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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 11 May 2014 13:14:48 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/May/11/t139982852775uoxekjwlmx1ax.htm/, Retrieved Sun, 19 May 2024 16:29:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234795, Retrieved Sun, 19 May 2024 16:29:58 +0000

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Estimated Impact

139

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-     [Classical Decomposition] [] [2014-05-11 16:46:15] [4512ef39545e98c37276c02512a09398]
-    D    [Classical Decomposition] [] [2014-05-11 17:14:48] [5f7d0cda5d8a9348873c82369b6851b6] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234795&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234795&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234795&T=0

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	28.33	NA	NA	-0.0391927	NA
2	28.67	NA	NA	-0.0177344	NA
3	28.81	NA	NA	0.00809896	NA
4	28.99	NA	NA	-0.0136719	NA
5	29.16	NA	NA	0.0140365	NA
6	29.25	NA	NA	0.0492448	NA
7	29.25	29.2872	29.2608	0.0263281	-0.0371615
8	29.38	29.3853	29.38	0.00528646	-0.00528646
9	29.48	29.5105	29.4992	0.0113281	-0.0304948
10	29.65	29.6388	29.6183	0.0204948	0.0111719
11	29.69	29.7147	29.7317	-0.0170052	-0.0246615
12	29.73	29.7995	29.8467	-0.0472135	-0.0694531
13	29.81	29.9279	29.9671	-0.0391927	-0.117891
14	30.05	30.0668	30.0846	-0.0177344	-0.016849
15	30.29	30.2023	30.1942	0.00809896	0.0877344
16	30.37	30.2826	30.2962	-0.0136719	0.0874219
17	30.5	30.407	30.3929	0.0140365	0.0930469
18	30.67	30.5372	30.4879	0.0492448	0.132839
19	30.72	30.6076	30.5812	0.0263281	0.112422
20	30.73	30.6703	30.665	0.00528646	0.0597135
21	30.76	30.7422	30.7308	0.0113281	0.0178385
22	30.82	30.8055	30.785	0.0204948	0.0145052
23	30.84	30.8184	30.8354	-0.0170052	0.0215885
24	30.86	30.834	30.8812	-0.0472135	0.0259635
25	30.92	30.8829	30.9221	-0.0391927	0.0371094
26	30.95	30.9435	30.9612	-0.0177344	0.00648438
27	30.97	31.0118	31.0037	0.00809896	-0.041849
28	30.99	31.0347	31.0483	-0.0136719	-0.0446615
29	31.09	31.1053	31.0912	0.0140365	-0.0152865
30	31.18	31.1826	31.1333	0.0492448	-0.00257812
31	31.19	31.1992	31.1729	0.0263281	-0.00924479
32	31.2	31.2145	31.2092	0.00528646	-0.0144531
33	31.31	31.2555	31.2442	0.0113281	0.0545052
34	31.34	31.2988	31.2783	0.0204948	0.0411719
35	31.35	31.2917	31.3088	-0.0170052	0.0582552
36	31.36	31.2874	31.3346	-0.0472135	0.0726302
37	31.37	31.3196	31.3588	-0.0391927	0.0504427
38	31.37	31.366	31.3838	-0.0177344	0.00398437
39	31.39	31.4143	31.4062	0.00809896	-0.024349
40	31.39	31.4109	31.4246	-0.0136719	-0.0209115
41	31.42	31.4557	31.4417	0.0140365	-0.0357031
