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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Tue, 24 Nov 2015 20:00:22 +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/24/t1448395255h5lykiip8y1srdd.htm/, Retrieved Mon, 13 May 2024 20:39:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284056, Retrieved Mon, 13 May 2024 20:39:46 +0000

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-       [Classical Decomposition] [kaas en melk opga...] [2015-11-24 20:00:22] [c4e632f9a17048eeb9519d4e8ae83546] [Current]
- R PD    [Classical Decomposition] [oefening 9 additi...] [2015-12-14 19:17:24] [1625b1453ed47b256ce4b6eedb089cd5] 

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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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284056&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284056&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284056&T=0

As an alternative you can also use a QR Code:

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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	79.58	NA	NA	1.00565	NA
2	80.08	NA	NA	1.00602	NA
3	80.41	NA	NA	1.0043	NA
4	80.34	NA	NA	1.00237	NA
5	80.32	NA	NA	1.00041	NA
6	80.39	NA	NA	0.996619	NA
7	81.01	82.4465	83.0108	0.993202	0.982576
8	81.54	83.6299	84.0988	0.994425	0.97501
9	82.48	84.7403	85.1987	0.994619	0.973327
10	84.68	86.0492	86.3133	0.996939	0.984089
11	88.26	87.633	87.4458	1.00214	1.00715
12	90.6	88.8587	88.5658	1.00331	1.0196
13	92.46	90.1574	89.6504	1.00565	1.02554
14	93.31	91.2446	90.6988	1.00602	1.02264
15	93.58	92.0852	91.6913	1.0043	1.01623
16	93.92	92.7774	92.5579	1.00237	1.01232
17	93.92	93.2234	93.1854	1.00041	1.00747
18	93.67	93.22	93.5363	0.996619	1.00483
19	93.76	93.0605	93.6975	0.993202	1.00752
20	93.95	93.2315	93.7542	0.994425	1.00771
21	93.89	93.2538	93.7583	0.994619	1.00682
22	94.07	93.4431	93.73	0.996939	1.00671
23	93.93	93.8768	93.6762	1.00214	1.00057
24	93.35	93.9245	93.615	1.00331	0.993883
25	93.58	94.0979	93.5688	1.00565	0.994497
26	93.55	94.1231	93.56	1.00602	0.993911
27	93.44	93.977	93.575	1.0043	0.994285
28	93.38	93.8015	93.5796	1.00237	0.995507
29	93.17	93.6374	93.5992	1.00041	0.995009
30	92.95	93.3657	93.6825	0.996619	0.995547
31	93.37	93.1309	93.7683	0.993202	1.00257
32	94.13	93.2949	93.8179	0.994425	1.00895
33	94.07	93.3591	93.8642	0.994619	1.00762
34	94	93.5922	93.8796	0.996939	1.00436
35	94.47	94.0726	93.8717	1.00214	1.00422
36	94.81	94.162	93.8517	1.00331	1.00688
37	94.18	94.3271	93.7967	1.00565	0.998441
38	94.14	94.2656	93.7017	1.00602	0.998668
39	93.96	93.9904	93.5883	1.0043	0.999676
40	93.23	93.7063	93.4846	1.00237	0.994917
41	93.13	93.4064	93.3683	1.00041	0.997041
42	92.51	92.9214	93.2367	0.996619	0.995573
43	92.49	92.5308	93.1642	0.993202	0.999559
44	92.73	92.6448	93.1642	0.994425	1.00092
45	92.75	92.6964	93.1979	0.994619	1.00058
46	92.83	92.9957	93.2812	0.996939	0.998218
47	92.85	93.6095	93.4096	1.00214	0.991886
48	93.27	93.8961	93.5867	1.00331	0.993332
