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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 23 Dec 2016 10:43:33 +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/Dec/23/t14824862747r0z93og6x5kpdf.htm/, Retrieved Tue, 07 May 2024 13:17:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302823, Retrieved Tue, 07 May 2024 13:17:42 +0000

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-       [Classical Decomposition] [classical decompo...] [2016-12-23 09:43:33] [bd7223969ac5b08f41438741a34686d6] [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	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302823&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

2 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302823&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302823&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	Big Analytics Cloud Computing Center

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	99	NA	NA	-0.356709	NA
2	102	NA	NA	0.393291	NA
3	100	NA	NA	-0.9765	NA
4	98	NA	NA	0.518291	NA
5	98	NA	NA	-0.356709	NA
6	99	NA	NA	0.283172	NA
7	100	98.9922	99.9583	-0.966084	1.00775
8	99	99.8672	99.9583	-0.0910838	-0.86725
9	100	99.9245	99.875	0.0495412	0.0754588
10	99	100.596	99.9167	0.67975	-1.59642
11	101	100.836	100.167	0.669333	0.164
12	104	100.487	100.333	0.153708	3.51296
13	100	99.935	100.292	-0.356709	0.0650422
14	101	100.685	100.292	0.393291	0.315042
15	99	99.3152	100.292	-0.9765	-0.315166
16	100	101.018	100.5	0.518291	-1.01829
17	102	100.352	100.708	-0.356709	1.64838
18	99	100.825	100.542	0.283172	-1.82484
19	99	99.4506	100.417	-0.966084	-0.450583
20	100	100.326	100.417	-0.0910838	-0.325583
21	99	100.466	100.417	0.0495412	-1.46621
22	105	101.096	100.417	0.67975	3.90358
23	100	101.003	100.333	0.669333	-1.00267
24	101	100.445	100.292	0.153708	0.554625
25	100	100.018	100.375	-0.356709	-0.0182912
26	101	100.852	100.458	0.393291	0.148375
27	99	99.6068	100.583	-0.9765	-0.606833
28	100	100.977	100.458	0.518291	-0.976625
29	100	99.8516	100.208	-0.356709	0.148375
30	100	100.45	100.167	0.283172	-0.449839
31	100	99.2422	100.208	-0.966084	0.75775
32	101	100.159	100.25	-0.0910838	0.841084
33	101	100.341	100.292	0.0495412	0.658792
34	100	101.013	100.333	0.67975	-1.01308
35	99	101.003	100.333	0.669333	-2.00267
36	101	100.529	100.375	0.153708	0.471292
37	101	99.9766	100.333	-0.356709	1.02338
38	101	100.56	100.167	0.393291	0.440042
39	100	99.0652	100.042	-0.9765	0.934834
40	100	100.56	100.042	0.518291	-0.559958
41	100	99.7683	100.125	-0.356709	0.231709
42	101	100.408	100.125	0.283172	0.591828
43	98	99.0339	100	-0.966084	-1.03392
44	99	99.7839	99.875	-0.0910838	-0.783916
45	100	99.8412	99.7917	0.0495412	0.158792
46	101	100.471	99.7917	0.67975	0.528584
47	100	100.419	99.75	0.669333	-0.419333
48	100	99.7787	99.625	0.153708	0.221292
49	99	99.2683	99.625	-0.356709	-0.268291
50	100	100.227	99.8333	0.393291	-0.226625
51	99	99.2318	100.208	-0.9765	-0.231833
52	101	100.893	100.375	0.518291	0.106709
53	98	100.018	100.375	-0.356709	-2.01829
54	100	100.7	100.417	0.283172	-0.699839
55	99	99.4506	100.417	-0.966084	-0.450583
56	103	100.326	100.417	-0.0910838	2.67442
57	105	100.466	100.417	0.0495412	4.53379
58	100	101.263	100.583	0.67975	-1.26308
59	101	101.461	100.792	0.669333	-0.461