42	31.47	31.508	31.4587	0.0492448	-0.0379948
43	31.48	31.5059	31.4796	0.0263281	-0.0259115
44	31.51	31.5099	31.5046	0.00528646	0.000130208
45	31.54	31.5417	31.5304	0.0113281	-0.00174479
46	31.55	31.5767	31.5562	0.0204948	-0.0267448
47	31.55	31.5651	31.5821	-0.0170052	-0.0150781
48	31.57	31.559	31.6062	-0.0472135	0.0109635
49	31.66	31.5896	31.6287	-0.0391927	0.0704427
50	31.68	31.6335	31.6512	-0.0177344	0.0464844
51	31.7	31.6814	31.6733	0.00809896	0.0185677
52	31.7	31.6817	31.6954	-0.0136719	0.0182552
53	31.73	31.732	31.7179	0.0140365	-0.00195312
54	31.74	31.7922	31.7429	0.0492448	-0.0521615
55	31.75	NA	NA	0.0263281	NA
56	31.78	NA	NA	0.00528646	NA
57	31.8	NA	NA	0.0113281	NA
58	31.82	NA	NA	0.0204948	NA
59	31.82	NA	NA	-0.0170052	NA
60	31.9	NA	NA	-0.0472135	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 28.33 & NA & NA & -0.0391927 & NA \tabularnewline
2 & 28.67 & NA & NA & -0.0177344 & NA \tabularnewline
3 & 28.81 & NA & NA & 0.00809896 & NA \tabularnewline
4 & 28.99 & NA & NA & -0.0136719 & NA \tabularnewline
5 & 29.16 & NA & NA & 0.0140365 & NA \tabularnewline
6 & 29.25 & NA & NA & 0.0492448 & NA \tabularnewline
7 & 29.25 & 29.2872 & 29.2608 & 0.0263281 & -0.0371615 \tabularnewline
8 & 29.38 & 29.3853 & 29.38 & 0.00528646 & -0.00528646 \tabularnewline
9 & 29.48 & 29.5105 & 29.4992 & 0.0113281 & -0.0304948 \tabularnewline
10 & 29.65 & 29.6388 & 29.6183 & 0.0204948 & 0.0111719 \tabularnewline
11 & 29.69 & 29.7147 & 29.7317 & -0.0170052 & -0.0246615 \tabularnewline
12 & 29.73 & 29.7995 & 29.8467 & -0.0472135 & -0.0694531 \tabularnewline
13 & 29.81 & 29.9279 & 29.9671 & -0.0391927 & -0.117891 \tabularnewline
14 & 30.05 & 30.0668 & 30.0846 & -0.0177344 & -0.016849 \tabularnewline
15 & 30.29 & 30.2023 & 30.1942 & 0.00809896 & 0.0877344 \tabularnewline
16 & 30.37 & 30.2826 & 30.2962 & -0.0136719 & 0.0874219 \tabularnewline
17 & 30.5 & 30.407 & 30.3929 & 0.0140365 & 0.0930469 \tabularnewline
18 & 30.67 & 30.5372 & 30.4879 & 0.0492448 & 0.132839 \tabularnewline
19 & 30.72 & 30.6076 & 30.5812 & 0.0263281 & 0.112422 \tabularnewline
20 & 30.73 & 30.6703 & 30.665 & 0.00528646 & 0.0597135 \tabularnewline
21 & 30.76 & 30.7422 & 30.7308 & 0.0113281 & 0.0178385 \tabularnewline
22 & 30.82 & 30.8055 & 30.785 & 0.0204948 & 0.0145052 \tabularnewline
23 & 30.84 & 30.8184 & 30.8354 & -0.0170052 & 0.0215885 \tabularnewline
24 & 30.86 & 30.834 & 30.8812 & -0.0472135 & 0.0259635 \tabularnewline
25 & 30.92 & 30.8829 & 30.9221 & -0.0391927 & 0.0371094 \tabularnewline
26 & 30.95 & 30.9435 & 30.9612 & -0.0177344 & 0.00648438 \tabularnewline
27 & 30.97 & 31.0118 & 31.0037 & 0.00809896 & -0.041849 \tabularnewline