49	93.98	94.3585	93.8279	1.00565	0.995989
50	94.34	94.6676	94.1012	1.00602	0.99654
51	94.57	94.8035	94.3979	1.0043	0.997537
52	94.62	94.9283	94.7037	1.00237	0.996752
53	94.82	95.055	95.0162	1.00041	0.997527
54	95.07	95.0147	95.3371	0.996619	1.00058
55	95.72	94.9811	95.6312	0.993202	1.00778
56	96.06	95.3642	95.8987	0.994425	1.0073
57	96.54	95.6517	96.1692	0.994619	1.00929
58	96.38	96.1427	96.4379	0.996939	1.00247
59	96.8	96.8899	96.6829	1.00214	0.999073
60	97.02	97.2154	96.895	1.00331	0.99799
61	97.29	97.608	97.0592	1.00565	0.996742
62	97.45	97.7967	97.2117	1.00602	0.996455
63	97.95	97.7883	97.37	1.0043	1.00165
64	97.69	97.7659	97.5346	1.00237	0.999224
65	97.63	97.747	97.7071	1.00041	0.998803
66	97.35	97.532	97.8629	0.996619	0.998134
67	97.38	97.3491	98.0154	0.993202	1.00032
68	98.06	97.6439	98.1912	0.994425	1.00426
69	98.34	97.8369	98.3662	0.994619	1.00514
70	98.53	98.2326	98.5342	0.996939	1.00303
71	98.79	98.9284	98.7171	1.00214	0.998601
72	98.77	99.2266	98.8996	1.00331	0.995399
73	99.2	99.6436	99.0833	1.00565	0.995548
74	99.76	99.839	99.2417	1.00602	0.999209
75	99.84	99.7965	99.3696	1.0043	1.00044
76	99.83	99.7606	99.5246	1.00237	1.0007
77	99.88	99.7557	99.715	1.00041	1.00125
78	99.48	99.5697	99.9075	0.996619	0.999099
79	99.66	99.4162	100.097	0.993202	1.00245
80	99.58	99.7173	100.276	0.994425	0.998624
81	99.89	99.8904	100.431	0.994619	0.999996
82	100.7	100.309	100.617	0.996939	1.0039
83	101.19	101.063	100.847	1.00214	1.00126
84	100.99	101.428	101.093	1.00331	0.995686
85	101.52	101.926	101.353	1.00565	0.996012
86	101.75	102.225	101.614	1.00602	0.99535
87	101.56	102.281	101.844	1.0043	0.992948
88	102.57	102.227	101.985	1.00237	1.00336
89	102.66	102.081	102.04	1.00041	1.00567
90	102.62	101.704	102.049	0.996619	1.00901
91	102.76	NA	NA	0.993202	NA
92	102.73	NA	NA	0.994425	NA
93	102.26	NA	NA	0.994619	NA
94	101.72	NA	NA	0.996939	NA
95	101.48	NA	NA	1.00214	NA
96	100.93	NA	NA	1.00331	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 79.58 & NA & NA & 1.00565 & NA \tabularnewline
2 & 80.08 & NA & NA & 1.00602 & NA \tabularnewline
3 & 80.41 & NA & NA & 1.0043 & NA \tabularnewline
4 & 80.34 & NA & NA & 1.00237 & NA \tabularnewline
5 & 80.32 & NA & NA & 1.00041 & NA \tabularnewline
6 & 80.39 & NA & NA & 0.996619 & NA \tabularnewline
7 & 81.01 & 82.4465 & 83.0108 & 0.993202 & 0.982576 \tabularnewline
8 & 81.54 & 83.6299 & 84.0988 & 0.994425 & 0.97501 \tabularnewline
9 & 82.48 & 84.7403 & 85.1987 & 0.994619 & 0.973327 \tabularnewline
10 & 84.68 & 86.0492 & 86.3133 & 0.996939 & 0.984089 \tabularnewline
11 & 88.26 & 87.633 & 87.4458 & 1.00214 & 1.00715 \tabularnewline
12 & 90.6 & 88.8587 & 88.5658 & 1.00331 & 1.0196 \tabularnewline
13 & 92.46 & 90.1574 & 89.6504 & 1.00565 & 1.02554 \tabularnewline
14 & 93.31 & 91.2446 & 90.6988 & 1.00602 & 1.02264 \tabularnewline
15 & 93.58 & 92.0852 & 91.6913 & 1.0043 & 1.01623 \tabularnewline
16 & 93.92 & 92.7774 & 92.5579 & 1.00237 & 1.01232 \tabularnewline
17 & 93.92 & 93.2234 & 93.1854 & 1.00041 & 1.00747 \tabularnewline