60	100	101.07	100.917	0.153708	-1.07037
61	99	100.685	101.042	-0.356709	-1.68496
62	100	101.352	100.958	0.393291	-1.35162
63	99	99.6068	100.583	-0.9765	-0.606833
64	105	100.935	100.417	0.518291	4.06504
65	99	100.06	100.417	-0.356709	-1.05996
66	102	100.658	100.375	0.283172	1.34183
67	100	99.4922	100.458	-0.966084	0.50775
68	100	100.409	100.5	-0.0910838	-0.408916
69	99	100.55	100.5	0.0495412	-1.54954
70	102	101.013	100.333	0.67975	0.986917
71	99	100.878	100.208	0.669333	-1.87767
72	101	100.32	100.167	0.153708	0.679625
73	100	99.6433	100	-0.356709	0.356709
74	100	100.268	99.875	0.393291	-0.268291
75	99	98.8568	99.8333	-0.9765	0.143167
76	101	100.185	99.6667	0.518291	0.815042
77	100	99.3933	99.75	-0.356709	0.606709
78	100	100.158	99.875	0.283172	-0.158172
79	98	98.7839	99.75	-0.966084	-0.783916
80	99	99.7006	99.7917	-0.0910838	-0.700583
81	99	99.9662	99.9167	0.0495412	-0.966208
82	98	100.638	99.9583	0.67975	-2.63808
83	105	100.628	99.9583	0.669333	4.37233
84	98	100.237	100.083	0.153708	-2.23704
85	100	99.8933	100.25	-0.356709	0.106709
86	101	100.768	100.375	0.393291	0.231709
87	101	99.4402	100.417	-0.9765	1.55983
88	100	101.102	100.583	0.518291	-1.10162
89	101	100.268	100.625	-0.356709	0.731709
90	102	100.783	100.5	0.283172	1.21683
91	100	99.5339	100.5	-0.966084	0.466084
92	100	100.409	100.5	-0.0910838	-0.408916
93	99	100.425	100.375	0.0495412	-1.42454
94	102	100.888	100.208	0.67975	1.11192
95	102	100.753	100.083	0.669333	1.24733
96	98	100.112	99.9583	0.153708	-2.11204
97	100	99.56	99.9167	-0.356709	0.440042
98	101	100.268	99.875	0.393291	0.731709
99	98	98.8568	99.8333	-0.9765	-0.856833
100	99	100.31	99.7917	0.518291	-1.30996
101	99	99.2683	99.625	-0.356709	-0.268291
102	101	NA	NA	0.283172	NA
103	100	NA	NA	-0.966084	NA
104	99	NA	NA	-0.0910838	NA
105	99	NA	NA	0.0495412	NA
106	101	NA	NA	0.67975	NA
107	99	NA	NA	0.669333	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 99 & NA & NA & -0.356709 & NA \tabularnewline
2 & 102 & NA & NA & 0.393291 & NA \tabularnewline
3 & 100 & NA & NA & -0.9765 & NA \tabularnewline
4 & 98 & NA & NA & 0.518291 & NA \tabularnewline
5 & 98 & NA & NA & -0.356709 & NA \tabularnewline
6 & 99 & NA & NA & 0.283172 & NA \tabularnewline
7 & 100 & 98.9922 & 99.9583 & -0.966084 & 1.00775 \tabularnewline
8 & 99 & 99.8672 & 99.9583 & -0.0910838 & -0.86725 \tabularnewline
9 & 100 & 99.9245 & 99.875 & 0.0495412 & 0.0754588 \tabularnewline
10 & 99 & 100.596 & 99.9167 & 0.67975 & -1.59642 \tabularnewline
11 & 101 & 100.836 & 100.167 & 0.669333 & 0.164 \tabularnewline
12 & 104 & 100.487 & 100.333 & 0.153708 & 3.51296 \tabularnewline
13 & 100 & 99.935 & 100.292 & -0.356709 & 0.0650422 \tabularnewline
14 & 101 & 100.685 & 100.292 & 0.393291 & 0.315042 \tabularnewline
15 & 99 & 99.3152 & 100.292 & -0.9765 & -0.315166 \tabularnewline
16 & 100 & 101.018 & 100.5 & 0.518291 & -1.01829 \tabularnewline
17 & 102 & 100.352 & 100.708 & -0.356709 & 1.64838 \tabularnewline
18 & 99 & 100.825 & 100.542 & 0.283172 & -1.82484 \tabularnewline
19 & 99 & 99.4506 & 100.417 & -0.966084 & -0.450583 \tabularnewline
20 & 100 & 100.326 & 100.417 & -0.0910838 & -0.325583 \tabularnewline
21 & 99 & 100.466 & 100.417 & 0.0495412 & -1.46621 \tabularnewline
22 & 105 & 101.096 & 100.417 & 0.67975 & 3.90358 \tabularnewline