28 & 30.99 & 31.0347 & 31.0483 & -0.0136719 & -0.0446615 \tabularnewline
29 & 31.09 & 31.1053 & 31.0912 & 0.0140365 & -0.0152865 \tabularnewline
30 & 31.18 & 31.1826 & 31.1333 & 0.0492448 & -0.00257812 \tabularnewline
31 & 31.19 & 31.1992 & 31.1729 & 0.0263281 & -0.00924479 \tabularnewline
32 & 31.2 & 31.2145 & 31.2092 & 0.00528646 & -0.0144531 \tabularnewline
33 & 31.31 & 31.2555 & 31.2442 & 0.0113281 & 0.0545052 \tabularnewline
34 & 31.34 & 31.2988 & 31.2783 & 0.0204948 & 0.0411719 \tabularnewline
35 & 31.35 & 31.2917 & 31.3088 & -0.0170052 & 0.0582552 \tabularnewline
36 & 31.36 & 31.2874 & 31.3346 & -0.0472135 & 0.0726302 \tabularnewline
37 & 31.37 & 31.3196 & 31.3588 & -0.0391927 & 0.0504427 \tabularnewline
38 & 31.37 & 31.366 & 31.3838 & -0.0177344 & 0.00398437 \tabularnewline
39 & 31.39 & 31.4143 & 31.4062 & 0.00809896 & -0.024349 \tabularnewline
40 & 31.39 & 31.4109 & 31.4246 & -0.0136719 & -0.0209115 \tabularnewline
41 & 31.42 & 31.4557 & 31.4417 & 0.0140365 & -0.0357031 \tabularnewline
42 & 31.47 & 31.508 & 31.4587 & 0.0492448 & -0.0379948 \tabularnewline
43 & 31.48 & 31.5059 & 31.4796 & 0.0263281 & -0.0259115 \tabularnewline
44 & 31.51 & 31.5099 & 31.5046 & 0.00528646 & 0.000130208 \tabularnewline
45 & 31.54 & 31.5417 & 31.5304 & 0.0113281 & -0.00174479 \tabularnewline
46 & 31.55 & 31.5767 & 31.5562 & 0.0204948 & -0.0267448 \tabularnewline
47 & 31.55 & 31.5651 & 31.5821 & -0.0170052 & -0.0150781 \tabularnewline
48 & 31.57 & 31.559 & 31.6062 & -0.0472135 & 0.0109635 \tabularnewline
49 & 31.66 & 31.5896 & 31.6287 & -0.0391927 & 0.0704427 \tabularnewline
50 & 31.68 & 31.6335 & 31.6512 & -0.0177344 & 0.0464844 \tabularnewline
51 & 31.7 & 31.6814 & 31.6733 & 0.00809896 & 0.0185677 \tabularnewline
52 & 31.7 & 31.6817 & 31.6954 & -0.0136719 & 0.0182552 \tabularnewline
53 & 31.73 & 31.732 & 31.7179 & 0.0140365 & -0.00195312 \tabularnewline
54 & 31.74 & 31.7922 & 31.7429 & 0.0492448 & -0.0521615 \tabularnewline
55 & 31.75 & NA & NA & 0.0263281 & NA \tabularnewline
56 & 31.78 & NA & NA & 0.00528646 & NA \tabularnewline
57 & 31.8 & NA & NA & 0.0113281 & NA \tabularnewline
58 & 31.82 & NA & NA & 0.0204948 & NA \tabularnewline
59 & 31.82 & NA & NA & -0.0170052 & NA \tabularnewline
60 & 31.9 & NA & NA & -0.0472135 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234795&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]28.33[/C][C]NA[/C][C]NA[/C][C]-0.0391927[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]28.67[/C][C]NA[/C][C]NA[/C][C]-0.0177344[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]28.81[/C][C]NA[/C][C]NA[/C][C]0.00809896[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]28.99[/C][C]NA[/C][C]NA[/C][C]-0.0136719[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]29.16[/C][C]NA[/C][C]NA[/C][C]0.0140365[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]29.25[/C][C]NA[/C][C]NA[/C][C]0.0492448[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]29.25[/C][C]29.2872[/C][C]29.2608[/C][C]0.0263281[/C][C]-0.0371615[/C][/ROW]