18 & 93.67 & 93.22 & 93.5363 & 0.996619 & 1.00483 \tabularnewline
19 & 93.76 & 93.0605 & 93.6975 & 0.993202 & 1.00752 \tabularnewline
20 & 93.95 & 93.2315 & 93.7542 & 0.994425 & 1.00771 \tabularnewline
21 & 93.89 & 93.2538 & 93.7583 & 0.994619 & 1.00682 \tabularnewline
22 & 94.07 & 93.4431 & 93.73 & 0.996939 & 1.00671 \tabularnewline
23 & 93.93 & 93.8768 & 93.6762 & 1.00214 & 1.00057 \tabularnewline
24 & 93.35 & 93.9245 & 93.615 & 1.00331 & 0.993883 \tabularnewline
25 & 93.58 & 94.0979 & 93.5688 & 1.00565 & 0.994497 \tabularnewline
26 & 93.55 & 94.1231 & 93.56 & 1.00602 & 0.993911 \tabularnewline
27 & 93.44 & 93.977 & 93.575 & 1.0043 & 0.994285 \tabularnewline
28 & 93.38 & 93.8015 & 93.5796 & 1.00237 & 0.995507 \tabularnewline
29 & 93.17 & 93.6374 & 93.5992 & 1.00041 & 0.995009 \tabularnewline
30 & 92.95 & 93.3657 & 93.6825 & 0.996619 & 0.995547 \tabularnewline
31 & 93.37 & 93.1309 & 93.7683 & 0.993202 & 1.00257 \tabularnewline
32 & 94.13 & 93.2949 & 93.8179 & 0.994425 & 1.00895 \tabularnewline
33 & 94.07 & 93.3591 & 93.8642 & 0.994619 & 1.00762 \tabularnewline
34 & 94 & 93.5922 & 93.8796 & 0.996939 & 1.00436 \tabularnewline
35 & 94.47 & 94.0726 & 93.8717 & 1.00214 & 1.00422 \tabularnewline
36 & 94.81 & 94.162 & 93.8517 & 1.00331 & 1.00688 \tabularnewline
37 & 94.18 & 94.3271 & 93.7967 & 1.00565 & 0.998441 \tabularnewline
38 & 94.14 & 94.2656 & 93.7017 & 1.00602 & 0.998668 \tabularnewline
39 & 93.96 & 93.9904 & 93.5883 & 1.0043 & 0.999676 \tabularnewline
40 & 93.23 & 93.7063 & 93.4846 & 1.00237 & 0.994917 \tabularnewline
41 & 93.13 & 93.4064 & 93.3683 & 1.00041 & 0.997041 \tabularnewline
42 & 92.51 & 92.9214 & 93.2367 & 0.996619 & 0.995573 \tabularnewline
43 & 92.49 & 92.5308 & 93.1642 & 0.993202 & 0.999559 \tabularnewline
44 & 92.73 & 92.6448 & 93.1642 & 0.994425 & 1.00092 \tabularnewline
45 & 92.75 & 92.6964 & 93.1979 & 0.994619 & 1.00058 \tabularnewline
46 & 92.83 & 92.9957 & 93.2812 & 0.996939 & 0.998218 \tabularnewline
47 & 92.85 & 93.6095 & 93.4096 & 1.00214 & 0.991886 \tabularnewline
48 & 93.27 & 93.8961 & 93.5867 & 1.00331 & 0.993332 \tabularnewline
49 & 93.98 & 94.3585 & 93.8279 & 1.00565 & 0.995989 \tabularnewline
50 & 94.34 & 94.6676 & 94.1012 & 1.00602 & 0.99654 \tabularnewline
51 & 94.57 & 94.8035 & 94.3979 & 1.0043 & 0.997537 \tabularnewline
52 & 94.62 & 94.9283 & 94.7037 & 1.00237 & 0.996752 \tabularnewline
53 & 94.82 & 95.055 & 95.0162 & 1.00041 & 0.997527 \tabularnewline
54 & 95.07 & 95.0147 & 95.3371 & 0.996619 & 1.00058 \tabularnewline
55 & 95.72 & 94.9811 & 95.6312 & 0.993202 & 1.00778 \tabularnewline
56 & 96.06 & 95.3642 & 95.8987 & 0.994425 & 1.0073 \tabularnewline
57 & 96.54 & 95.6517 & 96.1692 & 0.994619 & 1.00929 \tabularnewline
58 & 96.38 & 96.1427 & 96.4379 & 0.996939 & 1.00247 \tabularnewline
59 & 96.8 & 96.8899 & 96.6829 & 1.00214 & 0.999073 \tabularnewline
60 & 97.02 & 97.2154 & 96.895 & 1.00331 & 0.99799 \tabularnewline
61 & 97.29 & 97.608 & 97.0592 & 1.00565 & 0.996742 \tabularnewline
62 & 97.45 & 97.7967 & 97.2117 & 1.00602 & 0.996455 \tabularnewline