23 & 100 & 101.003 & 100.333 & 0.669333 & -1.00267 \tabularnewline
24 & 101 & 100.445 & 100.292 & 0.153708 & 0.554625 \tabularnewline
25 & 100 & 100.018 & 100.375 & -0.356709 & -0.0182912 \tabularnewline
26 & 101 & 100.852 & 100.458 & 0.393291 & 0.148375 \tabularnewline
27 & 99 & 99.6068 & 100.583 & -0.9765 & -0.606833 \tabularnewline
28 & 100 & 100.977 & 100.458 & 0.518291 & -0.976625 \tabularnewline
29 & 100 & 99.8516 & 100.208 & -0.356709 & 0.148375 \tabularnewline
30 & 100 & 100.45 & 100.167 & 0.283172 & -0.449839 \tabularnewline
31 & 100 & 99.2422 & 100.208 & -0.966084 & 0.75775 \tabularnewline
32 & 101 & 100.159 & 100.25 & -0.0910838 & 0.841084 \tabularnewline
33 & 101 & 100.341 & 100.292 & 0.0495412 & 0.658792 \tabularnewline
34 & 100 & 101.013 & 100.333 & 0.67975 & -1.01308 \tabularnewline
35 & 99 & 101.003 & 100.333 & 0.669333 & -2.00267 \tabularnewline
36 & 101 & 100.529 & 100.375 & 0.153708 & 0.471292 \tabularnewline
37 & 101 & 99.9766 & 100.333 & -0.356709 & 1.02338 \tabularnewline
38 & 101 & 100.56 & 100.167 & 0.393291 & 0.440042 \tabularnewline
39 & 100 & 99.0652 & 100.042 & -0.9765 & 0.934834 \tabularnewline
40 & 100 & 100.56 & 100.042 & 0.518291 & -0.559958 \tabularnewline
41 & 100 & 99.7683 & 100.125 & -0.356709 & 0.231709 \tabularnewline
42 & 101 & 100.408 & 100.125 & 0.283172 & 0.591828 \tabularnewline
43 & 98 & 99.0339 & 100 & -0.966084 & -1.03392 \tabularnewline
44 & 99 & 99.7839 & 99.875 & -0.0910838 & -0.783916 \tabularnewline
45 & 100 & 99.8412 & 99.7917 & 0.0495412 & 0.158792 \tabularnewline
46 & 101 & 100.471 & 99.7917 & 0.67975 & 0.528584 \tabularnewline
47 & 100 & 100.419 & 99.75 & 0.669333 & -0.419333 \tabularnewline
48 & 100 & 99.7787 & 99.625 & 0.153708 & 0.221292 \tabularnewline
49 & 99 & 99.2683 & 99.625 & -0.356709 & -0.268291 \tabularnewline
50 & 100 & 100.227 & 99.8333 & 0.393291 & -0.226625 \tabularnewline
51 & 99 & 99.2318 & 100.208 & -0.9765 & -0.231833 \tabularnewline
52 & 101 & 100.893 & 100.375 & 0.518291 & 0.106709 \tabularnewline
53 & 98 & 100.018 & 100.375 & -0.356709 & -2.01829 \tabularnewline
54 & 100 & 100.7 & 100.417 & 0.283172 & -0.699839 \tabularnewline
55 & 99 & 99.4506 & 100.417 & -0.966084 & -0.450583 \tabularnewline
56 & 103 & 100.326 & 100.417 & -0.0910838 & 2.67442 \tabularnewline
57 & 105 & 100.466 & 100.417 & 0.0495412 & 4.53379 \tabularnewline
58 & 100 & 101.263 & 100.583 & 0.67975 & -1.26308 \tabularnewline
59 & 101 & 101.461 & 100.792 & 0.669333 & -0.461 \tabularnewline
60 & 100 & 101.07 & 100.917 & 0.153708 & -1.07037 \tabularnewline
61 & 99 & 100.685 & 101.042 & -0.356709 & -1.68496 \tabularnewline
62 & 100 & 101.352 & 100.958 & 0.393291 & -1.35162 \tabularnewline
63 & 99 & 99.6068 & 100.583 & -0.9765 & -0.606833 \tabularnewline
64 & 105 & 100.935 & 100.417 & 0.518291 & 4.06504 \tabularnewline
65 & 99 & 100.06 & 100.417 & -0.356709 & -1.05996 \tabularnewline
66 & 102 & 100.658 & 100.375 & 0.283172 & 1.34183 \tabularnewline
67 & 100 & 99.4922 & 100.458 & -0.966084 & 0.50775 \tabularnewline
68 & 100 & 100.409 & 100.5 & -0.0910838 & -0.408916 \tabularnewline
69 & 99 & 100.55 & 100.5 & 0.0495412 & -1.54954 \tabularnewline
70 & 102 & 101.013 & 100.333 & 0.67975 & 0.986917 \tabularnewline
