353	104.978	19.3753	-1.15319
32	114.11	118.42	105.565	12.8559	-4.31048
33	120.93	113.121	105.962	7.15938	7.80853
34	102.74	103.565	106.227	-2.66249	-0.824593
35	101.83	101.307	106.549	-5.24202	0.523271
36	95.47	92.9361	106.473	-13.5368	2.5339
37	100.01	96.9713	106.681	-9.70994	3.03869
38	100.01	99.0888	107.875	-8.78577	0.921188
39	98.2	98.8141	108.31	-9.49588	-0.614125
40	100.01	99.7058	108.196	-8.49046	0.304209
41	103.65	110.472	108.405	2.06712	-6.82212
42	114.56	124.852	108.386	16.4657	-10.2919
43	134.11	127.61	108.235	19.3753	6.49973
44	131.84	120.902	108.046	12.8559	10.9379
45	113.65	115.016	107.857	7.15938	-1.36647
46	107.29	105.1	107.762	-2.66249	2.18999
47	102.29	103.07	108.312	-5.24202	-0.780062
48	94.56	95.4194	108.956	-13.5368	-0.859437
49	97.29	99.6442	109.354	-9.70994	-2.35423
50	98.2	100.36	109.146	-8.78577	-2.16006
51	95.47	99.0629	108.559	-9.49588	-3.59287
52	100.47	100.03	108.521	-8.49046	0.439625
53	116.38	110.796	108.729	2.06712	5.58413
54	117.29	125.535	109.069	16.4657	-8.24486
55	140.93	128.823	109.448	19.3753	12.1072
56	120.02	122.682	109.826	12.8559	-2.66173
57	111.38	117.477	110.318	7.15938	-6.0973
58	108.65	108.167	110.829	-2.66249	0.483323
59	105.92	105.473	110.715	-5.24202	0.446605
60	99.1	97.7849	111.322	-13.5368	1.31515
61	101.83	101.271	110.981	-9.70994	0.559105
62	102.74	100.869	109.655	-8.78577	1.87119
63	102.74	100.462	109.958	-9.49588	2.27838
64	105.47	101.846	110.337	-8.49046	3.62379
65	108.65	112.518	110.451	2.06712	-3.86796
66	139.57	127.107	110.641	16.4657	12.4635
67	110.47	130.301	110.925	19.3753	-19.8307
68	118.65	124.217	111.361	12.8559	-5.56715
69	120.02	118.975	111.816	7.15938	1.04478
70	109.11	109.38	112.043	-2.66249	-0.270427
71	108.2	107.691	112.933	-5.24202	0.509105
72	101.38	100.248	113.785	-13.5368	1.13181
73	106.38	104.7	114.41	-9.70994	1.67994
74	108.65	106.477	115.262	-8.78577	2.17327
75	107.74	105.918	115.414	-9.49588	1.82213
76	105.92	106.923	115.413	-8.49046	-1.00287
77	129.56	117.613	115.546	2.06712	11.947
78	139.11	132.049	115.584	16.4657	7.06056
79	125.93	134.826	115.451	19.3753	-8.8961
80	123.65	128.126	115.27	12.8559	-4.47631
81	118.65	122.251	115.092	7.15938	-3.60105
82	110.47	112.402	115.064	-2.66249	-1.93168
83	110.02	109.402	114.644	-5.24202	0.617855
84	100.47	100.504	114.041	-13.5368	-0.034437
85	104.1	105.5	115.21	-9.70994	-1.40048
86	106.6	108.217	117.003	-8.78577	-1.61715
87	105.5	108.486	117.982	-9.49588	-2.98621
88	107.5	110.257	118.748	-8.49046	-2.75746
89	117.9	121.349	119.282	2.06712	-3.44879
90	136.3	136.198	119.732	16.4657	0.102222
91	156.8	139.629	120.254	19.3753	17.1706
92	135.8	133.698	120.842	12.8559	2.10244
93	130	128.593	121.433	7.15938	1.40728
94	117.5	119.296	121.958	-2.66249	-1.79584
95	115.8	117.012	122.254	-5.24202	-1.21215
96	105.5	109.276	122.812	-13.5368	-3.77569
97	111.6	113.286	122.996	-9.70994	-1.6859
98	113.2	113.731	122.517	-8.78577	-0.530895
99	113.1	113.021	122.517	-9.49588	0.0792088
100	112.5	114.414	122.904	-8.49046	-1.91371
101	120	NA	NA	2.06712	NA
102	147.6	NA	NA	16.4657	NA
103	149.9	NA	NA	19.3753	NA