63 & 97.95 & 97.7883 & 97.37 & 1.0043 & 1.00165 \tabularnewline
64 & 97.69 & 97.7659 & 97.5346 & 1.00237 & 0.999224 \tabularnewline
65 & 97.63 & 97.747 & 97.7071 & 1.00041 & 0.998803 \tabularnewline
66 & 97.35 & 97.532 & 97.8629 & 0.996619 & 0.998134 \tabularnewline
67 & 97.38 & 97.3491 & 98.0154 & 0.993202 & 1.00032 \tabularnewline
68 & 98.06 & 97.6439 & 98.1912 & 0.994425 & 1.00426 \tabularnewline
69 & 98.34 & 97.8369 & 98.3662 & 0.994619 & 1.00514 \tabularnewline
70 & 98.53 & 98.2326 & 98.5342 & 0.996939 & 1.00303 \tabularnewline
71 & 98.79 & 98.9284 & 98.7171 & 1.00214 & 0.998601 \tabularnewline
72 & 98.77 & 99.2266 & 98.8996 & 1.00331 & 0.995399 \tabularnewline
73 & 99.2 & 99.6436 & 99.0833 & 1.00565 & 0.995548 \tabularnewline
74 & 99.76 & 99.839 & 99.2417 & 1.00602 & 0.999209 \tabularnewline
75 & 99.84 & 99.7965 & 99.3696 & 1.0043 & 1.00044 \tabularnewline
76 & 99.83 & 99.7606 & 99.5246 & 1.00237 & 1.0007 \tabularnewline
77 & 99.88 & 99.7557 & 99.715 & 1.00041 & 1.00125 \tabularnewline
78 & 99.48 & 99.5697 & 99.9075 & 0.996619 & 0.999099 \tabularnewline
79 & 99.66 & 99.4162 & 100.097 & 0.993202 & 1.00245 \tabularnewline
80 & 99.58 & 99.7173 & 100.276 & 0.994425 & 0.998624 \tabularnewline
81 & 99.89 & 99.8904 & 100.431 & 0.994619 & 0.999996 \tabularnewline
82 & 100.7 & 100.309 & 100.617 & 0.996939 & 1.0039 \tabularnewline
83 & 101.19 & 101.063 & 100.847 & 1.00214 & 1.00126 \tabularnewline
84 & 100.99 & 101.428 & 101.093 & 1.00331 & 0.995686 \tabularnewline
85 & 101.52 & 101.926 & 101.353 & 1.00565 & 0.996012 \tabularnewline
86 & 101.75 & 102.225 & 101.614 & 1.00602 & 0.99535 \tabularnewline
87 & 101.56 & 102.281 & 101.844 & 1.0043 & 0.992948 \tabularnewline
88 & 102.57 & 102.227 & 101.985 & 1.00237 & 1.00336 \tabularnewline
89 & 102.66 & 102.081 & 102.04 & 1.00041 & 1.00567 \tabularnewline
90 & 102.62 & 101.704 & 102.049 & 0.996619 & 1.00901 \tabularnewline
91 & 102.76 & NA & NA & 0.993202 & NA \tabularnewline
92 & 102.73 & NA & NA & 0.994425 & NA \tabularnewline
93 & 102.26 & NA & NA & 0.994619 & NA \tabularnewline
94 & 101.72 & NA & NA & 0.996939 & NA \tabularnewline
95 & 101.48 & NA & NA & 1.00214 & NA \tabularnewline
96 & 100.93 & NA & NA & 1.00331 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284056&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]79.58[/C][C]NA[/C][C]NA[/C][C]1.00565[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]80.08[/C][C]NA[/C][C]NA[/C][C]1.00602[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]80.41[/C][C]NA[/C][C]NA[/C][C]1.0043[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]80.34[/C][C]NA[/C][C]NA[/C][C]1.00237[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]80.32[/C][C]NA[/C][C]NA[/C][C]1.00041[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]80.39[/C][C]NA[/C][C]NA[/C][C]0.996619[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]81.01[/C][C]82.4465[/C][C]83.0108[/C][C]0.993202[/C][C]0.982576[/C][/ROW]