71 & 99 & 100.878 & 100.208 & 0.669333 & -1.87767 \tabularnewline
72 & 101 & 100.32 & 100.167 & 0.153708 & 0.679625 \tabularnewline
73 & 100 & 99.6433 & 100 & -0.356709 & 0.356709 \tabularnewline
74 & 100 & 100.268 & 99.875 & 0.393291 & -0.268291 \tabularnewline
75 & 99 & 98.8568 & 99.8333 & -0.9765 & 0.143167 \tabularnewline
76 & 101 & 100.185 & 99.6667 & 0.518291 & 0.815042 \tabularnewline
77 & 100 & 99.3933 & 99.75 & -0.356709 & 0.606709 \tabularnewline
78 & 100 & 100.158 & 99.875 & 0.283172 & -0.158172 \tabularnewline
79 & 98 & 98.7839 & 99.75 & -0.966084 & -0.783916 \tabularnewline
80 & 99 & 99.7006 & 99.7917 & -0.0910838 & -0.700583 \tabularnewline
81 & 99 & 99.9662 & 99.9167 & 0.0495412 & -0.966208 \tabularnewline
82 & 98 & 100.638 & 99.9583 & 0.67975 & -2.63808 \tabularnewline
83 & 105 & 100.628 & 99.9583 & 0.669333 & 4.37233 \tabularnewline
84 & 98 & 100.237 & 100.083 & 0.153708 & -2.23704 \tabularnewline
85 & 100 & 99.8933 & 100.25 & -0.356709 & 0.106709 \tabularnewline
86 & 101 & 100.768 & 100.375 & 0.393291 & 0.231709 \tabularnewline
87 & 101 & 99.4402 & 100.417 & -0.9765 & 1.55983 \tabularnewline
88 & 100 & 101.102 & 100.583 & 0.518291 & -1.10162 \tabularnewline
89 & 101 & 100.268 & 100.625 & -0.356709 & 0.731709 \tabularnewline
90 & 102 & 100.783 & 100.5 & 0.283172 & 1.21683 \tabularnewline
91 & 100 & 99.5339 & 100.5 & -0.966084 & 0.466084 \tabularnewline
92 & 100 & 100.409 & 100.5 & -0.0910838 & -0.408916 \tabularnewline
93 & 99 & 100.425 & 100.375 & 0.0495412 & -1.42454 \tabularnewline
94 & 102 & 100.888 & 100.208 & 0.67975 & 1.11192 \tabularnewline
95 & 102 & 100.753 & 100.083 & 0.669333 & 1.24733 \tabularnewline
96 & 98 & 100.112 & 99.9583 & 0.153708 & -2.11204 \tabularnewline
97 & 100 & 99.56 & 99.9167 & -0.356709 & 0.440042 \tabularnewline
98 & 101 & 100.268 & 99.875 & 0.393291 & 0.731709 \tabularnewline
99 & 98 & 98.8568 & 99.8333 & -0.9765 & -0.856833 \tabularnewline
100 & 99 & 100.31 & 99.7917 & 0.518291 & -1.30996 \tabularnewline
101 & 99 & 99.2683 & 99.625 & -0.356709 & -0.268291 \tabularnewline
102 & 101 & NA & NA & 0.283172 & NA \tabularnewline
103 & 100 & NA & NA & -0.966084 & NA \tabularnewline
104 & 99 & NA & NA & -0.0910838 & NA \tabularnewline
105 & 99 & NA & NA & 0.0495412 & NA \tabularnewline
106 & 101 & NA & NA & 0.67975 & NA \tabularnewline
107 & 99 & NA & NA & 0.669333 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302823&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]99[/C][C]NA[/C][C]NA[/C][C]-0.356709[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]102[/C][C]NA[/C][C]NA[/C][C]0.393291[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]100[/C][C]NA[/C][C]NA[/C][C]-0.9765[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]98[/C][C]NA[/C][C]NA[/C][C]0.518291[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]98[/C][C]NA[/C][C]NA[/C][C]-0.356709[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]99[/C][C]NA[/C][C]NA[/C][C]0.283172[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]100[/C][C]98.9922[/C][C]99.9583[/C][C]-0.966084[/C][C]1.00775[/C][/ROW]
[ROW][C]8[/C][C]99[/C][C]99.8672[/C][C]99.9583[/C][C]-0.0910838[/C][C]-0.86725[/C][/ROW]
[ROW][C]9[/C][C]100[/C][C]99.9245[/C][C]99.875[/C][C]0.0495412[/C][C]0.0754588[/C][/ROW]
