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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 Apr 2016 16:03:31 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/25/t14615966405rdj1g43o1y9t52.htm/, Retrieved Mon, 06 May 2024 02:55:35 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294734, Retrieved Mon, 06 May 2024 02:55:35 +0000

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-       [Classical Decomposition] [] [2016-04-25 15:03:31] [c9bda892eb41b28d549a884a1978c032] [Current]

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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294734&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294734&T=0

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

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

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	94.65	NA	NA	0.338964	NA
2	94.16	NA	NA	1.11056	NA
3	93.91	NA	NA	0.329728	NA
4	93.21	NA	NA	-0.0148553	NA
5	92.81	NA	NA	-0.271175	NA
6	93.55	NA	NA	-0.0962442	NA
7	93.03	93.3783	93.4162	-0.0379803	-0.34827
8	93.25	92.937	93.4062	-0.4693	0.31305
9	94.24	93.5004	93.4979	0.00243634	0.739647
10	93.23	92.6464	93.6421	-0.995689	0.583605
11	93.52	94.0465	93.8237	0.222784	-0.526534
12	92.05	93.8791	93.9983	-0.11923	-1.8291
13	93.42	94.5044	94.1654	0.338964	-1.08438
14	95.15	95.4335	94.3229	1.11056	-0.283478
15	95.12	94.7706	94.4408	0.329728	0.349439
16	95.46	94.4893	94.5042	-0.0148553	0.970689
17	94.92	94.3176	94.5887	-0.271175	0.602425
18	95.63	94.6721	94.7683	-0.0962442	0.957911
19	94.96	94.9141	94.9521	-0.0379803	0.045897
20	95.1	94.6128	95.0821	-0.4693	0.487216
21	95.22	95.1408	95.1383	0.00243634	0.0792303
22	93.77	94.0701	95.0658	-0.995689	-0.300145
23	95.01	95.2199	94.9971	0.222784	-0.209867
24	94.87	94.9008	95.02	-0.11923	-0.0307697
25	95.01	95.4502	95.1112	0.338964	-0.440214
26	96.68	96.3526	95.2421	1.11056	0.327355
27	94.94	95.7318	95.4021	0.329728	-0.791811
28	93.9	95.591	95.6058	-0.0148553	-1.69098
29	94.83	95.5976	95.8687	-0.271175	-0.767575
30	96.27	96.11	96.2062	-0.0962442	0.159994
31	96.51	96.5283	96.5662	-0.0379803	-0.0182697
32	96.69	96.3982	96.8675	-0.4693	0.2918
33	97.47	97.1233	97.1208	0.00243634	0.34673
34	96.41	96.4447	97.4404	-0.995689	-0.034728
35	98.68	98.0124	97.7896	0.222784	0.667633
36	99.3	97.9054	98.0246	-0.11923	1.39465
37	99.22	98.551	98.2121	0.338964	0.668953
38	99.7	99.4972	98.3867	1.11056	0.202772
39	98	98.8751	98.5454	0.329728	-0.875145
40	98.51	98.7418	98.7567	-0.0148553	-0.231811
41	98.6	98.713	98.9842	-0.271175	-0.112992
42	98.14	99.0717	99.1679	-0.0962442	-0.931672
43	99.14	99.3054	99.3433	-0.0379803	-0.165353
44	98.25	99.117	99.5862	-0.4693	-0.86695