104	131.2	NA	NA	12.8559	NA
105	134.6	NA	NA	7.15938	NA
106	122.2	NA	NA	-2.66249	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 87.29 & NA & NA & -9.70994 & NA \tabularnewline
2 & 88.19 & NA & NA & -8.78577 & NA \tabularnewline
3 & 89.1 & NA & NA & -9.49588 & NA \tabularnewline
4 & 89.1 & NA & NA & -8.49046 & NA \tabularnewline
5 & 103.65 & NA & NA & 2.06712 & NA \tabularnewline
6 & 127.75 & NA & NA & 16.4657 & NA \tabularnewline
7 & 125.47 & 121.453 & 102.077 & 19.3753 & 4.01723 \tabularnewline
8 & 125.47 & 114.858 & 102.002 & 12.8559 & 10.6124 \tabularnewline
9 & 109.11 & 109.01 & 101.85 & 7.15938 & 0.100198 \tabularnewline
10 & 100.01 & 98.9988 & 101.661 & -2.66249 & 1.01124 \tabularnewline
11 & 95.01 & 96.1921 & 101.434 & -5.24202 & -1.18215 \tabularnewline
12 & 85.01 & 87.0828 & 100.62 & -13.5368 & -2.07277 \tabularnewline
13 & 86.83 & 89.3942 & 99.1042 & -9.70994 & -2.56423 \tabularnewline
14 & 86.83 & 88.538 & 97.3238 & -8.78577 & -1.70798 \tabularnewline
15 & 86.83 & 86.71 & 96.2058 & -9.49588 & 0.120042 \tabularnewline
16 & 86.83 & 87.3933 & 95.8837 & -8.49046 & -0.563291 \tabularnewline
17 & 100.47 & 97.7617 & 95.6946 & 2.06712 & 2.70829 \tabularnewline
18 & 111.38 & 112.198 & 95.7325 & 16.4657 & -0.818194 \tabularnewline
19 & 105.47 & 115.43 & 96.0546 & 19.3753 & -9.95985 \tabularnewline
20 & 102.74 & 109.422 & 96.5662 & 12.8559 & -6.68215 \tabularnewline
21 & 105.01 & 104.351 & 97.1917 & 7.15938 & 0.658948 \tabularnewline
22 & 96.38 & 95.2871 & 97.9496 & -2.66249 & 1.09291 \tabularnewline
23 & 94.1 & 93.0676 & 98.3096 & -5.24202 & 1.03244 \tabularnewline
24 & 86.83 & 85.1136 & 98.6504 & -13.5368 & 1.7164 \tabularnewline
25 & 92.74 & 90.058 & 99.7679 & -9.70994 & 2.68202 \tabularnewline
26 & 93.2 & 92.1946 & 100.98 & -8.78577 & 1.00535 \tabularnewline
27 & 95.47 & 92.6216 & 102.118 & -9.49588 & 2.84838 \tabularnewline
28 & 96.38 & 94.5554 & 103.046 & -8.49046 & 1.82463 \tabularnewline
29 & 99.56 & 105.7 & 103.633 & 2.06712 & -6.14004 \tabularnewline
30 & 120.47 & 120.781 & 104.315 & 16.4657 & -0.310694 \tabularnewline
31 & 123.2 & 124.353 & 104.978 & 19.3753 & -1.15319 \tabularnewline
32 & 114.11 & 118.42 & 105.565 & 12.8559 & -4.31048 \tabularnewline
33 & 120.93 & 113.121 & 105.962 & 7.15938 & 7.80853 \tabularnewline
34 & 102.74 & 103.565 & 106.227 & -2.66249 & -0.824593 \tabularnewline
35 & 101.83 & 101.307 & 106.549 & -5.24202 & 0.523271 \tabularnewline
36 & 95.47 & 92.9361 & 106.473 & -13.5368 & 2.5339 \tabularnewline
37 & 100.01 & 96.9713 & 106.681 & -9.70994 & 3.03869 \tabularnewline
38 & 100.01 & 99.0888 & 107.875 & -8.78577 & 0.921188 \tabularnewline
39 & 98.2 & 98.8141 & 108.31 & -9.49588 & -0.614125 \tabularnewline
40 & 100.01 & 99.7058 & 108.196 & -8.49046 & 0.304209 \tabularnewline
41 & 103.65 & 110.472 & 108.405 & 2.06712 & -6.82212 \tabularnewline
42 & 114.56 & 124.852 & 108.386 & 16.4657 & -10.2919 \tabularnewline
43 & 134.11 & 127.61 & 108.235 & 19.3753 & 6.49973 \tabularnewline
44 & 131.84 & 120.902 & 108.046 & 12.8559 & 10.9379 \tabularnewline
