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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 26 Apr 2016 12:26:13 +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/26/t14616700096vez2stx3kdtwo2.htm/, Retrieved Fri, 03 May 2024 16:07:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294855, Retrieved Fri, 03 May 2024 16:07:20 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

102

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

-       [Classical Decomposition] [CPI Wijnen - Addi...] [2016-04-26 11:26:13] [25a5f245cb671e152cfd8b6d35402e87] [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	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294855&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294855&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294855&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	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	110.27	NA	NA	1.12892	NA
2	110.91	NA	NA	0.776319	NA
3	110.27	NA	NA	0.245799	NA
4	109.41	NA	NA	0.0354861	NA
5	111.47	NA	NA	0.119549	NA
6	110.77	NA	NA	-0.287118	NA
7	110.83	110.698	110.49	0.207986	0.131597
8	110.52	110.362	110.567	-0.204722	0.158056
9	110.44	110.51	110.608	-0.0976389	-0.0702778
10	109.99	110.309	110.688	-0.37941	-0.318507
11	110.55	110.441	110.811	-0.369931	0.108681
12	109.99	109.724	110.899	-1.17524	0.266076
13	111.2	112.138	111.009	1.12892	-0.93809
14	111.81	111.914	111.137	0.776319	-0.103819
15	110.36	111.558	111.312	0.245799	-1.1983
16	111.24	111.583	111.548	0.0354861	-0.342986
17	112.6	111.945	111.826	0.119549	0.654618
18	111.75	111.852	112.139	-0.287118	-0.101632
19	112.49	112.784	112.576	0.207986	-0.293819
20	111.94	112.924	113.128	-0.204722	-0.983611
21	113.22	113.668	113.766	-0.0976389	-0.448194
22	112.85	114.036	114.415	-0.37941	-1.18559
23	114.37	114.534	114.904	-0.369931	-0.163819
24	113.68	114.172	115.348	-1.17524	-0.492257
25	118	116.955	115.826	1.12892	1.04524
26	118.27	117.114	116.338	0.776319	1.15618
27	119.2	117.048	116.802	0.245799	2.1517
28	117.98	117.288	117.252	0.0354861	0.692431
29	117.59	117.81	117.691	0.119549	-0.220382
30	117.41	117.745	118.032	-0.287118	-0.335382
31	118.31	118.489	118.281	0.207986	-0.179236
32	118.4	118.23	118.435	-0.204722	0.170139
33	117.92	118.381	118.479	-0.0976389	-0.461111
34	118.94	118.091	118.47	-0.37941	0.848993
35	118.81	118.175	118.545	-0.369931	0.635347
36	117.44	117.496	118.671	-1.17524	-0.0560069
37	120.21	119.915	118.786	1.12892	0.295243
38	119.74	119.659	118.882	0.776319	0.0811806
39	118.79	119.252	119.006	0.245799	-0.461632
40	118.19	119.137	119.101	0.0354861	-0.946736
41	119.16	119.209	119.089	0.119549	-0.0487153
42	118.88	118.807	119.095	-0.287118	0.0725347
43	119.59	119.322	119.114	0.207986	0.267847
44	119.44	118.858	119.063	-0.204722	0.581806
45	119.84	118.934	119.032	-0.0976389	0.905972
46	119.31	118.729	119.108	-0.37941	0.581493
47	118.15	118.804	119.174	-0.369931	-0.653819
48	118.23	118.021	119.197	-1.17524	0.208576
49	119.89	120.366	119.237	1.12892	-0.476007
50	118.83	120.037	119.261	0.776319	-1.20715
51	118.95	119.515	119.27	0.245799	-0.565382
52	119.86	119.336	119.301	0.0354861	0.523681
53	119.07	119.529	119.41	0.119549	-0.459132