45	99.72	99.9091	99.9067	0.00243634	-0.189103
46	99.23	99.1526	100.148	-0.995689	0.0773553
47	101.32	100.441	100.218	0.222784	0.878883
48	101.07	100.162	100.281	-0.11923	0.908397
49	101.66	100.699	100.36	0.338964	0.960619
50	103.09	101.548	100.438	1.11056	1.54152
51	102.3	100.789	100.46	0.329728	1.51069
52	100.01	100.361	100.376	-0.0148553	-0.350978
53	98.78	99.9709	100.242	-0.271175	-1.19091
54	99.46	99.9842	100.08	-0.0962442	-0.524172
55	99.73	99.8883	99.9262	-0.0379803	-0.15827
56	99.52	99.2665	99.7358	-0.4693	0.253466
57	98.97	99.5079	99.5054	0.00243634	-0.537853
58	97.97	98.4418	99.4375	-0.995689	-0.471811
59	99.37	99.817	99.5942	0.222784	-0.44695
60	99.14	99.642	99.7613	-0.11923	-0.50202
61	99.89	100.22	99.8813	0.338964	-0.330214
62	100.29	101.07	99.9592	1.11056	-0.779728
63	99.57	100.37	100.04	0.329728	-0.799728
64	101.11	100.191	100.206	-0.0148553	0.919022
65	101.44	100.108	100.379	-0.271175	1.33201
66	100.81	100.448	100.545	-0.0962442	0.361661
67	101.26	100.69	100.727	-0.0379803	0.57048
68	99.86	100.412	100.882	-0.4693	-0.552367
69	100.57	101.082	101.08	0.00243634	-0.512436
70	100.35	100.278	101.274	-0.995689	0.0719387
71	101.15	101.587	101.364	0.222784	-0.43695
72	101.33	101.345	101.464	-0.11923	-0.0149363
73	102.09	101.939	101.6	0.338964	0.151453
74	101.79	102.872	101.762	1.11056	-1.08223
75	102.83	102.297	101.967	0.329728	0.532772
76	102.5	102.19	102.205	-0.0148553	0.310272
77	102.22	102.157	102.428	-0.271175	0.0632581
78	102.43	102.528	102.624	-0.0962442	-0.0975058
79	102.89	NA	NA	-0.0379803	NA
80	102.12	NA	NA	-0.4693	NA
81	103.25	NA	NA	0.00243634	NA
82	103.36	NA	NA	-0.995689	NA
83	103.5	NA	NA	0.222784	NA
84	103.68	NA	NA	-0.11923	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 94.65 & NA & NA & 0.338964 & NA \tabularnewline
2 & 94.16 & NA & NA & 1.11056 & NA \tabularnewline
3 & 93.91 & NA & NA & 0.329728 & NA \tabularnewline
4 & 93.21 & NA & NA & -0.0148553 & NA \tabularnewline
5 & 92.81 & NA & NA & -0.271175 & NA \tabularnewline
6 & 93.55 & NA & NA & -0.0962442 & NA \tabularnewline
7 & 93.03 & 93.3783 & 93.4162 & -0.0379803 & -0.34827 \tabularnewline
8 & 93.25 & 92.937 & 93.4062 & -0.4693 & 0.31305 \tabularnewline
9 & 94.24 & 93.5004 & 93.4979 & 0.00243634 & 0.739647 \tabularnewline
10 & 93.23 & 92.6464 & 93.6421 & -0.995689 & 0.583605 \tabularnewline
11 & 93.52 & 94.0465 & 93.8237 & 0.222784 & -0.526534 \tabularnewline
12 & 92.05 & 93.8791 & 93.9983 & -0.11923 & -1.8291 \tabularnewline
13 & 93.42 & 94.5044 & 94.1654 & 0.338964 & -1.08438 \tabularnewline
14 & 95.15 & 95.4335 & 94.3229 & 1.11056 & -0.283478 \tabularnewline
15 & 95.12 & 94.7706 & 94.4408 & 0.329728 & 0.349439 \tabularnewline
16 & 95.46 & 94.4893 & 94.5042 & -0.0148553 & 0.970689 \tabularnewline