45 & 113.65 & 115.016 & 107.857 & 7.15938 & -1.36647 \tabularnewline
46 & 107.29 & 105.1 & 107.762 & -2.66249 & 2.18999 \tabularnewline
47 & 102.29 & 103.07 & 108.312 & -5.24202 & -0.780062 \tabularnewline
48 & 94.56 & 95.4194 & 108.956 & -13.5368 & -0.859437 \tabularnewline
49 & 97.29 & 99.6442 & 109.354 & -9.70994 & -2.35423 \tabularnewline
50 & 98.2 & 100.36 & 109.146 & -8.78577 & -2.16006 \tabularnewline
51 & 95.47 & 99.0629 & 108.559 & -9.49588 & -3.59287 \tabularnewline
52 & 100.47 & 100.03 & 108.521 & -8.49046 & 0.439625 \tabularnewline
53 & 116.38 & 110.796 & 108.729 & 2.06712 & 5.58413 \tabularnewline
54 & 117.29 & 125.535 & 109.069 & 16.4657 & -8.24486 \tabularnewline
55 & 140.93 & 128.823 & 109.448 & 19.3753 & 12.1072 \tabularnewline
56 & 120.02 & 122.682 & 109.826 & 12.8559 & -2.66173 \tabularnewline
57 & 111.38 & 117.477 & 110.318 & 7.15938 & -6.0973 \tabularnewline
58 & 108.65 & 108.167 & 110.829 & -2.66249 & 0.483323 \tabularnewline
59 & 105.92 & 105.473 & 110.715 & -5.24202 & 0.446605 \tabularnewline
60 & 99.1 & 97.7849 & 111.322 & -13.5368 & 1.31515 \tabularnewline
61 & 101.83 & 101.271 & 110.981 & -9.70994 & 0.559105 \tabularnewline
62 & 102.74 & 100.869 & 109.655 & -8.78577 & 1.87119 \tabularnewline
63 & 102.74 & 100.462 & 109.958 & -9.49588 & 2.27838 \tabularnewline
64 & 105.47 & 101.846 & 110.337 & -8.49046 & 3.62379 \tabularnewline
65 & 108.65 & 112.518 & 110.451 & 2.06712 & -3.86796 \tabularnewline
66 & 139.57 & 127.107 & 110.641 & 16.4657 & 12.4635 \tabularnewline
67 & 110.47 & 130.301 & 110.925 & 19.3753 & -19.8307 \tabularnewline
68 & 118.65 & 124.217 & 111.361 & 12.8559 & -5.56715 \tabularnewline
69 & 120.02 & 118.975 & 111.816 & 7.15938 & 1.04478 \tabularnewline
70 & 109.11 & 109.38 & 112.043 & -2.66249 & -0.270427 \tabularnewline
71 & 108.2 & 107.691 & 112.933 & -5.24202 & 0.509105 \tabularnewline
72 & 101.38 & 100.248 & 113.785 & -13.5368 & 1.13181 \tabularnewline
73 & 106.38 & 104.7 & 114.41 & -9.70994 & 1.67994 \tabularnewline
74 & 108.65 & 106.477 & 115.262 & -8.78577 & 2.17327 \tabularnewline
75 & 107.74 & 105.918 & 115.414 & -9.49588 & 1.82213 \tabularnewline
76 & 105.92 & 106.923 & 115.413 & -8.49046 & -1.00287 \tabularnewline
77 & 129.56 & 117.613 & 115.546 & 2.06712 & 11.947 \tabularnewline
78 & 139.11 & 132.049 & 115.584 & 16.4657 & 7.06056 \tabularnewline
79 & 125.93 & 134.826 & 115.451 & 19.3753 & -8.8961 \tabularnewline
80 & 123.65 & 128.126 & 115.27 & 12.8559 & -4.47631 \tabularnewline
81 & 118.65 & 122.251 & 115.092 & 7.15938 & -3.60105 \tabularnewline
82 & 110.47 & 112.402 & 115.064 & -2.66249 & -1.93168 \tabularnewline
83 & 110.02 & 109.402 & 114.644 & -5.24202 & 0.617855 \tabularnewline
84 & 100.47 & 100.504 & 114.041 & -13.5368 & -0.034437 \tabularnewline
85 & 104.1 & 105.5 & 115.21 & -9.70994 & -1.40048 \tabularnewline
86 & 106.6 & 108.217 & 117.003 & -8.78577 & -1.61715 \tabularnewline
87 & 105.5 & 108.486 & 117.982 & -9.49588 & -2.98621 \tabularnewline
88 & 107.5 & 110.257 & 118.748 & -8.49046 & -2.75746 \tabularnewline
89 & 117.9 & 121.349 & 119.282 & 2.06712 & -3.44879 \tabularnewline