54	119.52	119.229	119.516	-0.287118	0.290868
55	119.92	NA	NA	0.207986	NA
56	119.68	NA	NA	-0.204722	NA
57	119.81	NA	NA	-0.0976389	NA
58	120.09	NA	NA	-0.37941	NA
59	119.98	NA	NA	-0.369931	NA
60	118.96	NA	NA	-1.17524	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 110.27 & NA & NA & 1.12892 & NA \tabularnewline
2 & 110.91 & NA & NA & 0.776319 & NA \tabularnewline
3 & 110.27 & NA & NA & 0.245799 & NA \tabularnewline
4 & 109.41 & NA & NA & 0.0354861 & NA \tabularnewline
5 & 111.47 & NA & NA & 0.119549 & NA \tabularnewline
6 & 110.77 & NA & NA & -0.287118 & NA \tabularnewline
7 & 110.83 & 110.698 & 110.49 & 0.207986 & 0.131597 \tabularnewline
8 & 110.52 & 110.362 & 110.567 & -0.204722 & 0.158056 \tabularnewline
9 & 110.44 & 110.51 & 110.608 & -0.0976389 & -0.0702778 \tabularnewline
10 & 109.99 & 110.309 & 110.688 & -0.37941 & -0.318507 \tabularnewline
11 & 110.55 & 110.441 & 110.811 & -0.369931 & 0.108681 \tabularnewline
12 & 109.99 & 109.724 & 110.899 & -1.17524 & 0.266076 \tabularnewline
13 & 111.2 & 112.138 & 111.009 & 1.12892 & -0.93809 \tabularnewline
14 & 111.81 & 111.914 & 111.137 & 0.776319 & -0.103819 \tabularnewline
15 & 110.36 & 111.558 & 111.312 & 0.245799 & -1.1983 \tabularnewline
16 & 111.24 & 111.583 & 111.548 & 0.0354861 & -0.342986 \tabularnewline
17 & 112.6 & 111.945 & 111.826 & 0.119549 & 0.654618 \tabularnewline
18 & 111.75 & 111.852 & 112.139 & -0.287118 & -0.101632 \tabularnewline
19 & 112.49 & 112.784 & 112.576 & 0.207986 & -0.293819 \tabularnewline
20 & 111.94 & 112.924 & 113.128 & -0.204722 & -0.983611 \tabularnewline
21 & 113.22 & 113.668 & 113.766 & -0.0976389 & -0.448194 \tabularnewline
22 & 112.85 & 114.036 & 114.415 & -0.37941 & -1.18559 \tabularnewline
23 & 114.37 & 114.534 & 114.904 & -0.369931 & -0.163819 \tabularnewline
24 & 113.68 & 114.172 & 115.348 & -1.17524 & -0.492257 \tabularnewline
25 & 118 & 116.955 & 115.826 & 1.12892 & 1.04524 \tabularnewline
26 & 118.27 & 117.114 & 116.338 & 0.776319 & 1.15618 \tabularnewline
27 & 119.2 & 117.048 & 116.802 & 0.245799 & 2.1517 \tabularnewline
28 & 117.98 & 117.288 & 117.252 & 0.0354861 & 0.692431 \tabularnewline
29 & 117.59 & 117.81 & 117.691 & 0.119549 & -0.220382 \tabularnewline
30 & 117.41 & 117.745 & 118.032 & -0.287118 & -0.335382 \tabularnewline
31 & 118.31 & 118.489 & 118.281 & 0.207986 & -0.179236 \tabularnewline
32 & 118.4 & 118.23 & 118.435 & -0.204722 & 0.170139 \tabularnewline
33 & 117.92 & 118.381 & 118.479 & -0.0976389 & -0.461111 \tabularnewline
34 & 118.94 & 118.091 & 118.47 & -0.37941 & 0.848993 \tabularnewline
35 & 118.81 & 118.175 & 118.545 & -0.369931 & 0.635347 \tabularnewline
36 & 117.44 & 117.496 & 118.671 & -1.17524 & -0.0560069 \tabularnewline
37 & 120.21 & 119.915 & 118.786 & 1.12892 & 0.295243 \tabularnewline
38 & 119.74 & 119.659 & 118.882 & 0.776319 & 0.0811806 \tabularnewline
39 & 118.79 & 119.252 & 119.006 & 0.245799 & -0.461632 \tabularnewline
40 & 118.19 & 119.137 & 119.101 & 0.0354861 & -0.946736 \tabularnewline
41 & 119.16 & 119.209 & 119.089 & 0.119549 & -0.0487153 \tabularnewline
42 & 118.88 & 118.807 & 119.095 & -0.287118 & 0.0725347 \tabularnewline
43 & 119.59 & 119.322 & 119.114 & 0.207986 & 0.267847 \tabularnewline