17 & 94.92 & 94.3176 & 94.5887 & -0.271175 & 0.602425 \tabularnewline
18 & 95.63 & 94.6721 & 94.7683 & -0.0962442 & 0.957911 \tabularnewline
19 & 94.96 & 94.9141 & 94.9521 & -0.0379803 & 0.045897 \tabularnewline
20 & 95.1 & 94.6128 & 95.0821 & -0.4693 & 0.487216 \tabularnewline
21 & 95.22 & 95.1408 & 95.1383 & 0.00243634 & 0.0792303 \tabularnewline
22 & 93.77 & 94.0701 & 95.0658 & -0.995689 & -0.300145 \tabularnewline
23 & 95.01 & 95.2199 & 94.9971 & 0.222784 & -0.209867 \tabularnewline
24 & 94.87 & 94.9008 & 95.02 & -0.11923 & -0.0307697 \tabularnewline
25 & 95.01 & 95.4502 & 95.1112 & 0.338964 & -0.440214 \tabularnewline
26 & 96.68 & 96.3526 & 95.2421 & 1.11056 & 0.327355 \tabularnewline
27 & 94.94 & 95.7318 & 95.4021 & 0.329728 & -0.791811 \tabularnewline
28 & 93.9 & 95.591 & 95.6058 & -0.0148553 & -1.69098 \tabularnewline
29 & 94.83 & 95.5976 & 95.8687 & -0.271175 & -0.767575 \tabularnewline
30 & 96.27 & 96.11 & 96.2062 & -0.0962442 & 0.159994 \tabularnewline
31 & 96.51 & 96.5283 & 96.5662 & -0.0379803 & -0.0182697 \tabularnewline
32 & 96.69 & 96.3982 & 96.8675 & -0.4693 & 0.2918 \tabularnewline
33 & 97.47 & 97.1233 & 97.1208 & 0.00243634 & 0.34673 \tabularnewline
34 & 96.41 & 96.4447 & 97.4404 & -0.995689 & -0.034728 \tabularnewline
35 & 98.68 & 98.0124 & 97.7896 & 0.222784 & 0.667633 \tabularnewline
36 & 99.3 & 97.9054 & 98.0246 & -0.11923 & 1.39465 \tabularnewline
37 & 99.22 & 98.551 & 98.2121 & 0.338964 & 0.668953 \tabularnewline
38 & 99.7 & 99.4972 & 98.3867 & 1.11056 & 0.202772 \tabularnewline
39 & 98 & 98.8751 & 98.5454 & 0.329728 & -0.875145 \tabularnewline
40 & 98.51 & 98.7418 & 98.7567 & -0.0148553 & -0.231811 \tabularnewline
41 & 98.6 & 98.713 & 98.9842 & -0.271175 & -0.112992 \tabularnewline
42 & 98.14 & 99.0717 & 99.1679 & -0.0962442 & -0.931672 \tabularnewline
43 & 99.14 & 99.3054 & 99.3433 & -0.0379803 & -0.165353 \tabularnewline
44 & 98.25 & 99.117 & 99.5862 & -0.4693 & -0.86695 \tabularnewline
45 & 99.72 & 99.9091 & 99.9067 & 0.00243634 & -0.189103 \tabularnewline
46 & 99.23 & 99.1526 & 100.148 & -0.995689 & 0.0773553 \tabularnewline
47 & 101.32 & 100.441 & 100.218 & 0.222784 & 0.878883 \tabularnewline
48 & 101.07 & 100.162 & 100.281 & -0.11923 & 0.908397 \tabularnewline
49 & 101.66 & 100.699 & 100.36 & 0.338964 & 0.960619 \tabularnewline
50 & 103.09 & 101.548 & 100.438 & 1.11056 & 1.54152 \tabularnewline
51 & 102.3 & 100.789 & 100.46 & 0.329728 & 1.51069 \tabularnewline
52 & 100.01 & 100.361 & 100.376 & -0.0148553 & -0.350978 \tabularnewline
53 & 98.78 & 99.9709 & 100.242 & -0.271175 & -1.19091 \tabularnewline
54 & 99.46 & 99.9842 & 100.08 & -0.0962442 & -0.524172 \tabularnewline