[ROW][C]8[/C][C]81.54[/C][C]83.6299[/C][C]84.0988[/C][C]0.994425[/C][C]0.97501[/C][/ROW]
[ROW][C]9[/C][C]82.48[/C][C]84.7403[/C][C]85.1987[/C][C]0.994619[/C][C]0.973327[/C][/ROW]
[ROW][C]10[/C][C]84.68[/C][C]86.0492[/C][C]86.3133[/C][C]0.996939[/C][C]0.984089[/C][/ROW]
[ROW][C]11[/C][C]88.26[/C][C]87.633[/C][C]87.4458[/C][C]1.00214[/C][C]1.00715[/C][/ROW]
[ROW][C]12[/C][C]90.6[/C][C]88.8587[/C][C]88.5658[/C][C]1.00331[/C][C]1.0196[/C][/ROW]
[ROW][C]13[/C][C]92.46[/C][C]90.1574[/C][C]89.6504[/C][C]1.00565[/C][C]1.02554[/C][/ROW]
[ROW][C]14[/C][C]93.31[/C][C]91.2446[/C][C]90.6988[/C][C]1.00602[/C][C]1.02264[/C][/ROW]
[ROW][C]15[/C][C]93.58[/C][C]92.0852[/C][C]91.6913[/C][C]1.0043[/C][C]1.01623[/C][/ROW]
[ROW][C]16[/C][C]93.92[/C][C]92.7774[/C][C]92.5579[/C][C]1.00237[/C][C]1.01232[/C][/ROW]
[ROW][C]17[/C][C]93.92[/C][C]93.2234[/C][C]93.1854[/C][C]1.00041[/C][C]1.00747[/C][/ROW]
[ROW][C]18[/C][C]93.67[/C][C]93.22[/C][C]93.5363[/C][C]0.996619[/C][C]1.00483[/C][/ROW]
[ROW][C]19[/C][C]93.76[/C][C]93.0605[/C][C]93.6975[/C][C]0.993202[/C][C]1.00752[/C][/ROW]
[ROW][C]20[/C][C]93.95[/C][C]93.2315[/C][C]93.7542[/C][C]0.994425[/C][C]1.00771[/C][/ROW]
[ROW][C]21[/C][C]93.89[/C][C]93.2538[/C][C]93.7583[/C][C]0.994619[/C][C]1.00682[/C][/ROW]
[ROW][C]22[/C][C]94.07[/C][C]93.4431[/C][C]93.73[/C][C]0.996939[/C][C]1.00671[/C][/ROW]
[ROW][C]23[/C][C]93.93[/C][C]93.8768[/C][C]93.6762[/C][C]1.00214[/C][C]1.00057[/C][/ROW]
[ROW][C]24[/C][C]93.35[/C][C]93.9245[/C][C]93.615[/C][C]1.00331[/C][C]0.993883[/C][/ROW]
[ROW][C]25[/C][C]93.58[/C][C]94.0979[/C][C]93.5688[/C][C]1.00565[/C][C]0.994497[/C][/ROW]
[ROW][C]26[/C][C]93.55[/C][C]94.1231[/C][C]93.56[/C][C]1.00602[/C][C]0.993911[/C][/ROW]
[ROW][C]27[/C][C]93.44[/C][C]93.977[/C][C]93.575[/C][C]1.0043[/C][C]0.994285[/C][/ROW]
[ROW][C]28[/C][C]93.38[/C][C]93.8015[/C][C]93.5796[/C][C]1.00237[/C][C]0.995507[/C][/ROW]
[ROW][C]29[/C][C]93.17[/C][C]93.6374[/C][C]93.5992[/C][C]1.00041[/C][C]0.995009[/C][/ROW]
[ROW][C]30[/C][C]92.95[/C][C]93.3657[/C][C]93.6825[/C][C]0.996619[/C][C]0.995547[/C][/ROW]
[ROW][C]31[/C][C]93.37[/C][C]93.1309[/C][C]93.7683[/C][C]0.993202[/C][C]1.00257[/C][/ROW]
[ROW][C]32[/C][C]94.13[/C][C]93.2949[/C][C]93.8179[/C][C]0.994425[/C][C]1.00895[/C][/ROW]
[ROW][C]33[/C][C]94.07[/C][C]93.3591[/C][C]93.8642[/C][C]0.994619[/C][C]1.00762[/C][/ROW]
[ROW][C]34[/C][C]94[/C][C]93.5922[/C][C]93.8796[/C][C]0.996939[/C][C]1.00436[/C][/ROW]
[ROW][C]35[/C][C]94.47[/C][C]94.0726[/C][C]93.8717[/C][C]1.00214[/C][C]1.00422[/C][/ROW]
[ROW][C]36[/C][C]94.81[/C][C]94.162[/C][C]93.8517[/C][C]1.00331[/C][C]1.00688[/C][/ROW]
[ROW][C]37[/C][C]94.18[/C][C]94.3271[/C][C]93.7967[/C][C]1.00565[/C][C]0.998441[/C][/ROW]
[ROW][C]38[/C][C]94.14[/C][C]94.2656[/C][C]93.7017[/C][C]1.00602[/C][C]0.998668[/C][/ROW]
[ROW][C]39[/C][C]93.96[/C][C]93.9904[/C][C]93.5883[/C][C]1.0043[/C][C]0.999676[/C][/ROW]
[ROW][C]40[/C][C]93.23[/C][C]93.7063[/C][C]93.4846[/C][C]1.00237[/C][C]0.994917[/C][/ROW]
[ROW][C]41[/C][C]93.13[/C][C]93.4064[/C][C]93.3683[/C][C]1.00041[/C][C]0.997041[/C][/ROW]