90 & 136.3 & 136.198 & 119.732 & 16.4657 & 0.102222 \tabularnewline
91 & 156.8 & 139.629 & 120.254 & 19.3753 & 17.1706 \tabularnewline
92 & 135.8 & 133.698 & 120.842 & 12.8559 & 2.10244 \tabularnewline
93 & 130 & 128.593 & 121.433 & 7.15938 & 1.40728 \tabularnewline
94 & 117.5 & 119.296 & 121.958 & -2.66249 & -1.79584 \tabularnewline
95 & 115.8 & 117.012 & 122.254 & -5.24202 & -1.21215 \tabularnewline
96 & 105.5 & 109.276 & 122.812 & -13.5368 & -3.77569 \tabularnewline
97 & 111.6 & 113.286 & 122.996 & -9.70994 & -1.6859 \tabularnewline
98 & 113.2 & 113.731 & 122.517 & -8.78577 & -0.530895 \tabularnewline
99 & 113.1 & 113.021 & 122.517 & -9.49588 & 0.0792088 \tabularnewline
100 & 112.5 & 114.414 & 122.904 & -8.49046 & -1.91371 \tabularnewline
101 & 120 & NA & NA & 2.06712 & NA \tabularnewline
102 & 147.6 & NA & NA & 16.4657 & NA \tabularnewline
103 & 149.9 & NA & NA & 19.3753 & NA \tabularnewline
104 & 131.2 & NA & NA & 12.8559 & NA \tabularnewline
105 & 134.6 & NA & NA & 7.15938 & NA \tabularnewline
106 & 122.2 & NA & NA & -2.66249 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286802&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]87.29[/C][C]NA[/C][C]NA[/C][C]-9.70994[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]88.19[/C][C]NA[/C][C]NA[/C][C]-8.78577[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]89.1[/C][C]NA[/C][C]NA[/C][C]-9.49588[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]89.1[/C][C]NA[/C][C]NA[/C][C]-8.49046[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]103.65[/C][C]NA[/C][C]NA[/C][C]2.06712[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]127.75[/C][C]NA[/C][C]NA[/C][C]16.4657[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]125.47[/C][C]121.453[/C][C]102.077[/C][C]19.3753[/C][C]4.01723[/C][/ROW]
[ROW][C]8[/C][C]125.47[/C][C]114.858[/C][C]102.002[/C][C]12.8559[/C][C]10.6124[/C][/ROW]
[ROW][C]9[/C][C]109.11[/C][C]109.01[/C][C]101.85[/C][C]7.15938[/C][C]0.100198[/C][/ROW]
[ROW][C]10[/C][C]100.01[/C][C]98.9988[/C][C]101.661[/C][C]-2.66249[/C][C]1.01124[/C][/ROW]
[ROW][C]11[/C][C]95.01[/C][C]96.1921[/C][C]101.434[/C][C]-5.24202[/C][C]-1.18215[/C][/ROW]
[ROW][C]12[/C][C]85.01[/C][C]87.0828[/C][C]100.62[/C][C]-13.5368[/C][C]-2.07277[/C][/ROW]
[ROW][C]13[/C][C]86.83[/C][C]89.3942[/C][C]99.1042[/C][C]-9.70994[/C][C]-2.56423[/C][/ROW]
[ROW][C]14[/C][C]86.83[/C][C]88.538[/C][C]97.3238[/C][C]-8.78577[/C][C]-1.70798[/C][/ROW]
[ROW][C]15[/C][C]86.83[/C][C]86.71[/C][C]96.2058[/C][C]-9.49588[/C][C]0.120042[/C][/ROW]
[ROW][C]16[/C][C]86.83[/C][C]87.3933[/C][C]95.8837[/C][C]-8.49046[/C][C]-0.563291[/C][/ROW]
[ROW][C]17[/C][C]100.47[/C][C]97.7617[/C][C]95.6946[/C][C]2.06712[/C][C]2.70829[/C][/ROW]
[ROW][C]18[/C][C]111.38[/C][C]112.198[/C][C]95.7325[/C][C]16.4657[/C][C]-0.818194[/C][/ROW]
[ROW][C]19[/C][C]105.47[/C][C]115.43[/C][C]96.0546[/C][C]19.3753[/C][C]-9.95985[/C][/ROW]
[ROW][C]20[/C][C]102.74[/C][C]109.422[/C][C]96.5662[/C][C]12.8559[/C][C]-6.68215[/C][/ROW]
[ROW][C]21[/C][C]105.01[/C][C]104.351[/C][C]97.1917[/C][C]7.15938[/C][C]0.658948[/C][/ROW]