[ROW][C]10[/C][C]99[/C][C]100.596[/C][C]99.9167[/C][C]0.67975[/C][C]-1.59642[/C][/ROW]
[ROW][C]11[/C][C]101[/C][C]100.836[/C][C]100.167[/C][C]0.669333[/C][C]0.164[/C][/ROW]
[ROW][C]12[/C][C]104[/C][C]100.487[/C][C]100.333[/C][C]0.153708[/C][C]3.51296[/C][/ROW]
[ROW][C]13[/C][C]100[/C][C]99.935[/C][C]100.292[/C][C]-0.356709[/C][C]0.0650422[/C][/ROW]
[ROW][C]14[/C][C]101[/C][C]100.685[/C][C]100.292[/C][C]0.393291[/C][C]0.315042[/C][/ROW]
[ROW][C]15[/C][C]99[/C][C]99.3152[/C][C]100.292[/C][C]-0.9765[/C][C]-0.315166[/C][/ROW]
[ROW][C]16[/C][C]100[/C][C]101.018[/C][C]100.5[/C][C]0.518291[/C][C]-1.01829[/C][/ROW]
[ROW][C]17[/C][C]102[/C][C]100.352[/C][C]100.708[/C][C]-0.356709[/C][C]1.64838[/C][/ROW]
[ROW][C]18[/C][C]99[/C][C]100.825[/C][C]100.542[/C][C]0.283172[/C][C]-1.82484[/C][/ROW]
[ROW][C]19[/C][C]99[/C][C]99.4506[/C][C]100.417[/C][C]-0.966084[/C][C]-0.450583[/C][/ROW]
[ROW][C]20[/C][C]100[/C][C]100.326[/C][C]100.417[/C][C]-0.0910838[/C][C]-0.325583[/C][/ROW]
[ROW][C]21[/C][C]99[/C][C]100.466[/C][C]100.417[/C][C]0.0495412[/C][C]-1.46621[/C][/ROW]
[ROW][C]22[/C][C]105[/C][C]101.096[/C][C]100.417[/C][C]0.67975[/C][C]3.90358[/C][/ROW]
[ROW][C]23[/C][C]100[/C][C]101.003[/C][C]100.333[/C][C]0.669333[/C][C]-1.00267[/C][/ROW]
[ROW][C]24[/C][C]101[/C][C]100.445[/C][C]100.292[/C][C]0.153708[/C][C]0.554625[/C][/ROW]
[ROW][C]25[/C][C]100[/C][C]100.018[/C][C]100.375[/C][C]-0.356709[/C][C]-0.0182912[/C][/ROW]
[ROW][C]26[/C][C]101[/C][C]100.852[/C][C]100.458[/C][C]0.393291[/C][C]0.148375[/C][/ROW]
[ROW][C]27[/C][C]99[/C][C]99.6068[/C][C]100.583[/C][C]-0.9765[/C][C]-0.606833[/C][/ROW]
[ROW][C]28[/C][C]100[/C][C]100.977[/C][C]100.458[/C][C]0.518291[/C][C]-0.976625[/C][/ROW]
[ROW][C]29[/C][C]100[/C][C]99.8516[/C][C]100.208[/C][C]-0.356709[/C][C]0.148375[/C][/ROW]
[ROW][C]30[/C][C]100[/C][C]100.45[/C][C]100.167[/C][C]0.283172[/C][C]-0.449839[/C][/ROW]
[ROW][C]31[/C][C]100[/C][C]99.2422[/C][C]100.208[/C][C]-0.966084[/C][C]0.75775[/C][/ROW]
[ROW][C]32[/C][C]101[/C][C]100.159[/C][C]100.25[/C][C]-0.0910838[/C][C]0.841084[/C][/ROW]
[ROW][C]33[/C][C]101[/C][C]100.341[/C][C]100.292[/C][C]0.0495412[/C][C]0.658792[/C][/ROW]
[ROW][C]34[/C][C]100[/C][C]101.013[/C][C]100.333[/C][C]0.67975[/C][C]-1.01308[/C][/ROW]
[ROW][C]35[/C][C]99[/C][C]101.003[/C][C]100.333[/C][C]0.669333[/C][C]-2.00267[/C][/ROW]
[ROW][C]36[/C][C]101[/C][C]100.529[/C][C]100.375[/C][C]0.153708[/C][C]0.471292[/C][/ROW]
[ROW][C]37[/C][C]101[/C][C]99.9766[/C][C]100.333[/C][C]-0.356709[/C][C]1.02338[/C][/ROW]
[ROW][C]38[/C][C]101[/C][C]100.56[/C][C]100.167[/C][C]0.393291[/C][C]0.440042[/C][/ROW]
[ROW][C]39[/C][C]100[/C][C]99.0652[/C][C]100.042[/C][C]-0.9765[/C][C]0.934834[/C][/ROW]
[ROW][C]40[/C][C]100[/C][C]100.56[/C][C]100.042[/C][C]0.518291[/C][C]-0.559958[/C][/ROW]
[ROW][C]41[/C][C]100[/C][C]99.7683[/C][C]100.125[/C][C]-0.356709[/C][C]0.231709[/C][/ROW]
[ROW][C]42[/C][C]101[/C][C]100.408[/C][C]100.125[/C][C]0.283172[/C][C]0.591828[/C][/ROW]
[ROW][C]43[/C][C]98[/C][C]99.0339[/C][C]100[/C][C]-0.966084[/C][C]-1.03392[/C][/ROW]
[ROW][C]44[/C][C]99[/C][C]99.7839[/C][C]99.875[/C][C]-0.0910838[/C][C]-0.783916[/C][/ROW]
[ROW][C]45[/C][C]100[/C][C]99.8412[/C][C]99.7917[/C][C]0.0495412[/C][C]0.158792[/C][/ROW]
[ROW][C]46[/C][C]101[/C][C]100.471[/C][C]99.7917[/C][C]0.67975[/C][C]0.528584[/C][/ROW]