[ROW][C]42[/C][C]92.51[/C][C]92.9214[/C][C]93.2367[/C][C]0.996619[/C][C]0.995573[/C][/ROW]
[ROW][C]43[/C][C]92.49[/C][C]92.5308[/C][C]93.1642[/C][C]0.993202[/C][C]0.999559[/C][/ROW]
[ROW][C]44[/C][C]92.73[/C][C]92.6448[/C][C]93.1642[/C][C]0.994425[/C][C]1.00092[/C][/ROW]
[ROW][C]45[/C][C]92.75[/C][C]92.6964[/C][C]93.1979[/C][C]0.994619[/C][C]1.00058[/C][/ROW]
[ROW][C]46[/C][C]92.83[/C][C]92.9957[/C][C]93.2812[/C][C]0.996939[/C][C]0.998218[/C][/ROW]
[ROW][C]47[/C][C]92.85[/C][C]93.6095[/C][C]93.4096[/C][C]1.00214[/C][C]0.991886[/C][/ROW]
[ROW][C]48[/C][C]93.27[/C][C]93.8961[/C][C]93.5867[/C][C]1.00331[/C][C]0.993332[/C][/ROW]
[ROW][C]49[/C][C]93.98[/C][C]94.3585[/C][C]93.8279[/C][C]1.00565[/C][C]0.995989[/C][/ROW]
[ROW][C]50[/C][C]94.34[/C][C]94.6676[/C][C]94.1012[/C][C]1.00602[/C][C]0.99654[/C][/ROW]
[ROW][C]51[/C][C]94.57[/C][C]94.8035[/C][C]94.3979[/C][C]1.0043[/C][C]0.997537[/C][/ROW]
[ROW][C]52[/C][C]94.62[/C][C]94.9283[/C][C]94.7037[/C][C]1.00237[/C][C]0.996752[/C][/ROW]
[ROW][C]53[/C][C]94.82[/C][C]95.055[/C][C]95.0162[/C][C]1.00041[/C][C]0.997527[/C][/ROW]
[ROW][C]54[/C][C]95.07[/C][C]95.0147[/C][C]95.3371[/C][C]0.996619[/C][C]1.00058[/C][/ROW]
[ROW][C]55[/C][C]95.72[/C][C]94.9811[/C][C]95.6312[/C][C]0.993202[/C][C]1.00778[/C][/ROW]
[ROW][C]56[/C][C]96.06[/C][C]95.3642[/C][C]95.8987[/C][C]0.994425[/C][C]1.0073[/C][/ROW]
[ROW][C]57[/C][C]96.54[/C][C]95.6517[/C][C]96.1692[/C][C]0.994619[/C][C]1.00929[/C][/ROW]
[ROW][C]58[/C][C]96.38[/C][C]96.1427[/C][C]96.4379[/C][C]0.996939[/C][C]1.00247[/C][/ROW]
[ROW][C]59[/C][C]96.8[/C][C]96.8899[/C][C]96.6829[/C][C]1.00214[/C][C]0.999073[/C][/ROW]
[ROW][C]60[/C][C]97.02[/C][C]97.2154[/C][C]96.895[/C][C]1.00331[/C][C]0.99799[/C][/ROW]
[ROW][C]61[/C][C]97.29[/C][C]97.608[/C][C]97.0592[/C][C]1.00565[/C][C]0.996742[/C][/ROW]
[ROW][C]62[/C][C]97.45[/C][C]97.7967[/C][C]97.2117[/C][C]1.00602[/C][C]0.996455[/C][/ROW]
[ROW][C]63[/C][C]97.95[/C][C]97.7883[/C][C]97.37[/C][C]1.0043[/C][C]1.00165[/C][/ROW]
[ROW][C]64[/C][C]97.69[/C][C]97.7659[/C][C]97.5346[/C][C]1.00237[/C][C]0.999224[/C][/ROW]
[ROW][C]65[/C][C]97.63[/C][C]97.747[/C][C]97.7071[/C][C]1.00041[/C][C]0.998803[/C][/ROW]
[ROW][C]66[/C][C]97.35[/C][C]97.532[/C][C]97.8629[/C][C]0.996619[/C][C]0.998134[/C][/ROW]
[ROW][C]67[/C][C]97.38[/C][C]97.3491[/C][C]98.0154[/C][C]0.993202[/C][C]1.00032[/C][/ROW]
[ROW][C]68[/C][C]98.06[/C][C]97.6439[/C][C]98.1912[/C][C]0.994425[/C][C]1.00426[/C][/ROW]
[ROW][C]69[/C][C]98.34[/C][C]97.8369[/C][C]98.3662[/C][C]0.994619[/C][C]1.00514[/C][/ROW]
[ROW][C]70[/C][C]98.53[/C][C]98.2326[/C][C]98.5342[/C][C]0.996939[/C][C]1.00303[/C][/ROW]
[ROW][C]71[/C][C]98.79[/C][C]98.9284[/C][C]98.7171[/C][C]1.00214[/C][C]0.998601[/C][/ROW]
[ROW][C]72[/C][C]98.77[/C][C]99.2266[/C][C]98.8996[/C][C]1.00331[/C][C]0.995399[/C][/ROW]
[ROW][C]73[/C][C]99.2[/C][C]99.6436[/C][C]99.0833[/C][C]1.00565[/C][C]0.995548[/C][/ROW]
[ROW][C]74[/C][C]99.76[/C][C]99.839[/C][C]99.2417[/C][C]1.00602[/C][C]0.999209[/C][/ROW]