[ROW][C]22[/C][C]96.38[/C][C]95.2871[/C][C]97.9496[/C][C]-2.66249[/C][C]1.09291[/C][/ROW]
[ROW][C]23[/C][C]94.1[/C][C]93.0676[/C][C]98.3096[/C][C]-5.24202[/C][C]1.03244[/C][/ROW]
[ROW][C]24[/C][C]86.83[/C][C]85.1136[/C][C]98.6504[/C][C]-13.5368[/C][C]1.7164[/C][/ROW]
[ROW][C]25[/C][C]92.74[/C][C]90.058[/C][C]99.7679[/C][C]-9.70994[/C][C]2.68202[/C][/ROW]
[ROW][C]26[/C][C]93.2[/C][C]92.1946[/C][C]100.98[/C][C]-8.78577[/C][C]1.00535[/C][/ROW]
[ROW][C]27[/C][C]95.47[/C][C]92.6216[/C][C]102.118[/C][C]-9.49588[/C][C]2.84838[/C][/ROW]
[ROW][C]28[/C][C]96.38[/C][C]94.5554[/C][C]103.046[/C][C]-8.49046[/C][C]1.82463[/C][/ROW]
[ROW][C]29[/C][C]99.56[/C][C]105.7[/C][C]103.633[/C][C]2.06712[/C][C]-6.14004[/C][/ROW]
[ROW][C]30[/C][C]120.47[/C][C]120.781[/C][C]104.315[/C][C]16.4657[/C][C]-0.310694[/C][/ROW]
[ROW][C]31[/C][C]123.2[/C][C]124.353[/C][C]104.978[/C][C]19.3753[/C][C]-1.15319[/C][/ROW]
[ROW][C]32[/C][C]114.11[/C][C]118.42[/C][C]105.565[/C][C]12.8559[/C][C]-4.31048[/C][/ROW]
[ROW][C]33[/C][C]120.93[/C][C]113.121[/C][C]105.962[/C][C]7.15938[/C][C]7.80853[/C][/ROW]
[ROW][C]34[/C][C]102.74[/C][C]103.565[/C][C]106.227[/C][C]-2.66249[/C][C]-0.824593[/C][/ROW]
[ROW][C]35[/C][C]101.83[/C][C]101.307[/C][C]106.549[/C][C]-5.24202[/C][C]0.523271[/C][/ROW]
[ROW][C]36[/C][C]95.47[/C][C]92.9361[/C][C]106.473[/C][C]-13.5368[/C][C]2.5339[/C][/ROW]
[ROW][C]37[/C][C]100.01[/C][C]96.9713[/C][C]106.681[/C][C]-9.70994[/C][C]3.03869[/C][/ROW]
[ROW][C]38[/C][C]100.01[/C][C]99.0888[/C][C]107.875[/C][C]-8.78577[/C][C]0.921188[/C][/ROW]
[ROW][C]39[/C][C]98.2[/C][C]98.8141[/C][C]108.31[/C][C]-9.49588[/C][C]-0.614125[/C][/ROW]
[ROW][C]40[/C][C]100.01[/C][C]99.7058[/C][C]108.196[/C][C]-8.49046[/C][C]0.304209[/C][/ROW]
[ROW][C]41[/C][C]103.65[/C][C]110.472[/C][C]108.405[/C][C]2.06712[/C][C]-6.82212[/C][/ROW]
[ROW][C]42[/C][C]114.56[/C][C]124.852[/C][C]108.386[/C][C]16.4657[/C][C]-10.2919[/C][/ROW]
[ROW][C]43[/C][C]134.11[/C][C]127.61[/C][C]108.235[/C][C]19.3753[/C][C]6.49973[/C][/ROW]
[ROW][C]44[/C][C]131.84[/C][C]120.902[/C][C]108.046[/C][C]12.8559[/C][C]10.9379[/C][/ROW]
[ROW][C]45[/C][C]113.65[/C][C]115.016[/C][C]107.857[/C][C]7.15938[/C][C]-1.36647[/C][/ROW]
[ROW][C]46[/C][C]107.29[/C][C]105.1[/C][C]107.762[/C][C]-2.66249[/C][C]2.18999[/C][/ROW]
[ROW][C]47[/C][C]102.29[/C][C]103.07[/C][C]108.312[/C][C]-5.24202[/C][C]-0.780062[/C][/ROW]
[ROW][C]48[/C][C]94.56[/C][C]95.4194[/C][C]108.956[/C][C]-13.5368[/C][C]-0.859437[/C][/ROW]
[ROW][C]49[/C][C]97.29[/C][C]99.6442[/C][C]109.354[/C][C]-9.70994[/C][C]-2.35423[/C][/ROW]
[ROW][C]50[/C][C]98.2[/C][C]100.36[/C][C]109.146[/C][C]-8.78577[/C][C]-2.16006[/C][/ROW]
[ROW][C]51[/C][C]95.47[/C][C]99.0629[/C][C]108.559[/C][C]-9.49588[/C][C]-3.59287[/C][/ROW]
[ROW][C]52[/C][C]100.47[/C][C]100.03[/C][C]108.521[/C][C]-8.49046[/C][C]0.439625[/C][/ROW]
[ROW][C]53[/C][C]116.38[/C][C]110.796[/C][C]108.729[/C][C]2.06712[/C][C]5.58413[/C][/ROW]
[ROW][C]54[/C][C]117.29[/C][C]125.535[/C][C]109.069[/C][C]16.4657[/C][C]-8.24486[/C][/ROW]