44 & 119.44 & 118.858 & 119.063 & -0.204722 & 0.581806 \tabularnewline
45 & 119.84 & 118.934 & 119.032 & -0.0976389 & 0.905972 \tabularnewline
46 & 119.31 & 118.729 & 119.108 & -0.37941 & 0.581493 \tabularnewline
47 & 118.15 & 118.804 & 119.174 & -0.369931 & -0.653819 \tabularnewline
48 & 118.23 & 118.021 & 119.197 & -1.17524 & 0.208576 \tabularnewline
49 & 119.89 & 120.366 & 119.237 & 1.12892 & -0.476007 \tabularnewline
50 & 118.83 & 120.037 & 119.261 & 0.776319 & -1.20715 \tabularnewline
51 & 118.95 & 119.515 & 119.27 & 0.245799 & -0.565382 \tabularnewline
52 & 119.86 & 119.336 & 119.301 & 0.0354861 & 0.523681 \tabularnewline
53 & 119.07 & 119.529 & 119.41 & 0.119549 & -0.459132 \tabularnewline
54 & 119.52 & 119.229 & 119.516 & -0.287118 & 0.290868 \tabularnewline
55 & 119.92 & NA & NA & 0.207986 & NA \tabularnewline
56 & 119.68 & NA & NA & -0.204722 & NA \tabularnewline
57 & 119.81 & NA & NA & -0.0976389 & NA \tabularnewline
58 & 120.09 & NA & NA & -0.37941 & NA \tabularnewline
59 & 119.98 & NA & NA & -0.369931 & NA \tabularnewline
60 & 118.96 & NA & NA & -1.17524 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294855&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]110.27[/C][C]NA[/C][C]NA[/C][C]1.12892[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]110.91[/C][C]NA[/C][C]NA[/C][C]0.776319[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]110.27[/C][C]NA[/C][C]NA[/C][C]0.245799[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]109.41[/C][C]NA[/C][C]NA[/C][C]0.0354861[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]111.47[/C][C]NA[/C][C]NA[/C][C]0.119549[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]110.77[/C][C]NA[/C][C]NA[/C][C]-0.287118[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]110.83[/C][C]110.698[/C][C]110.49[/C][C]0.207986[/C][C]0.131597[/C][/ROW]
[ROW][C]8[/C][C]110.52[/C][C]110.362[/C][C]110.567[/C][C]-0.204722[/C][C]0.158056[/C][/ROW]
[ROW][C]9[/C][C]110.44[/C][C]110.51[/C][C]110.608[/C][C]-0.0976389[/C][C]-0.0702778[/C][/ROW]
[ROW][C]10[/C][C]109.99[/C][C]110.309[/C][C]110.688[/C][C]-0.37941[/C][C]-0.318507[/C][/ROW]
[ROW][C]11[/C][C]110.55[/C][C]110.441[/C][C]110.811[/C][C]-0.369931[/C][C]0.108681[/C][/ROW]
[ROW][C]12[/C][C]109.99[/C][C]109.724[/C][C]110.899[/C][C]-1.17524[/C][C]0.266076[/C][/ROW]
[ROW][C]13[/C][C]111.2[/C][C]112.138[/C][C]111.009[/C][C]1.12892[/C][C]-0.93809[/C][/ROW]
[ROW][C]14[/C][C]111.81[/C][C]111.914[/C][C]111.137[/C][C]0.776319[/C][C]-0.103819[/C][/ROW]
[ROW][C]15[/C][C]110.36[/C][C]111.558[/C][C]111.312[/C][C]0.245799[/C][C]-1.1983[/C][/ROW]
[ROW][C]16[/C][C]111.24[/C][C]111.583[/C][C]111.548[/C][C]0.0354861[/C][C]-0.342986[/C][/ROW]
[ROW][C]17[/C][C]112.6[/C][C]111.945[/C][C]111.826[/C][C]0.119549[/C][C]0.654618[/C][/ROW]
[ROW][C]18[/C][C]111.75[/C][C]111.852[/C][C]112.139[/C][C]-0.287118[/C][C]-0.101632[/C][/ROW]
[ROW][C]19[/C][C]112.49[/C][C]112.784[/C][C]112.576[/C][C]0.207986[/C][C]-0.293819[/C][/ROW]
[ROW][C]20[/C][C]111.94[/C][C]112.924[/C][C]113.128[/C][C]-0.204722[/C][C]-0.983611[/C][/ROW]
[ROW][C]21[/C][C]113.22[/C][C]113.668[/C][C]113.766[/C][C]-0.0976389[/C][C]-0.448194[/C][/ROW]