[ROW][C]75[/C][C]99.84[/C][C]99.7965[/C][C]99.3696[/C][C]1.0043[/C][C]1.00044[/C][/ROW]
[ROW][C]76[/C][C]99.83[/C][C]99.7606[/C][C]99.5246[/C][C]1.00237[/C][C]1.0007[/C][/ROW]
[ROW][C]77[/C][C]99.88[/C][C]99.7557[/C][C]99.715[/C][C]1.00041[/C][C]1.00125[/C][/ROW]
[ROW][C]78[/C][C]99.48[/C][C]99.5697[/C][C]99.9075[/C][C]0.996619[/C][C]0.999099[/C][/ROW]
[ROW][C]79[/C][C]99.66[/C][C]99.4162[/C][C]100.097[/C][C]0.993202[/C][C]1.00245[/C][/ROW]
[ROW][C]80[/C][C]99.58[/C][C]99.7173[/C][C]100.276[/C][C]0.994425[/C][C]0.998624[/C][/ROW]
[ROW][C]81[/C][C]99.89[/C][C]99.8904[/C][C]100.431[/C][C]0.994619[/C][C]0.999996[/C][/ROW]
[ROW][C]82[/C][C]100.7[/C][C]100.309[/C][C]100.617[/C][C]0.996939[/C][C]1.0039[/C][/ROW]
[ROW][C]83[/C][C]101.19[/C][C]101.063[/C][C]100.847[/C][C]1.00214[/C][C]1.00126[/C][/ROW]
[ROW][C]84[/C][C]100.99[/C][C]101.428[/C][C]101.093[/C][C]1.00331[/C][C]0.995686[/C][/ROW]
[ROW][C]85[/C][C]101.52[/C][C]101.926[/C][C]101.353[/C][C]1.00565[/C][C]0.996012[/C][/ROW]
[ROW][C]86[/C][C]101.75[/C][C]102.225[/C][C]101.614[/C][C]1.00602[/C][C]0.99535[/C][/ROW]
[ROW][C]87[/C][C]101.56[/C][C]102.281[/C][C]101.844[/C][C]1.0043[/C][C]0.992948[/C][/ROW]
[ROW][C]88[/C][C]102.57[/C][C]102.227[/C][C]101.985[/C][C]1.00237[/C][C]1.00336[/C][/ROW]
[ROW][C]89[/C][C]102.66[/C][C]102.081[/C][C]102.04[/C][C]1.00041[/C][C]1.00567[/C][/ROW]
[ROW][C]90[/C][C]102.62[/C][C]101.704[/C][C]102.049[/C][C]0.996619[/C][C]1.00901[/C][/ROW]
[ROW][C]91[/C][C]102.76[/C][C]NA[/C][C]NA[/C][C]0.993202[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]102.73[/C][C]NA[/C][C]NA[/C][C]0.994425[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]102.26[/C][C]NA[/C][C]NA[/C][C]0.994619[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]101.72[/C][C]NA[/C][C]NA[/C][C]0.996939[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]101.48[/C][C]NA[/C][C]NA[/C][C]1.00214[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]100.93[/C][C]NA[/C][C]NA[/C][C]1.00331[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284056&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284056&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	79.58	NA	NA	1.00565	NA
2	80.08	NA	NA	1.00602	NA
3	80.41	NA	NA	1.0043	NA
4	80.34	NA	NA	1.00237	NA
5	80.32	NA	NA	1.00041	NA
6	80.39	NA	NA	0.996619	NA
7	81.01	82.4465	83.0108	0.993202	0.982576
8	81.54	83.6299	84.0988	0.994425	0.97501
9	82.48	84.7403	85.1987	0.994619	0.973327
10	84.68	86.0492	86.3133	0.996939	0.984089
11	88.26	87.633	87.4458	1.00214	1.00715
12	90.6	88.8587	88.5658	1.00331	1.0196
13	92.46	90.1574	89.6504	1.00565	1.02554
14	93.31	91.2446	90.6988	1.00602	1.02264
15	93.58	92.0852	91.6913	1.0043	1.01623
16	93.92	92.7774	92.5579	1.00237	1.01232
17	93.92	93.2234	93.1854	1.00041	1.00747
18	93.67	93.22	93.5363	0.996619	1.00483
19	93.76	93.0605	93.6975	0.993202	1.00752
20	93.95	93.2315	93.7542	0.994425	1.00771
21	93.89	93.2538	93.7583	0.994619	1.00682
22	94.07	93.4431	93.73	0.996939	1.00671
23	93.93	93.8768	93.6762	1.00214	1.00057
24	93.35	93.9245	93.615	1.00331	0.993883