[ROW][C]55[/C][C]140.93[/C][C]128.823[/C][C]109.448[/C][C]19.3753[/C][C]12.1072[/C][/ROW]
[ROW][C]56[/C][C]120.02[/C][C]122.682[/C][C]109.826[/C][C]12.8559[/C][C]-2.66173[/C][/ROW]
[ROW][C]57[/C][C]111.38[/C][C]117.477[/C][C]110.318[/C][C]7.15938[/C][C]-6.0973[/C][/ROW]
[ROW][C]58[/C][C]108.65[/C][C]108.167[/C][C]110.829[/C][C]-2.66249[/C][C]0.483323[/C][/ROW]
[ROW][C]59[/C][C]105.92[/C][C]105.473[/C][C]110.715[/C][C]-5.24202[/C][C]0.446605[/C][/ROW]
[ROW][C]60[/C][C]99.1[/C][C]97.7849[/C][C]111.322[/C][C]-13.5368[/C][C]1.31515[/C][/ROW]
[ROW][C]61[/C][C]101.83[/C][C]101.271[/C][C]110.981[/C][C]-9.70994[/C][C]0.559105[/C][/ROW]
[ROW][C]62[/C][C]102.74[/C][C]100.869[/C][C]109.655[/C][C]-8.78577[/C][C]1.87119[/C][/ROW]
[ROW][C]63[/C][C]102.74[/C][C]100.462[/C][C]109.958[/C][C]-9.49588[/C][C]2.27838[/C][/ROW]
[ROW][C]64[/C][C]105.47[/C][C]101.846[/C][C]110.337[/C][C]-8.49046[/C][C]3.62379[/C][/ROW]
[ROW][C]65[/C][C]108.65[/C][C]112.518[/C][C]110.451[/C][C]2.06712[/C][C]-3.86796[/C][/ROW]
[ROW][C]66[/C][C]139.57[/C][C]127.107[/C][C]110.641[/C][C]16.4657[/C][C]12.4635[/C][/ROW]
[ROW][C]67[/C][C]110.47[/C][C]130.301[/C][C]110.925[/C][C]19.3753[/C][C]-19.8307[/C][/ROW]
[ROW][C]68[/C][C]118.65[/C][C]124.217[/C][C]111.361[/C][C]12.8559[/C][C]-5.56715[/C][/ROW]
[ROW][C]69[/C][C]120.02[/C][C]118.975[/C][C]111.816[/C][C]7.15938[/C][C]1.04478[/C][/ROW]
[ROW][C]70[/C][C]109.11[/C][C]109.38[/C][C]112.043[/C][C]-2.66249[/C][C]-0.270427[/C][/ROW]
[ROW][C]71[/C][C]108.2[/C][C]107.691[/C][C]112.933[/C][C]-5.24202[/C][C]0.509105[/C][/ROW]
[ROW][C]72[/C][C]101.38[/C][C]100.248[/C][C]113.785[/C][C]-13.5368[/C][C]1.13181[/C][/ROW]
[ROW][C]73[/C][C]106.38[/C][C]104.7[/C][C]114.41[/C][C]-9.70994[/C][C]1.67994[/C][/ROW]
[ROW][C]74[/C][C]108.65[/C][C]106.477[/C][C]115.262[/C][C]-8.78577[/C][C]2.17327[/C][/ROW]
[ROW][C]75[/C][C]107.74[/C][C]105.918[/C][C]115.414[/C][C]-9.49588[/C][C]1.82213[/C][/ROW]
[ROW][C]76[/C][C]105.92[/C][C]106.923[/C][C]115.413[/C][C]-8.49046[/C][C]-1.00287[/C][/ROW]
[ROW][C]77[/C][C]129.56[/C][C]117.613[/C][C]115.546[/C][C]2.06712[/C][C]11.947[/C][/ROW]
[ROW][C]78[/C][C]139.11[/C][C]132.049[/C][C]115.584[/C][C]16.4657[/C][C]7.06056[/C][/ROW]
[ROW][C]79[/C][C]125.93[/C][C]134.826[/C][C]115.451[/C][C]19.3753[/C][C]-8.8961[/C][/ROW]
[ROW][C]80[/C][C]123.65[/C][C]128.126[/C][C]115.27[/C][C]12.8559[/C][C]-4.47631[/C][/ROW]
[ROW][C]81[/C][C]118.65[/C][C]122.251[/C][C]115.092[/C][C]7.15938[/C][C]-3.60105[/C][/ROW]
[ROW][C]82[/C][C]110.47[/C][C]112.402[/C][C]115.064[/C][C]-2.66249[/C][C]-1.93168[/C][/ROW]
[ROW][C]83[/C][C]110.02[/C][C]109.402[/C][C]114.644[/C][C]-5.24202[/C][C]0.617855[/C][/ROW]
[ROW][C]84[/C][C]100.47[/C][C]100.504[/C][C]114.041[/C][C]-13.5368[/C][C]-0.034437[/C][/ROW]
[ROW][C]85[/C][C]104.1[/C][C]105.5[/C][C]115.21[/C][C]-9.70994[/C][C]-1.40048[/C][/ROW]
[ROW][C]86[/C][C]106.6[/C][C]108.217[/C][C]117.003[/C][C]-8.78577[/C][C]-1.61715[/C][/ROW]
[ROW][C]87[/C][C]105.5[/C][C]108.486[/C][C]117.982[/C][C]-9.49588[/C][C]-2.98621[/C][/ROW]
[ROW][C]88[/C][C]107.5[/C][C]110.257[/C][C]118.748[/C][C]-8.49046[/C][C]-2.75746[/C][/ROW]