[ROW][C]22[/C][C]112.85[/C][C]114.036[/C][C]114.415[/C][C]-0.37941[/C][C]-1.18559[/C][/ROW]
[ROW][C]23[/C][C]114.37[/C][C]114.534[/C][C]114.904[/C][C]-0.369931[/C][C]-0.163819[/C][/ROW]
[ROW][C]24[/C][C]113.68[/C][C]114.172[/C][C]115.348[/C][C]-1.17524[/C][C]-0.492257[/C][/ROW]
[ROW][C]25[/C][C]118[/C][C]116.955[/C][C]115.826[/C][C]1.12892[/C][C]1.04524[/C][/ROW]
[ROW][C]26[/C][C]118.27[/C][C]117.114[/C][C]116.338[/C][C]0.776319[/C][C]1.15618[/C][/ROW]
[ROW][C]27[/C][C]119.2[/C][C]117.048[/C][C]116.802[/C][C]0.245799[/C][C]2.1517[/C][/ROW]
[ROW][C]28[/C][C]117.98[/C][C]117.288[/C][C]117.252[/C][C]0.0354861[/C][C]0.692431[/C][/ROW]
[ROW][C]29[/C][C]117.59[/C][C]117.81[/C][C]117.691[/C][C]0.119549[/C][C]-0.220382[/C][/ROW]
[ROW][C]30[/C][C]117.41[/C][C]117.745[/C][C]118.032[/C][C]-0.287118[/C][C]-0.335382[/C][/ROW]
[ROW][C]31[/C][C]118.31[/C][C]118.489[/C][C]118.281[/C][C]0.207986[/C][C]-0.179236[/C][/ROW]
[ROW][C]32[/C][C]118.4[/C][C]118.23[/C][C]118.435[/C][C]-0.204722[/C][C]0.170139[/C][/ROW]
[ROW][C]33[/C][C]117.92[/C][C]118.381[/C][C]118.479[/C][C]-0.0976389[/C][C]-0.461111[/C][/ROW]
[ROW][C]34[/C][C]118.94[/C][C]118.091[/C][C]118.47[/C][C]-0.37941[/C][C]0.848993[/C][/ROW]
[ROW][C]35[/C][C]118.81[/C][C]118.175[/C][C]118.545[/C][C]-0.369931[/C][C]0.635347[/C][/ROW]
[ROW][C]36[/C][C]117.44[/C][C]117.496[/C][C]118.671[/C][C]-1.17524[/C][C]-0.0560069[/C][/ROW]
[ROW][C]37[/C][C]120.21[/C][C]119.915[/C][C]118.786[/C][C]1.12892[/C][C]0.295243[/C][/ROW]
[ROW][C]38[/C][C]119.74[/C][C]119.659[/C][C]118.882[/C][C]0.776319[/C][C]0.0811806[/C][/ROW]
[ROW][C]39[/C][C]118.79[/C][C]119.252[/C][C]119.006[/C][C]0.245799[/C][C]-0.461632[/C][/ROW]
[ROW][C]40[/C][C]118.19[/C][C]119.137[/C][C]119.101[/C][C]0.0354861[/C][C]-0.946736[/C][/ROW]
[ROW][C]41[/C][C]119.16[/C][C]119.209[/C][C]119.089[/C][C]0.119549[/C][C]-0.0487153[/C][/ROW]
[ROW][C]42[/C][C]118.88[/C][C]118.807[/C][C]119.095[/C][C]-0.287118[/C][C]0.0725347[/C][/ROW]
[ROW][C]43[/C][C]119.59[/C][C]119.322[/C][C]119.114[/C][C]0.207986[/C][C]0.267847[/C][/ROW]
[ROW][C]44[/C][C]119.44[/C][C]118.858[/C][C]119.063[/C][C]-0.204722[/C][C]0.581806[/C][/ROW]
[ROW][C]45[/C][C]119.84[/C][C]118.934[/C][C]119.032[/C][C]-0.0976389[/C][C]0.905972[/C][/ROW]
[ROW][C]46[/C][C]119.31[/C][C]118.729[/C][C]119.108[/C][C]-0.37941[/C][C]0.581493[/C][/ROW]
[ROW][C]47[/C][C]118.15[/C][C]118.804[/C][C]119.174[/C][C]-0.369931[/C][C]-0.653819[/C][/ROW]
[ROW][C]48[/C][C]118.23[/C][C]118.021[/C][C]119.197[/C][C]-1.17524[/C][C]0.208576[/C][/ROW]
[ROW][C]49[/C][C]119.89[/C][C]120.366[/C][C]119.237[/C][C]1.12892[/C][C]-0.476007[/C][/ROW]
[ROW][C]50[/C][C]118.83[/C][C]120.037[/C][C]119.261[/C][C]0.776319[/C][C]-1.20715[/C][/ROW]
[ROW][C]51[/C][C]118.95[/C][C]119.515[/C][C]119.27[/C][C]0.245799[/C][C]-0.565382[/C][/ROW]
[ROW][C]52[/C][C]119.86[/C][C]119.336[/C][C]119.301[/C][C]0.0354861[/C][C]0.523681[/C][/ROW]
[ROW][C]53[/C][C]119.07[/C][C]119.529[/C][C]119.41[/C][C]0.119549[/C][C]-0.459132[/C][/ROW]
[ROW][C]54[/C][C]119.52[/C][C]119.229[/C][C]119.516[/C][C]-0.287118[/C][C]0.290868[/C][/ROW]