55 & 99.73 & 99.8883 & 99.9262 & -0.0379803 & -0.15827 \tabularnewline
56 & 99.52 & 99.2665 & 99.7358 & -0.4693 & 0.253466 \tabularnewline
57 & 98.97 & 99.5079 & 99.5054 & 0.00243634 & -0.537853 \tabularnewline
58 & 97.97 & 98.4418 & 99.4375 & -0.995689 & -0.471811 \tabularnewline
59 & 99.37 & 99.817 & 99.5942 & 0.222784 & -0.44695 \tabularnewline
60 & 99.14 & 99.642 & 99.7613 & -0.11923 & -0.50202 \tabularnewline
61 & 99.89 & 100.22 & 99.8813 & 0.338964 & -0.330214 \tabularnewline
62 & 100.29 & 101.07 & 99.9592 & 1.11056 & -0.779728 \tabularnewline
63 & 99.57 & 100.37 & 100.04 & 0.329728 & -0.799728 \tabularnewline
64 & 101.11 & 100.191 & 100.206 & -0.0148553 & 0.919022 \tabularnewline
65 & 101.44 & 100.108 & 100.379 & -0.271175 & 1.33201 \tabularnewline
66 & 100.81 & 100.448 & 100.545 & -0.0962442 & 0.361661 \tabularnewline
67 & 101.26 & 100.69 & 100.727 & -0.0379803 & 0.57048 \tabularnewline
68 & 99.86 & 100.412 & 100.882 & -0.4693 & -0.552367 \tabularnewline
69 & 100.57 & 101.082 & 101.08 & 0.00243634 & -0.512436 \tabularnewline
70 & 100.35 & 100.278 & 101.274 & -0.995689 & 0.0719387 \tabularnewline
71 & 101.15 & 101.587 & 101.364 & 0.222784 & -0.43695 \tabularnewline
72 & 101.33 & 101.345 & 101.464 & -0.11923 & -0.0149363 \tabularnewline
73 & 102.09 & 101.939 & 101.6 & 0.338964 & 0.151453 \tabularnewline
74 & 101.79 & 102.872 & 101.762 & 1.11056 & -1.08223 \tabularnewline
75 & 102.83 & 102.297 & 101.967 & 0.329728 & 0.532772 \tabularnewline
76 & 102.5 & 102.19 & 102.205 & -0.0148553 & 0.310272 \tabularnewline
77 & 102.22 & 102.157 & 102.428 & -0.271175 & 0.0632581 \tabularnewline
78 & 102.43 & 102.528 & 102.624 & -0.0962442 & -0.0975058 \tabularnewline
79 & 102.89 & NA & NA & -0.0379803 & NA \tabularnewline
80 & 102.12 & NA & NA & -0.4693 & NA \tabularnewline
81 & 103.25 & NA & NA & 0.00243634 & NA \tabularnewline
82 & 103.36 & NA & NA & -0.995689 & NA \tabularnewline
83 & 103.5 & NA & NA & 0.222784 & NA \tabularnewline
84 & 103.68 & NA & NA & -0.11923 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294734&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]94.65[/C][C]NA[/C][C]NA[/C][C]0.338964[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]94.16[/C][C]NA[/C][C]NA[/C][C]1.11056[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]93.91[/C][C]NA[/C][C]NA[/C][C]0.329728[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]93.21[/C][C]NA[/C][C]NA[/C][C]-0.0148553[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]92.81[/C][C]NA[/C][C]NA[/C][C]-0.271175[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]93.55[/C][C]NA[/C][C]NA[/C][C]-0.0962442[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]93.03[/C][C]93.3783[/C][C]93.4162[/C][C]-0.0379803[/C][C]-0.34827[/C][/ROW]