[ROW][C]89[/C][C]117.9[/C][C]121.349[/C][C]119.282[/C][C]2.06712[/C][C]-3.44879[/C][/ROW]
[ROW][C]90[/C][C]136.3[/C][C]136.198[/C][C]119.732[/C][C]16.4657[/C][C]0.102222[/C][/ROW]
[ROW][C]91[/C][C]156.8[/C][C]139.629[/C][C]120.254[/C][C]19.3753[/C][C]17.1706[/C][/ROW]
[ROW][C]92[/C][C]135.8[/C][C]133.698[/C][C]120.842[/C][C]12.8559[/C][C]2.10244[/C][/ROW]
[ROW][C]93[/C][C]130[/C][C]128.593[/C][C]121.433[/C][C]7.15938[/C][C]1.40728[/C][/ROW]
[ROW][C]94[/C][C]117.5[/C][C]119.296[/C][C]121.958[/C][C]-2.66249[/C][C]-1.79584[/C][/ROW]
[ROW][C]95[/C][C]115.8[/C][C]117.012[/C][C]122.254[/C][C]-5.24202[/C][C]-1.21215[/C][/ROW]
[ROW][C]96[/C][C]105.5[/C][C]109.276[/C][C]122.812[/C][C]-13.5368[/C][C]-3.77569[/C][/ROW]
[ROW][C]97[/C][C]111.6[/C][C]113.286[/C][C]122.996[/C][C]-9.70994[/C][C]-1.6859[/C][/ROW]
[ROW][C]98[/C][C]113.2[/C][C]113.731[/C][C]122.517[/C][C]-8.78577[/C][C]-0.530895[/C][/ROW]
[ROW][C]99[/C][C]113.1[/C][C]113.021[/C][C]122.517[/C][C]-9.49588[/C][C]0.0792088[/C][/ROW]
[ROW][C]100[/C][C]112.5[/C][C]114.414[/C][C]122.904[/C][C]-8.49046[/C][C]-1.91371[/C][/ROW]
[ROW][C]101[/C][C]120[/C][C]NA[/C][C]NA[/C][C]2.06712[/C][C]NA[/C][/ROW]
[ROW][C]102[/C][C]147.6[/C][C]NA[/C][C]NA[/C][C]16.4657[/C][C]NA[/C][/ROW]
[ROW][C]103[/C][C]149.9[/C][C]NA[/C][C]NA[/C][C]19.3753[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]131.2[/C][C]NA[/C][C]NA[/C][C]12.8559[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]134.6[/C][C]NA[/C][C]NA[/C][C]7.15938[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]122.2[/C][C]NA[/C][C]NA[/C][C]-2.66249[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286802&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286802&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	87.29	NA	NA	-9.70994	NA
2	88.19	NA	NA	-8.78577	NA
3	89.1	NA	NA	-9.49588	NA
4	89.1	NA	NA	-8.49046	NA
5	103.65	NA	NA	2.06712	NA
6	127.75	NA	NA	16.4657	NA
7	125.47	121.453	102.077	19.3753	4.01723
8	125.47	114.858	102.002	12.8559	10.6124
9	109.11	109.01	101.85	7.15938	0.100198
10	100.01	98.9988	101.661	-2.66249	1.01124
11	95.01	96.1921	101.434	-5.24202	-1.18215
12	85.01	87.0828	100.62	-13.5368	-2.07277
13	86.83	89.3942	99.1042	-9.70994	-2.56423
14	86.83	88.538	97.3238	-8.78577	-1.70798
15	86.83	86.71	96.2058	-9.49588	0.120042
16	86.83	87.3933	95.8837	-8.49046	-0.563291
17	100.47	97.7617	95.6946	2.06712	2.70829
18	111.38	112.198	95.7325	16.4657	-0.818194
19	105.47	115.43	96.0546	19.3753	-9.95985
20	102.74	109.422	96.5662	12.8559	-6.68215
21	105.01	104.351	97.1917	7.15938	0.658948
22	96.38	95.2871	97.9496	-2.66249	1.09291
23	94.1	93.0676	98.3096	-5.24202	1.03244
24	86.83	85.1136	98.6504	-13.5368	1.7164
25	92.74	90.058	99.7679	-9.70994	2.68202
26	93.2	92.1946	100.98	-8.78577	1.00535
27	95.47	92.6216	102.118	-9.49588	2.84838
28	96.38	94.5554	103.046	-8.49046	1.82463
29	99.56	105.7	103.633	2.06712	-6.14004
30	120.47	120.781	104.315	16.4657	-0.310694
31	123.2	124.353	104.978	19.3753	-1.15319
32	114.11	118.42	105.565	12.8559	-4.31048
33	120.93	113.121	105.962	7.15938	7.80853