[ROW][C]55[/C][C]119.92[/C][C]NA[/C][C]NA[/C][C]0.207986[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]119.68[/C][C]NA[/C][C]NA[/C][C]-0.204722[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]119.81[/C][C]NA[/C][C]NA[/C][C]-0.0976389[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]120.09[/C][C]NA[/C][C]NA[/C][C]-0.37941[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]119.98[/C][C]NA[/C][C]NA[/C][C]-0.369931[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]118.96[/C][C]NA[/C][C]NA[/C][C]-1.17524[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294855&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294855&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	110.27	NA	NA	1.12892	NA
2	110.91	NA	NA	0.776319	NA
3	110.27	NA	NA	0.245799	NA
4	109.41	NA	NA	0.0354861	NA
5	111.47	NA	NA	0.119549	NA
6	110.77	NA	NA	-0.287118	NA
7	110.83	110.698	110.49	0.207986	0.131597
8	110.52	110.362	110.567	-0.204722	0.158056
9	110.44	110.51	110.608	-0.0976389	-0.0702778
10	109.99	110.309	110.688	-0.37941	-0.318507
11	110.55	110.441	110.811	-0.369931	0.108681
12	109.99	109.724	110.899	-1.17524	0.266076
13	111.2	112.138	111.009	1.12892	-0.93809
14	111.81	111.914	111.137	0.776319	-0.103819
15	110.36	111.558	111.312	0.245799	-1.1983
16	111.24	111.583	111.548	0.0354861	-0.342986
17	112.6	111.945	111.826	0.119549	0.654618
18	111.75	111.852	112.139	-0.287118	-0.101632
19	112.49	112.784	112.576	0.207986	-0.293819
20	111.94	112.924	113.128	-0.204722	-0.983611
21	113.22	113.668	113.766	-0.0976389	-0.448194
22	112.85	114.036	114.415	-0.37941	-1.18559
23	114.37	114.534	114.904	-0.369931	-0.163819
24	113.68	114.172	115.348	-1.17524	-0.492257
25	118	116.955	115.826	1.12892	1.04524
26	118.27	117.114	116.338	0.776319	1.15618
27	119.2	117.048	116.802	0.245799	2.1517
28	117.98	117.288	117.252	0.0354861	0.692431
29	117.59	117.81	117.691	0.119549	-0.220382
30	117.41	117.745	118.032	-0.287118	-0.335382
31	118.31	118.489	118.281	0.207986	-0.179236
32	118.4	118.23	118.435	-0.204722	0.170139
33	117.92	118.381	118.479	-0.0976389	-0.461111
34	118.94	118.091	118.47	-0.37941	0.848993
35	118.81	118.175	118.545	-0.369931	0.635347
36	117.44	117.496	118.671	-1.17524	-0.0560069
37	120.21	119.915	118.786	1.12892	0.295243
38	119.74	119.659	118.882	0.776319	0.0811806
39	118.79	119.252	119.006	0.245799	-0.461632
40	118.19	119.137	119.101	0.0354861	-0.946736
41	119.16	119.209	119.089	0.119549	-0.0487153
42	118.88	118.807	119.095	-0.287118	0.0725347
43	119.59	119.322	119.114	0.207986	0.267847
44	119.44	118.858	119.063	-0.204722	0.581806
45	119.84	118.934	119.032	-0.0976389	0.905972
46	119.31	118.729	119.108	-0.37941	0.581493
47	118.15	118.804	119.174	-0.369931	-0.653819
48	118.23	118.021	119.197	-1.17524	0.208576
49	119.89	120.366	119.237	1.12892	-0.476007
50	118.83	120.037	119.261	0.776319	-1.20715
51	118.95	119.515	119.27	0.245799	-0.565382
52	119.86	119.336	119.301	0.0354861	0.523681
53	119.07	119.529	119.41	0.119549	-0.459132
54	119.52	119.229	119.516	-0.287118	0.290868
55	119.92	NA	NA	0.207986	NA
56	119.68	NA	NA	-0.204722	NA
57	119.81	NA	NA	-0.0976389	NA
58	120.09	NA	NA	-0.37941	NA
59	119.98	NA	NA	-0.369931	NA
60	118.96	NA	NA	-1.17524	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 <- '12'
par1 <- 'multiplicative'
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