[ROW][C]8[/C][C]93.25[/C][C]92.937[/C][C]93.4062[/C][C]-0.4693[/C][C]0.31305[/C][/ROW]
[ROW][C]9[/C][C]94.24[/C][C]93.5004[/C][C]93.4979[/C][C]0.00243634[/C][C]0.739647[/C][/ROW]
[ROW][C]10[/C][C]93.23[/C][C]92.6464[/C][C]93.6421[/C][C]-0.995689[/C][C]0.583605[/C][/ROW]
[ROW][C]11[/C][C]93.52[/C][C]94.0465[/C][C]93.8237[/C][C]0.222784[/C][C]-0.526534[/C][/ROW]
[ROW][C]12[/C][C]92.05[/C][C]93.8791[/C][C]93.9983[/C][C]-0.11923[/C][C]-1.8291[/C][/ROW]
[ROW][C]13[/C][C]93.42[/C][C]94.5044[/C][C]94.1654[/C][C]0.338964[/C][C]-1.08438[/C][/ROW]
[ROW][C]14[/C][C]95.15[/C][C]95.4335[/C][C]94.3229[/C][C]1.11056[/C][C]-0.283478[/C][/ROW]
[ROW][C]15[/C][C]95.12[/C][C]94.7706[/C][C]94.4408[/C][C]0.329728[/C][C]0.349439[/C][/ROW]
[ROW][C]16[/C][C]95.46[/C][C]94.4893[/C][C]94.5042[/C][C]-0.0148553[/C][C]0.970689[/C][/ROW]
[ROW][C]17[/C][C]94.92[/C][C]94.3176[/C][C]94.5887[/C][C]-0.271175[/C][C]0.602425[/C][/ROW]
[ROW][C]18[/C][C]95.63[/C][C]94.6721[/C][C]94.7683[/C][C]-0.0962442[/C][C]0.957911[/C][/ROW]
[ROW][C]19[/C][C]94.96[/C][C]94.9141[/C][C]94.9521[/C][C]-0.0379803[/C][C]0.045897[/C][/ROW]
[ROW][C]20[/C][C]95.1[/C][C]94.6128[/C][C]95.0821[/C][C]-0.4693[/C][C]0.487216[/C][/ROW]
[ROW][C]21[/C][C]95.22[/C][C]95.1408[/C][C]95.1383[/C][C]0.00243634[/C][C]0.0792303[/C][/ROW]
[ROW][C]22[/C][C]93.77[/C][C]94.0701[/C][C]95.0658[/C][C]-0.995689[/C][C]-0.300145[/C][/ROW]
[ROW][C]23[/C][C]95.01[/C][C]95.2199[/C][C]94.9971[/C][C]0.222784[/C][C]-0.209867[/C][/ROW]
[ROW][C]24[/C][C]94.87[/C][C]94.9008[/C][C]95.02[/C][C]-0.11923[/C][C]-0.0307697[/C][/ROW]
[ROW][C]25[/C][C]95.01[/C][C]95.4502[/C][C]95.1112[/C][C]0.338964[/C][C]-0.440214[/C][/ROW]
[ROW][C]26[/C][C]96.68[/C][C]96.3526[/C][C]95.2421[/C][C]1.11056[/C][C]0.327355[/C][/ROW]
[ROW][C]27[/C][C]94.94[/C][C]95.7318[/C][C]95.4021[/C][C]0.329728[/C][C]-0.791811[/C][/ROW]
[ROW][C]28[/C][C]93.9[/C][C]95.591[/C][C]95.6058[/C][C]-0.0148553[/C][C]-1.69098[/C][/ROW]
[ROW][C]29[/C][C]94.83[/C][C]95.5976[/C][C]95.8687[/C][C]-0.271175[/C][C]-0.767575[/C][/ROW]
[ROW][C]30[/C][C]96.27[/C][C]96.11[/C][C]96.2062[/C][C]-0.0962442[/C][C]0.159994[/C][/ROW]
[ROW][C]31[/C][C]96.51[/C][C]96.5283[/C][C]96.5662[/C][C]-0.0379803[/C][C]-0.0182697[/C][/ROW]
[ROW][C]32[/C][C]96.69[/C][C]96.3982[/C][C]96.8675[/C][C]-0.4693[/C][C]0.2918[/C][/ROW]
[ROW][C]33[/C][C]97.47[/C][C]97.1233[/C][C]97.1208[/C][C]0.00243634[/C][C]0.34673[/C][/ROW]
[ROW][C]34[/C][C]96.41[/C][C]96.4447[/C][C]97.4404[/C][C]-0.995689[/C][C]-0.034728[/C][/ROW]
[ROW][C]35[/C][C]98.68[/C][C]98.0124[/C][C]97.7896[/C][C]0.222784[/C][C]0.667633[/C][/ROW]
[ROW][C]36[/C][C]99.3[/C][C]97.9054[/C][C]98.0246[/C][C]-0.11923[/C][C]1.39465[/C][/ROW]