34	102.74	103.565	106.227	-2.66249	-0.824593
35	101.83	101.307	106.549	-5.24202	0.523271
36	95.47	92.9361	106.473	-13.5368	2.5339
37	100.01	96.9713	106.681	-9.70994	3.03869
38	100.01	99.0888	107.875	-8.78577	0.921188
39	98.2	98.8141	108.31	-9.49588	-0.614125
40	100.01	99.7058	108.196	-8.49046	0.304209
41	103.65	110.472	108.405	2.06712	-6.82212
42	114.56	124.852	108.386	16.4657	-10.2919
43	134.11	127.61	108.235	19.3753	6.49973
44	131.84	120.902	108.046	12.8559	10.9379
45	113.65	115.016	107.857	7.15938	-1.36647
46	107.29	105.1	107.762	-2.66249	2.18999
47	102.29	103.07	108.312	-5.24202	-0.780062
48	94.56	95.4194	108.956	-13.5368	-0.859437
49	97.29	99.6442	109.354	-9.70994	-2.35423
50	98.2	100.36	109.146	-8.78577	-2.16006
51	95.47	99.0629	108.559	-9.49588	-3.59287
52	100.47	100.03	108.521	-8.49046	0.439625
53	116.38	110.796	108.729	2.06712	5.58413
54	117.29	125.535	109.069	16.4657	-8.24486
55	140.93	128.823	109.448	19.3753	12.1072
56	120.02	122.682	109.826	12.8559	-2.66173
57	111.38	117.477	110.318	7.15938	-6.0973
58	108.65	108.167	110.829	-2.66249	0.483323
59	105.92	105.473	110.715	-5.24202	0.446605
60	99.1	97.7849	111.322	-13.5368	1.31515
61	101.83	101.271	110.981	-9.70994	0.559105
62	102.74	100.869	109.655	-8.78577	1.87119
63	102.74	100.462	109.958	-9.49588	2.27838
64	105.47	101.846	110.337	-8.49046	3.62379
65	108.65	112.518	110.451	2.06712	-3.86796
66	139.57	127.107	110.641	16.4657	12.4635
67	110.47	130.301	110.925	19.3753	-19.8307
68	118.65	124.217	111.361	12.8559	-5.56715
69	120.02	118.975	111.816	7.15938	1.04478
70	109.11	109.38	112.043	-2.66249	-0.270427
71	108.2	107.691	112.933	-5.24202	0.509105
72	101.38	100.248	113.785	-13.5368	1.13181
73	106.38	104.7	114.41	-9.70994	1.67994
74	108.65	106.477	115.262	-8.78577	2.17327
75	107.74	105.918	115.414	-9.49588	1.82213
76	105.92	106.923	115.413	-8.49046	-1.00287
77	129.56	117.613	115.546	2.06712	11.947
78	139.11	132.049	115.584	16.4657	7.06056
79	125.93	134.826	115.451	19.3753	-8.8961
80	123.65	128.126	115.27	12.8559	-4.47631
81	118.65	122.251	115.092	7.15938	-3.60105
82	110.47	112.402	115.064	-2.66249	-1.93168
83	110.02	109.402	114.644	-5.24202	0.617855
84	100.47	100.504	114.041	-13.5368	-0.034437
85	104.1	105.5	115.21	-9.70994	-1.40048
86	106.6	108.217	117.003	-8.78577	-1.61715
87	105.5	108.486	117.982	-9.49588	-2.98621
88	107.5	110.257	118.748	-8.49046	-2.75746
89	117.9	121.349	119.282	2.06712	-3.44879
90	136.3	136.198	119.732	16.4657	0.102222
91	156.8	139.629	120.254	19.3753	17.1706
92	135.8	133.698	120.842	12.8559	2.10244
93	130	128.593	121.433	7.15938	1.40728
94	117.5	119.296	121.958	-2.66249	-1.79584
95	115.8	117.012	122.254	-5.24202	-1.21215
96	105.5	109.276	122.812	-13.5368	-3.77569
97	111.6	113.286	122.996	-9.70994	-1.6859
98	113.2	113.731	122.517	-8.78577	-0.530895
99	113.1	113.021	122.517	-9.49588	0.0792088
100	112.5	114.414	122.904	-8.49046	-1.91371
101	120	NA	NA	2.06712	NA
102	147.6	NA	NA	16.4657	NA
103	149.9	NA	NA	19.3753	NA
104	131.2	NA	NA	12.8559	NA
105	134.6	NA	NA	7.15938	NA
106	122.2	NA	NA	-2.66249	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