25	93.58	94.0979	93.5688	1.00565	0.994497
26	93.55	94.1231	93.56	1.00602	0.993911
27	93.44	93.977	93.575	1.0043	0.994285
28	93.38	93.8015	93.5796	1.00237	0.995507
29	93.17	93.6374	93.5992	1.00041	0.995009
30	92.95	93.3657	93.6825	0.996619	0.995547
31	93.37	93.1309	93.7683	0.993202	1.00257
32	94.13	93.2949	93.8179	0.994425	1.00895
33	94.07	93.3591	93.8642	0.994619	1.00762
34	94	93.5922	93.8796	0.996939	1.00436
35	94.47	94.0726	93.8717	1.00214	1.00422
36	94.81	94.162	93.8517	1.00331	1.00688
37	94.18	94.3271	93.7967	1.00565	0.998441
38	94.14	94.2656	93.7017	1.00602	0.998668
39	93.96	93.9904	93.5883	1.0043	0.999676
40	93.23	93.7063	93.4846	1.00237	0.994917
41	93.13	93.4064	93.3683	1.00041	0.997041
42	92.51	92.9214	93.2367	0.996619	0.995573
43	92.49	92.5308	93.1642	0.993202	0.999559
44	92.73	92.6448	93.1642	0.994425	1.00092
45	92.75	92.6964	93.1979	0.994619	1.00058
46	92.83	92.9957	93.2812	0.996939	0.998218
47	92.85	93.6095	93.4096	1.00214	0.991886
48	93.27	93.8961	93.5867	1.00331	0.993332
49	93.98	94.3585	93.8279	1.00565	0.995989
50	94.34	94.6676	94.1012	1.00602	0.99654
51	94.57	94.8035	94.3979	1.0043	0.997537
52	94.62	94.9283	94.7037	1.00237	0.996752
53	94.82	95.055	95.0162	1.00041	0.997527
54	95.07	95.0147	95.3371	0.996619	1.00058
55	95.72	94.9811	95.6312	0.993202	1.00778
56	96.06	95.3642	95.8987	0.994425	1.0073
57	96.54	95.6517	96.1692	0.994619	1.00929
58	96.38	96.1427	96.4379	0.996939	1.00247
59	96.8	96.8899	96.6829	1.00214	0.999073
60	97.02	97.2154	96.895	1.00331	0.99799
61	97.29	97.608	97.0592	1.00565	0.996742
62	97.45	97.7967	97.2117	1.00602	0.996455
63	97.95	97.7883	97.37	1.0043	1.00165
64	97.69	97.7659	97.5346	1.00237	0.999224
65	97.63	97.747	97.7071	1.00041	0.998803
66	97.35	97.532	97.8629	0.996619	0.998134
67	97.38	97.3491	98.0154	0.993202	1.00032
68	98.06	97.6439	98.1912	0.994425	1.00426
69	98.34	97.8369	98.3662	0.994619	1.00514
70	98.53	98.2326	98.5342	0.996939	1.00303
71	98.79	98.9284	98.7171	1.00214	0.998601
72	98.77	99.2266	98.8996	1.00331	0.995399
73	99.2	99.6436	99.0833	1.00565	0.995548
74	99.76	99.839	99.2417	1.00602	0.999209
75	99.84	99.7965	99.3696	1.0043	1.00044
76	99.83	99.7606	99.5246	1.00237	1.0007
77	99.88	99.7557	99.715	1.00041	1.00125
78	99.48	99.5697	99.9075	0.996619	0.999099
79	99.66	99.4162	100.097	0.993202	1.00245
80	99.58	99.7173	100.276	0.994425	0.998624
81	99.89	99.8904	100.431	0.994619	0.999996
82	100.7	100.309	100.617	0.996939	1.0039
83	101.19	101.063	100.847	1.00214	1.00126
84	100.99	101.428	101.093	1.00331	0.995686
85	101.52	101.926	101.353	1.00565	0.996012
86	101.75	102.225	101.614	1.00602	0.99535
87	101.56	102.281	101.844	1.0043	0.992948
88	102.57	102.227	101.985	1.00237	1.00336
89	102.66	102.081	102.04	1.00041	1.00567
90	102.62	101.704	102.049	0.996619	1.00901
91	102.76	NA	NA	0.993202	NA
92	102.73	NA	NA	0.994425	NA
93	102.26	NA	NA	0.994619	NA
94	101.72	NA	NA	0.996939	NA
95	101.48	NA	NA	1.00214	NA
96	100.93	NA	NA	1.00331	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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