[ROW][C]37[/C][C]99.22[/C][C]98.551[/C][C]98.2121[/C][C]0.338964[/C][C]0.668953[/C][/ROW]
[ROW][C]38[/C][C]99.7[/C][C]99.4972[/C][C]98.3867[/C][C]1.11056[/C][C]0.202772[/C][/ROW]
[ROW][C]39[/C][C]98[/C][C]98.8751[/C][C]98.5454[/C][C]0.329728[/C][C]-0.875145[/C][/ROW]
[ROW][C]40[/C][C]98.51[/C][C]98.7418[/C][C]98.7567[/C][C]-0.0148553[/C][C]-0.231811[/C][/ROW]
[ROW][C]41[/C][C]98.6[/C][C]98.713[/C][C]98.9842[/C][C]-0.271175[/C][C]-0.112992[/C][/ROW]
[ROW][C]42[/C][C]98.14[/C][C]99.0717[/C][C]99.1679[/C][C]-0.0962442[/C][C]-0.931672[/C][/ROW]
[ROW][C]43[/C][C]99.14[/C][C]99.3054[/C][C]99.3433[/C][C]-0.0379803[/C][C]-0.165353[/C][/ROW]
[ROW][C]44[/C][C]98.25[/C][C]99.117[/C][C]99.5862[/C][C]-0.4693[/C][C]-0.86695[/C][/ROW]
[ROW][C]45[/C][C]99.72[/C][C]99.9091[/C][C]99.9067[/C][C]0.00243634[/C][C]-0.189103[/C][/ROW]
[ROW][C]46[/C][C]99.23[/C][C]99.1526[/C][C]100.148[/C][C]-0.995689[/C][C]0.0773553[/C][/ROW]
[ROW][C]47[/C][C]101.32[/C][C]100.441[/C][C]100.218[/C][C]0.222784[/C][C]0.878883[/C][/ROW]
[ROW][C]48[/C][C]101.07[/C][C]100.162[/C][C]100.281[/C][C]-0.11923[/C][C]0.908397[/C][/ROW]
[ROW][C]49[/C][C]101.66[/C][C]100.699[/C][C]100.36[/C][C]0.338964[/C][C]0.960619[/C][/ROW]
[ROW][C]50[/C][C]103.09[/C][C]101.548[/C][C]100.438[/C][C]1.11056[/C][C]1.54152[/C][/ROW]
[ROW][C]51[/C][C]102.3[/C][C]100.789[/C][C]100.46[/C][C]0.329728[/C][C]1.51069[/C][/ROW]
[ROW][C]52[/C][C]100.01[/C][C]100.361[/C][C]100.376[/C][C]-0.0148553[/C][C]-0.350978[/C][/ROW]
[ROW][C]53[/C][C]98.78[/C][C]99.9709[/C][C]100.242[/C][C]-0.271175[/C][C]-1.19091[/C][/ROW]
[ROW][C]54[/C][C]99.46[/C][C]99.9842[/C][C]100.08[/C][C]-0.0962442[/C][C]-0.524172[/C][/ROW]
[ROW][C]55[/C][C]99.73[/C][C]99.8883[/C][C]99.9262[/C][C]-0.0379803[/C][C]-0.15827[/C][/ROW]
[ROW][C]56[/C][C]99.52[/C][C]99.2665[/C][C]99.7358[/C][C]-0.4693[/C][C]0.253466[/C][/ROW]
[ROW][C]57[/C][C]98.97[/C][C]99.5079[/C][C]99.5054[/C][C]0.00243634[/C][C]-0.537853[/C][/ROW]
[ROW][C]58[/C][C]97.97[/C][C]98.4418[/C][C]99.4375[/C][C]-0.995689[/C][C]-0.471811[/C][/ROW]
[ROW][C]59[/C][C]99.37[/C][C]99.817[/C][C]99.5942[/C][C]0.222784[/C][C]-0.44695[/C][/ROW]
[ROW][C]60[/C][C]99.14[/C][C]99.642[/C][C]99.7613[/C][C]-0.11923[/C][C]-0.50202[/C][/ROW]
[ROW][C]61[/C][C]99.89[/C][C]100.22[/C][C]99.8813[/C][C]0.338964[/C][C]-0.330214[/C][/ROW]
[ROW][C]62[/C][C]100.29[/C][C]101.07[/C][C]99.9592[/C][C]1.11056[/C][C]-0.779728[/C][/ROW]
[ROW][C]63[/C][C]99.57[/C][C]100.37[/C][C]100.04[/C][C]0.329728[/C][C]-0.799728[/C][/ROW]
[ROW][C]64[/C][C]101.11[/C][C]100.191[/C][C]100.206[/C][C]-0.0148553[/C][C]0.919022[/C][/ROW]
[ROW][C]65[/C][C]101.44[/C][C]100.108[/C][C]100.379[/C][C]-0.271175[/C][C]1.33201[/C][/ROW]