[ROW][C]47[/C][C]100[/C][C]100.419[/C][C]99.75[/C][C]0.669333[/C][C]-0.419333[/C][/ROW]
[ROW][C]48[/C][C]100[/C][C]99.7787[/C][C]99.625[/C][C]0.153708[/C][C]0.221292[/C][/ROW]
[ROW][C]49[/C][C]99[/C][C]99.2683[/C][C]99.625[/C][C]-0.356709[/C][C]-0.268291[/C][/ROW]
[ROW][C]50[/C][C]100[/C][C]100.227[/C][C]99.8333[/C][C]0.393291[/C][C]-0.226625[/C][/ROW]
[ROW][C]51[/C][C]99[/C][C]99.2318[/C][C]100.208[/C][C]-0.9765[/C][C]-0.231833[/C][/ROW]
[ROW][C]52[/C][C]101[/C][C]100.893[/C][C]100.375[/C][C]0.518291[/C][C]0.106709[/C][/ROW]
[ROW][C]53[/C][C]98[/C][C]100.018[/C][C]100.375[/C][C]-0.356709[/C][C]-2.01829[/C][/ROW]
[ROW][C]54[/C][C]100[/C][C]100.7[/C][C]100.417[/C][C]0.283172[/C][C]-0.699839[/C][/ROW]
[ROW][C]55[/C][C]99[/C][C]99.4506[/C][C]100.417[/C][C]-0.966084[/C][C]-0.450583[/C][/ROW]
[ROW][C]56[/C][C]103[/C][C]100.326[/C][C]100.417[/C][C]-0.0910838[/C][C]2.67442[/C][/ROW]
[ROW][C]57[/C][C]105[/C][C]100.466[/C][C]100.417[/C][C]0.0495412[/C][C]4.53379[/C][/ROW]
[ROW][C]58[/C][C]100[/C][C]101.263[/C][C]100.583[/C][C]0.67975[/C][C]-1.26308[/C][/ROW]
[ROW][C]59[/C][C]101[/C][C]101.461[/C][C]100.792[/C][C]0.669333[/C][C]-0.461[/C][/ROW]
[ROW][C]60[/C][C]100[/C][C]101.07[/C][C]100.917[/C][C]0.153708[/C][C]-1.07037[/C][/ROW]
[ROW][C]61[/C][C]99[/C][C]100.685[/C][C]101.042[/C][C]-0.356709[/C][C]-1.68496[/C][/ROW]
[ROW][C]62[/C][C]100[/C][C]101.352[/C][C]100.958[/C][C]0.393291[/C][C]-1.35162[/C][/ROW]
[ROW][C]63[/C][C]99[/C][C]99.6068[/C][C]100.583[/C][C]-0.9765[/C][C]-0.606833[/C][/ROW]
[ROW][C]64[/C][C]105[/C][C]100.935[/C][C]100.417[/C][C]0.518291[/C][C]4.06504[/C][/ROW]
[ROW][C]65[/C][C]99[/C][C]100.06[/C][C]100.417[/C][C]-0.356709[/C][C]-1.05996[/C][/ROW]
[ROW][C]66[/C][C]102[/C][C]100.658[/C][C]100.375[/C][C]0.283172[/C][C]1.34183[/C][/ROW]
[ROW][C]67[/C][C]100[/C][C]99.4922[/C][C]100.458[/C][C]-0.966084[/C][C]0.50775[/C][/ROW]
[ROW][C]68[/C][C]100[/C][C]100.409[/C][C]100.5[/C][C]-0.0910838[/C][C]-0.408916[/C][/ROW]
[ROW][C]69[/C][C]99[/C][C]100.55[/C][C]100.5[/C][C]0.0495412[/C][C]-1.54954[/C][/ROW]
[ROW][C]70[/C][C]102[/C][C]101.013[/C][C]100.333[/C][C]0.67975[/C][C]0.986917[/C][/ROW]
[ROW][C]71[/C][C]99[/C][C]100.878[/C][C]100.208[/C][C]0.669333[/C][C]-1.87767[/C][/ROW]
[ROW][C]72[/C][C]101[/C][C]100.32[/C][C]100.167[/C][C]0.153708[/C][C]0.679625[/C][/ROW]
[ROW][C]73[/C][C]100[/C][C]99.6433[/C][C]100[/C][C]-0.356709[/C][C]0.356709[/C][/ROW]
[ROW][C]74[/C][C]100[/C][C]100.268[/C][C]99.875[/C][C]0.393291[/C][C]-0.268291[/C][/ROW]
[ROW][C]75[/C][C]99[/C][C]98.8568[/C][C]99.8333[/C][C]-0.9765[/C][C]0.143167[/C][/ROW]
[ROW][C]76[/C][C]101[/C][C]100.185[/C][C]99.6667[/C][C]0.518291[/C][C]0.815042[/C][/ROW]
[ROW][C]77[/C][C]100[/C][C]99.3933[/C][C]99.75[/C][C]-0.356709[/C][C]0.606709[/C][/ROW]
[ROW][C]78[/C][C]100[/C][C]100.158[/C][C]99.875[/C][C]0.283172[/C][C]-0.158172[/C][/ROW]
[ROW][C]79[/C][C]98[/C][C]98.7839[/C][C]99.75[/C][C]-0.966084[/C][C]-0.783916[/C][/ROW]
[ROW][C]80[/C][C]99[/C][C]99.7006[/C][C]99.7917[/C][C]-0.0910838[/C][C]-0.700583[/C][/ROW]
[ROW][C]81[/C][C]99[/C][C]99.9662[/C][C]99.9167[/C][C]0.0495412[/C][C]-0.966208[/C][/ROW]
[ROW][C]82[/C][C]98[/C][C]100.638[/C][C]99.9583[/C][C]0.67975[/C][C]-2.63808[/C][/ROW]
[ROW][C]83[/C][C]105[/C][C]100.628[/C][C]99.9583[/C][C]0.669333[/C][C]4.37233[/C][/ROW]