[ROW][C]8[/C][C]29.38[/C][C]29.3853[/C][C]29.38[/C][C]0.00528646[/C][C]-0.00528646[/C][/ROW]
[ROW][C]9[/C][C]29.48[/C][C]29.5105[/C][C]29.4992[/C][C]0.0113281[/C][C]-0.0304948[/C][/ROW]
[ROW][C]10[/C][C]29.65[/C][C]29.6388[/C][C]29.6183[/C][C]0.0204948[/C][C]0.0111719[/C][/ROW]
[ROW][C]11[/C][C]29.69[/C][C]29.7147[/C][C]29.7317[/C][C]-0.0170052[/C][C]-0.0246615[/C][/ROW]
[ROW][C]12[/C][C]29.73[/C][C]29.7995[/C][C]29.8467[/C][C]-0.0472135[/C][C]-0.0694531[/C][/ROW]
[ROW][C]13[/C][C]29.81[/C][C]29.9279[/C][C]29.9671[/C][C]-0.0391927[/C][C]-0.117891[/C][/ROW]
[ROW][C]14[/C][C]30.05[/C][C]30.0668[/C][C]30.0846[/C][C]-0.0177344[/C][C]-0.016849[/C][/ROW]
[ROW][C]15[/C][C]30.29[/C][C]30.2023[/C][C]30.1942[/C][C]0.00809896[/C][C]0.0877344[/C][/ROW]
[ROW][C]16[/C][C]30.37[/C][C]30.2826[/C][C]30.2962[/C][C]-0.0136719[/C][C]0.0874219[/C][/ROW]
[ROW][C]17[/C][C]30.5[/C][C]30.407[/C][C]30.3929[/C][C]0.0140365[/C][C]0.0930469[/C][/ROW]
[ROW][C]18[/C][C]30.67[/C][C]30.5372[/C][C]30.4879[/C][C]0.0492448[/C][C]0.132839[/C][/ROW]
[ROW][C]19[/C][C]30.72[/C][C]30.6076[/C][C]30.5812[/C][C]0.0263281[/C][C]0.112422[/C][/ROW]
[ROW][C]20[/C][C]30.73[/C][C]30.6703[/C][C]30.665[/C][C]0.00528646[/C][C]0.0597135[/C][/ROW]
[ROW][C]21[/C][C]30.76[/C][C]30.7422[/C][C]30.7308[/C][C]0.0113281[/C][C]0.0178385[/C][/ROW]
[ROW][C]22[/C][C]30.82[/C][C]30.8055[/C][C]30.785[/C][C]0.0204948[/C][C]0.0145052[/C][/ROW]
[ROW][C]23[/C][C]30.84[/C][C]30.8184[/C][C]30.8354[/C][C]-0.0170052[/C][C]0.0215885[/C][/ROW]
[ROW][C]24[/C][C]30.86[/C][C]30.834[/C][C]30.8812[/C][C]-0.0472135[/C][C]0.0259635[/C][/ROW]
[ROW][C]25[/C][C]30.92[/C][C]30.8829[/C][C]30.9221[/C][C]-0.0391927[/C][C]0.0371094[/C][/ROW]
[ROW][C]26[/C][C]30.95[/C][C]30.9435[/C][C]30.9612[/C][C]-0.0177344[/C][C]0.00648438[/C][/ROW]
[ROW][C]27[/C][C]30.97[/C][C]31.0118[/C][C]31.0037[/C][C]0.00809896[/C][C]-0.041849[/C][/ROW]
[ROW][C]28[/C][C]30.99[/C][C]31.0347[/C][C]31.0483[/C][C]-0.0136719[/C][C]-0.0446615[/C][/ROW]
[ROW][C]29[/C][C]31.09[/C][C]31.1053[/C][C]31.0912[/C][C]0.0140365[/C][C]-0.0152865[/C][/ROW]
[ROW][C]30[/C][C]31.18[/C][C]31.1826[/C][C]31.1333[/C][C]0.0492448[/C][C]-0.00257812[/C][/ROW]
[ROW][C]31[/C][C]31.19[/C][C]31.1992[/C][C]31.1729[/C][C]0.0263281[/C][C]-0.00924479[/C][/ROW]
[ROW][C]32[/C][C]31.2[/C][C]31.2145[/C][C]31.2092[/C][C]0.00528646[/C][C]-0.0144531[/C][/ROW]