[ROW][C]66[/C][C]100.81[/C][C]100.448[/C][C]100.545[/C][C]-0.0962442[/C][C]0.361661[/C][/ROW]
[ROW][C]67[/C][C]101.26[/C][C]100.69[/C][C]100.727[/C][C]-0.0379803[/C][C]0.57048[/C][/ROW]
[ROW][C]68[/C][C]99.86[/C][C]100.412[/C][C]100.882[/C][C]-0.4693[/C][C]-0.552367[/C][/ROW]
[ROW][C]69[/C][C]100.57[/C][C]101.082[/C][C]101.08[/C][C]0.00243634[/C][C]-0.512436[/C][/ROW]
[ROW][C]70[/C][C]100.35[/C][C]100.278[/C][C]101.274[/C][C]-0.995689[/C][C]0.0719387[/C][/ROW]
[ROW][C]71[/C][C]101.15[/C][C]101.587[/C][C]101.364[/C][C]0.222784[/C][C]-0.43695[/C][/ROW]
[ROW][C]72[/C][C]101.33[/C][C]101.345[/C][C]101.464[/C][C]-0.11923[/C][C]-0.0149363[/C][/ROW]
[ROW][C]73[/C][C]102.09[/C][C]101.939[/C][C]101.6[/C][C]0.338964[/C][C]0.151453[/C][/ROW]
[ROW][C]74[/C][C]101.79[/C][C]102.872[/C][C]101.762[/C][C]1.11056[/C][C]-1.08223[/C][/ROW]
[ROW][C]75[/C][C]102.83[/C][C]102.297[/C][C]101.967[/C][C]0.329728[/C][C]0.532772[/C][/ROW]
[ROW][C]76[/C][C]102.5[/C][C]102.19[/C][C]102.205[/C][C]-0.0148553[/C][C]0.310272[/C][/ROW]
[ROW][C]77[/C][C]102.22[/C][C]102.157[/C][C]102.428[/C][C]-0.271175[/C][C]0.0632581[/C][/ROW]
[ROW][C]78[/C][C]102.43[/C][C]102.528[/C][C]102.624[/C][C]-0.0962442[/C][C]-0.0975058[/C][/ROW]
[ROW][C]79[/C][C]102.89[/C][C]NA[/C][C]NA[/C][C]-0.0379803[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]102.12[/C][C]NA[/C][C]NA[/C][C]-0.4693[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]103.25[/C][C]NA[/C][C]NA[/C][C]0.00243634[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]103.36[/C][C]NA[/C][C]NA[/C][C]-0.995689[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]103.5[/C][C]NA[/C][C]NA[/C][C]0.222784[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]103.68[/C][C]NA[/C][C]NA[/C][C]-0.11923[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294734&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	94.65	NA	NA	0.338964	NA
2	94.16	NA	NA	1.11056	NA
3	93.91	NA	NA	0.329728	NA
4	93.21	NA	NA	-0.0148553	NA
5	92.81	NA	NA	-0.271175	NA
6	93.55	NA	NA	-0.0962442	NA
7	93.03	93.3783	93.4162	-0.0379803	-0.34827
8	93.25	92.937	93.4062	-0.4693	0.31305
9	94.24	93.5004	93.4979	0.00243634	0.739647
10	93.23	92.6464	93.6421	-0.995689	0.583605
11	93.52	94.0465	93.8237	0.222784	-0.526534
12	92.05	93.8791	93.9983	-0.11923	-1.8291
13	93.42	94.5044	94.1654	0.338964	-1.08438
14	95.15	95.4335	94.3229	1.11056	-0.283478
15	95.12	94.7706	94.4408	0.329728	0.349439
16	95.46	94.4893	94.5042	-0.0148553	0.970689
17	94.92	94.3176	94.5887	-0.271175	0.602425
18	95.63	94.6721	94.7683	-0.0962442	0.957911
19	94.96	94.9141	94.9521	-0.0379803	0.045897
20	95.1	94.6128	95.0821	-0.4693	0.487216
21	95.22	95.1408	95.1383	0.00243634	0.0792303
22	93.77	94.0701	95.0658	-0.995689	-0.300145