[ROW][C]84[/C][C]98[/C][C]100.237[/C][C]100.083[/C][C]0.153708[/C][C]-2.23704[/C][/ROW]
[ROW][C]85[/C][C]100[/C][C]99.8933[/C][C]100.25[/C][C]-0.356709[/C][C]0.106709[/C][/ROW]
[ROW][C]86[/C][C]101[/C][C]100.768[/C][C]100.375[/C][C]0.393291[/C][C]0.231709[/C][/ROW]
[ROW][C]87[/C][C]101[/C][C]99.4402[/C][C]100.417[/C][C]-0.9765[/C][C]1.55983[/C][/ROW]
[ROW][C]88[/C][C]100[/C][C]101.102[/C][C]100.583[/C][C]0.518291[/C][C]-1.10162[/C][/ROW]
[ROW][C]89[/C][C]101[/C][C]100.268[/C][C]100.625[/C][C]-0.356709[/C][C]0.731709[/C][/ROW]
[ROW][C]90[/C][C]102[/C][C]100.783[/C][C]100.5[/C][C]0.283172[/C][C]1.21683[/C][/ROW]
[ROW][C]91[/C][C]100[/C][C]99.5339[/C][C]100.5[/C][C]-0.966084[/C][C]0.466084[/C][/ROW]
[ROW][C]92[/C][C]100[/C][C]100.409[/C][C]100.5[/C][C]-0.0910838[/C][C]-0.408916[/C][/ROW]
[ROW][C]93[/C][C]99[/C][C]100.425[/C][C]100.375[/C][C]0.0495412[/C][C]-1.42454[/C][/ROW]
[ROW][C]94[/C][C]102[/C][C]100.888[/C][C]100.208[/C][C]0.67975[/C][C]1.11192[/C][/ROW]
[ROW][C]95[/C][C]102[/C][C]100.753[/C][C]100.083[/C][C]0.669333[/C][C]1.24733[/C][/ROW]
[ROW][C]96[/C][C]98[/C][C]100.112[/C][C]99.9583[/C][C]0.153708[/C][C]-2.11204[/C][/ROW]
[ROW][C]97[/C][C]100[/C][C]99.56[/C][C]99.9167[/C][C]-0.356709[/C][C]0.440042[/C][/ROW]
[ROW][C]98[/C][C]101[/C][C]100.268[/C][C]99.875[/C][C]0.393291[/C][C]0.731709[/C][/ROW]
[ROW][C]99[/C][C]98[/C][C]98.8568[/C][C]99.8333[/C][C]-0.9765[/C][C]-0.856833[/C][/ROW]
[ROW][C]100[/C][C]99[/C][C]100.31[/C][C]99.7917[/C][C]0.518291[/C][C]-1.30996[/C][/ROW]
[ROW][C]101[/C][C]99[/C][C]99.2683[/C][C]99.625[/C][C]-0.356709[/C][C]-0.268291[/C][/ROW]
[ROW][C]102[/C][C]101[/C][C]NA[/C][C]NA[/C][C]0.283172[/C][C]NA[/C][/ROW]
[ROW][C]103[/C][C]100[/C][C]NA[/C][C]NA[/C][C]-0.966084[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]99[/C][C]NA[/C][C]NA[/C][C]-0.0910838[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]99[/C][C]NA[/C][C]NA[/C][C]0.0495412[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]101[/C][C]NA[/C][C]NA[/C][C]0.67975[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]99[/C][C]NA[/C][C]NA[/C][C]0.669333[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302823&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302823&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	99	NA	NA	-0.356709	NA
2	102	NA	NA	0.393291	NA
3	100	NA	NA	-0.9765	NA
4	98	NA	NA	0.518291	NA
5	98	NA	NA	-0.356709	NA
6	99	NA	NA	0.283172	NA
7	100	98.9922	99.9583	-0.966084	1.00775
8	99	99.8672	99.9583	-0.0910838	-0.86725
9	100	99.9245	99.875	0.0495412	0.0754588
10	99	100.596	99.9167	0.67975	-1.59642
11	101	100.836	100.167	0.669333	0.164
12	104	100.487	100.333	0.153708	3.51296
13	100	99.935	100.292	-0.356709	0.0650422
14	101	100.685	100.292	0.393291	0.315042
15	99	99.3152	100.292	-0.9765	-0.315166
16	100	101.018	100.5	0.518291	-1.01829
17	102	100.352	100.708	-0.356709	1.64838
18	99	100.825	100.542	0.283172	-1.82484
19	99	99.4506	100.417	-0.966084	-0.450583
20	100	100.326	100.417	-0.0910838	-0.325583
21	99	100.466	100.417	0.0495412	-1.46621
22	105	101.096	100.417	0.67975	3.90358
23	100	101.003	100.333	0.669333	-1.00267
24	101	100.445	100.292	0.153708	0.554625
25	100	100.018	100.375	-0.356709	-0.0182912
26	101	100.852	100.458	0.393291	0.148375