[ROW][C]33[/C][C]31.31[/C][C]31.2555[/C][C]31.2442[/C][C]0.0113281[/C][C]0.0545052[/C][/ROW]
[ROW][C]34[/C][C]31.34[/C][C]31.2988[/C][C]31.2783[/C][C]0.0204948[/C][C]0.0411719[/C][/ROW]
[ROW][C]35[/C][C]31.35[/C][C]31.2917[/C][C]31.3088[/C][C]-0.0170052[/C][C]0.0582552[/C][/ROW]
[ROW][C]36[/C][C]31.36[/C][C]31.2874[/C][C]31.3346[/C][C]-0.0472135[/C][C]0.0726302[/C][/ROW]
[ROW][C]37[/C][C]31.37[/C][C]31.3196[/C][C]31.3588[/C][C]-0.0391927[/C][C]0.0504427[/C][/ROW]
[ROW][C]38[/C][C]31.37[/C][C]31.366[/C][C]31.3838[/C][C]-0.0177344[/C][C]0.00398437[/C][/ROW]
[ROW][C]39[/C][C]31.39[/C][C]31.4143[/C][C]31.4062[/C][C]0.00809896[/C][C]-0.024349[/C][/ROW]
[ROW][C]40[/C][C]31.39[/C][C]31.4109[/C][C]31.4246[/C][C]-0.0136719[/C][C]-0.0209115[/C][/ROW]
[ROW][C]41[/C][C]31.42[/C][C]31.4557[/C][C]31.4417[/C][C]0.0140365[/C][C]-0.0357031[/C][/ROW]
[ROW][C]42[/C][C]31.47[/C][C]31.508[/C][C]31.4587[/C][C]0.0492448[/C][C]-0.0379948[/C][/ROW]
[ROW][C]43[/C][C]31.48[/C][C]31.5059[/C][C]31.4796[/C][C]0.0263281[/C][C]-0.0259115[/C][/ROW]
[ROW][C]44[/C][C]31.51[/C][C]31.5099[/C][C]31.5046[/C][C]0.00528646[/C][C]0.000130208[/C][/ROW]
[ROW][C]45[/C][C]31.54[/C][C]31.5417[/C][C]31.5304[/C][C]0.0113281[/C][C]-0.00174479[/C][/ROW]
[ROW][C]46[/C][C]31.55[/C][C]31.5767[/C][C]31.5562[/C][C]0.0204948[/C][C]-0.0267448[/C][/ROW]
[ROW][C]47[/C][C]31.55[/C][C]31.5651[/C][C]31.5821[/C][C]-0.0170052[/C][C]-0.0150781[/C][/ROW]
[ROW][C]48[/C][C]31.57[/C][C]31.559[/C][C]31.6062[/C][C]-0.0472135[/C][C]0.0109635[/C][/ROW]
[ROW][C]49[/C][C]31.66[/C][C]31.5896[/C][C]31.6287[/C][C]-0.0391927[/C][C]0.0704427[/C][/ROW]
[ROW][C]50[/C][C]31.68[/C][C]31.6335[/C][C]31.6512[/C][C]-0.0177344[/C][C]0.0464844[/C][/ROW]
[ROW][C]51[/C][C]31.7[/C][C]31.6814[/C][C]31.6733[/C][C]0.00809896[/C][C]0.0185677[/C][/ROW]
[ROW][C]52[/C][C]31.7[/C][C]31.6817[/C][C]31.6954[/C][C]-0.0136719[/C][C]0.0182552[/C][/ROW]
[ROW][C]53[/C][C]31.73[/C][C]31.732[/C][C]31.7179[/C][C]0.0140365[/C][C]-0.00195312[/C][/ROW]
[ROW][C]54[/C][C]31.74[/C][C]31.7922[/C][C]31.7429[/C][C]0.0492448[/C][C]-0.0521615[/C][/ROW]
[ROW][C]55[/C][C]31.75[/C][C]NA[/C][C]NA[/C][C]0.0263281[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]31.78[/C][C]NA[/C][C]NA[/C][C]0.00528646[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]31.8[/C][C]NA[/C][C]NA[/C][C]0.0113281[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]31.82[/C][C]NA[/C][C]NA[/C][C]0.0204948[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]31.82[/C][C]NA[/C][C]NA[/C][C]-0.0170052[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]31.9[/C][C]NA[/C][C]NA[/C][C]-0.0472135[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234795&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234795&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	28.33	NA	NA	-0.0391927	NA