23	95.01	95.2199	94.9971	0.222784	-0.209867
24	94.87	94.9008	95.02	-0.11923	-0.0307697
25	95.01	95.4502	95.1112	0.338964	-0.440214
26	96.68	96.3526	95.2421	1.11056	0.327355
27	94.94	95.7318	95.4021	0.329728	-0.791811
28	93.9	95.591	95.6058	-0.0148553	-1.69098
29	94.83	95.5976	95.8687	-0.271175	-0.767575
30	96.27	96.11	96.2062	-0.0962442	0.159994
31	96.51	96.5283	96.5662	-0.0379803	-0.0182697
32	96.69	96.3982	96.8675	-0.4693	0.2918
33	97.47	97.1233	97.1208	0.00243634	0.34673
34	96.41	96.4447	97.4404	-0.995689	-0.034728
35	98.68	98.0124	97.7896	0.222784	0.667633
36	99.3	97.9054	98.0246	-0.11923	1.39465
37	99.22	98.551	98.2121	0.338964	0.668953
38	99.7	99.4972	98.3867	1.11056	0.202772
39	98	98.8751	98.5454	0.329728	-0.875145
40	98.51	98.7418	98.7567	-0.0148553	-0.231811
41	98.6	98.713	98.9842	-0.271175	-0.112992
42	98.14	99.0717	99.1679	-0.0962442	-0.931672
43	99.14	99.3054	99.3433	-0.0379803	-0.165353
44	98.25	99.117	99.5862	-0.4693	-0.86695
45	99.72	99.9091	99.9067	0.00243634	-0.189103
46	99.23	99.1526	100.148	-0.995689	0.0773553
47	101.32	100.441	100.218	0.222784	0.878883
48	101.07	100.162	100.281	-0.11923	0.908397
49	101.66	100.699	100.36	0.338964	0.960619
50	103.09	101.548	100.438	1.11056	1.54152
51	102.3	100.789	100.46	0.329728	1.51069
52	100.01	100.361	100.376	-0.0148553	-0.350978
53	98.78	99.9709	100.242	-0.271175	-1.19091
54	99.46	99.9842	100.08	-0.0962442	-0.524172
55	99.73	99.8883	99.9262	-0.0379803	-0.15827
56	99.52	99.2665	99.7358	-0.4693	0.253466
57	98.97	99.5079	99.5054	0.00243634	-0.537853
58	97.97	98.4418	99.4375	-0.995689	-0.471811
59	99.37	99.817	99.5942	0.222784	-0.44695
60	99.14	99.642	99.7613	-0.11923	-0.50202
61	99.89	100.22	99.8813	0.338964	-0.330214
62	100.29	101.07	99.9592	1.11056	-0.779728
63	99.57	100.37	100.04	0.329728	-0.799728
64	101.11	100.191	100.206	-0.0148553	0.919022
65	101.44	100.108	100.379	-0.271175	1.33201
66	100.81	100.448	100.545	-0.0962442	0.361661
67	101.26	100.69	100.727	-0.0379803	0.57048
68	99.86	100.412	100.882	-0.4693	-0.552367
69	100.57	101.082	101.08	0.00243634	-0.512436
70	100.35	100.278	101.274	-0.995689	0.0719387
71	101.15	101.587	101.364	0.222784	-0.43695
72	101.33	101.345	101.464	-0.11923	-0.0149363
73	102.09	101.939	101.6	0.338964	0.151453
74	101.79	102.872	101.762	1.11056	-1.08223
75	102.83	102.297	101.967	0.329728	0.532772
76	102.5	102.19	102.205	-0.0148553	0.310272
77	102.22	102.157	102.428	-0.271175	0.0632581
78	102.43	102.528	102.624	-0.0962442	-0.0975058
79	102.89	NA	NA	-0.0379803	NA
80	102.12	NA	NA	-0.4693	NA
81	103.25	NA	NA	0.00243634	NA
82	103.36	NA	NA	-0.995689	NA
83	103.5	NA	NA	0.222784	NA
84	103.68	NA	NA	-0.11923	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