27	99	99.6068	100.583	-0.9765	-0.606833
28	100	100.977	100.458	0.518291	-0.976625
29	100	99.8516	100.208	-0.356709	0.148375
30	100	100.45	100.167	0.283172	-0.449839
31	100	99.2422	100.208	-0.966084	0.75775
32	101	100.159	100.25	-0.0910838	0.841084
33	101	100.341	100.292	0.0495412	0.658792
34	100	101.013	100.333	0.67975	-1.01308
35	99	101.003	100.333	0.669333	-2.00267
36	101	100.529	100.375	0.153708	0.471292
37	101	99.9766	100.333	-0.356709	1.02338
38	101	100.56	100.167	0.393291	0.440042
39	100	99.0652	100.042	-0.9765	0.934834
40	100	100.56	100.042	0.518291	-0.559958
41	100	99.7683	100.125	-0.356709	0.231709
42	101	100.408	100.125	0.283172	0.591828
43	98	99.0339	100	-0.966084	-1.03392
44	99	99.7839	99.875	-0.0910838	-0.783916
45	100	99.8412	99.7917	0.0495412	0.158792
46	101	100.471	99.7917	0.67975	0.528584
47	100	100.419	99.75	0.669333	-0.419333
48	100	99.7787	99.625	0.153708	0.221292
49	99	99.2683	99.625	-0.356709	-0.268291
50	100	100.227	99.8333	0.393291	-0.226625
51	99	99.2318	100.208	-0.9765	-0.231833
52	101	100.893	100.375	0.518291	0.106709
53	98	100.018	100.375	-0.356709	-2.01829
54	100	100.7	100.417	0.283172	-0.699839
55	99	99.4506	100.417	-0.966084	-0.450583
56	103	100.326	100.417	-0.0910838	2.67442
57	105	100.466	100.417	0.0495412	4.53379
58	100	101.263	100.583	0.67975	-1.26308
59	101	101.461	100.792	0.669333	-0.461
60	100	101.07	100.917	0.153708	-1.07037
61	99	100.685	101.042	-0.356709	-1.68496
62	100	101.352	100.958	0.393291	-1.35162
63	99	99.6068	100.583	-0.9765	-0.606833
64	105	100.935	100.417	0.518291	4.06504
65	99	100.06	100.417	-0.356709	-1.05996
66	102	100.658	100.375	0.283172	1.34183
67	100	99.4922	100.458	-0.966084	0.50775
68	100	100.409	100.5	-0.0910838	-0.408916
69	99	100.55	100.5	0.0495412	-1.54954
70	102	101.013	100.333	0.67975	0.986917
71	99	100.878	100.208	0.669333	-1.87767
72	101	100.32	100.167	0.153708	0.679625
73	100	99.6433	100	-0.356709	0.356709
74	100	100.268	99.875	0.393291	-0.268291
75	99	98.8568	99.8333	-0.9765	0.143167
76	101	100.185	99.6667	0.518291	0.815042
77	100	99.3933	99.75	-0.356709	0.606709
78	100	100.158	99.875	0.283172	-0.158172
79	98	98.7839	99.75	-0.966084	-0.783916
80	99	99.7006	99.7917	-0.0910838	-0.700583
81	99	99.9662	99.9167	0.0495412	-0.966208
82	98	100.638	99.9583	0.67975	-2.63808
83	105	100.628	99.9583	0.669333	4.37233
84	98	100.237	100.083	0.153708	-2.23704
85	100	99.8933	100.25	-0.356709	0.106709
86	101	100.768	100.375	0.393291	0.231709
87	101	99.4402	100.417	-0.9765	1.55983
88	100	101.102	100.583	0.518291	-1.10162
89	101	100.268	100.625	-0.356709	0.731709
90	102	100.783	100.5	0.283172	1.21683
91	100	99.5339	100.5	-0.966084	0.466084
92	100	100.409	100.5	-0.0910838	-0.408916
93	99	100.425	100.375	0.0495412	-1.42454
94	102	100.888	100.208	0.67975	1.11192
95	102	100.753	100.083	0.669333	1.24733
96	98	100.112	99.9583	0.153708	-2.11204
97	100	99.56	99.9167	-0.356709	0.440042
98	101	100.268	99.875	0.393291	0.731709
99	98	98.8568	99.8333	-0.9765	-0.856833
100	99	100.31	99.7917	0.518291	-1.30996
101	99	99.2683	99.625	-0.356709	-0.268291
102	101	NA	NA	0.283172	NA
103	100	NA	NA	-0.966084	NA
104	99	NA	NA	-0.0910838	NA
105	99	NA	NA	0.0495412	NA
106	101	NA	NA	0.67975	NA
107	99	NA	NA	0.669333	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