2	28.67	NA	NA	-0.0177344	NA
3	28.81	NA	NA	0.00809896	NA
4	28.99	NA	NA	-0.0136719	NA
5	29.16	NA	NA	0.0140365	NA
6	29.25	NA	NA	0.0492448	NA
7	29.25	29.2872	29.2608	0.0263281	-0.0371615
8	29.38	29.3853	29.38	0.00528646	-0.00528646
9	29.48	29.5105	29.4992	0.0113281	-0.0304948
10	29.65	29.6388	29.6183	0.0204948	0.0111719
11	29.69	29.7147	29.7317	-0.0170052	-0.0246615
12	29.73	29.7995	29.8467	-0.0472135	-0.0694531
13	29.81	29.9279	29.9671	-0.0391927	-0.117891
14	30.05	30.0668	30.0846	-0.0177344	-0.016849
15	30.29	30.2023	30.1942	0.00809896	0.0877344
16	30.37	30.2826	30.2962	-0.0136719	0.0874219
17	30.5	30.407	30.3929	0.0140365	0.0930469
18	30.67	30.5372	30.4879	0.0492448	0.132839
19	30.72	30.6076	30.5812	0.0263281	0.112422
20	30.73	30.6703	30.665	0.00528646	0.0597135
21	30.76	30.7422	30.7308	0.0113281	0.0178385
22	30.82	30.8055	30.785	0.0204948	0.0145052
23	30.84	30.8184	30.8354	-0.0170052	0.0215885
24	30.86	30.834	30.8812	-0.0472135	0.0259635
25	30.92	30.8829	30.9221	-0.0391927	0.0371094
26	30.95	30.9435	30.9612	-0.0177344	0.00648438
27	30.97	31.0118	31.0037	0.00809896	-0.041849
28	30.99	31.0347	31.0483	-0.0136719	-0.0446615
29	31.09	31.1053	31.0912	0.0140365	-0.0152865
30	31.18	31.1826	31.1333	0.0492448	-0.00257812
31	31.19	31.1992	31.1729	0.0263281	-0.00924479
32	31.2	31.2145	31.2092	0.00528646	-0.0144531
33	31.31	31.2555	31.2442	0.0113281	0.0545052
34	31.34	31.2988	31.2783	0.0204948	0.0411719
35	31.35	31.2917	31.3088	-0.0170052	0.0582552
36	31.36	31.2874	31.3346	-0.0472135	0.0726302
37	31.37	31.3196	31.3588	-0.0391927	0.0504427
38	31.37	31.366	31.3838	-0.0177344	0.00398437
39	31.39	31.4143	31.4062	0.00809896	-0.024349
40	31.39	31.4109	31.4246	-0.0136719	-0.0209115
41	31.42	31.4557	31.4417	0.0140365	-0.0357031
42	31.47	31.508	31.4587	0.0492448	-0.0379948
43	31.48	31.5059	31.4796	0.0263281	-0.0259115
44	31.51	31.5099	31.5046	0.00528646	0.000130208
45	31.54	31.5417	31.5304	0.0113281	-0.00174479
46	31.55	31.5767	31.5562	0.0204948	-0.0267448
47	31.55	31.5651	31.5821	-0.0170052	-0.0150781
48	31.57	31.559	31.6062	-0.0472135	0.0109635
49	31.66	31.5896	31.6287	-0.0391927	0.0704427
50	31.68	31.6335	31.6512	-0.0177344	0.0464844
51	31.7	31.6814	31.6733	0.00809896	0.0185677
52	31.7	31.6817	31.6954	-0.0136719	0.0182552
53	31.73	31.732	31.7179	0.0140365	-0.00195312
54	31.74	31.7922	31.7429	0.0492448	-0.0521615
55	31.75	NA	NA	0.0263281	NA
56	31.78	NA	NA	0.00528646	NA
57	31.8	NA	NA	0.0113281	NA
58	31.82	NA	NA	0.0204948	NA
59	31.82	NA	NA	-0.0170052	NA
60	31.9	NA	NA	-0.0472135	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