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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 26 Apr 2016 17:51:15 +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/t1461689505exkbj38k34t0l56.htm/, Retrieved Fri, 03 May 2024 16:02:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294920, Retrieved Fri, 03 May 2024 16:02:36 +0000

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

-       [Classical Decomposition] [] [2016-04-26 16:51:15] [60c466f2753cef60360c0cd0685abd02] [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	'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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294920&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294920&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294920&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	93.91	NA	NA	-0.26033	NA
2	94.27	NA	NA	0.0446701	NA
3	94.55	NA	NA	0.187795	NA
4	94.66	NA	NA	0.130816	NA
5	94.78	NA	NA	0.0436285	NA
6	94.91	NA	NA	0.0197743	NA
7	95.2	95.199	95.1954	0.00362847	0.000954861
8	95.48	95.4199	95.3921	0.0277951	0.0601215
9	95.56	95.6102	95.5937	0.016441	-0.050191
10	95.75	95.8366	95.8058	0.030816	-0.0866493
11	95.91	95.9598	96.0254	-0.0656424	-0.0497743
12	96.16	96.0719	96.2512	-0.179392	0.0881424
13	96.32	96.2134	96.4738	-0.26033	0.10658
14	96.58	96.738	96.6933	0.0446701	-0.158003
15	97.08	97.1049	96.9171	0.187795	-0.0248785
16	97.22	97.275	97.1442	0.130816	-0.0549826
17	97.49	97.4149	97.3712	0.0436285	0.0751215
18	97.62	97.6094	97.5896	0.0197743	0.0106424
19	97.83	97.802	97.7983	0.00362847	0.0280382
20	98.12	98.0382	98.0104	0.0277951	0.0817882
21	98.29	98.2306	98.2142	0.016441	0.0593924
22	98.47	98.4371	98.4062	0.030816	0.032934
23	98.64	98.5223	98.5879	-0.0656424	0.117726
24	98.67	98.5831	98.7625	-0.179392	0.0868924
25	98.82	98.6826	98.9429	-0.26033	0.137413
26	99.17	99.1663	99.1217	0.0446701	0.00366319
27	99.38	99.4911	99.3033	0.187795	-0.111128
28	99.53	99.6312	99.5004	0.130816	-0.101233
29	99.54	99.7449	99.7012	0.0436285	-0.204878
30	99.76	99.9189	99.8992	0.0197743	-0.158941
31	100.02	100.102	100.098	0.00362847	-0.0815451
32	100.22	100.34	100.312	0.0277951	-0.119878
33	100.55	100.564	100.547	0.016441	-0.0135243
34	100.94	100.821	100.79	0.030816	0.119184
35	100.99	100.974	101.04	-0.0656424	0.0156424
36	101.07	101.111	101.291	-0.179392	-0.041441
37	101.19	101.279	101.54	-0.26033	-0.0892535
38	101.94	101.833	101.788	0.0446701	0.107413
39	102.25	102.22	102.032	0.187795	0.0301215
40	102.49	102.395	102.264	0.130816	0.0950174
41	102.58	102.534	102.49	0.0436285	0.0459549
42	102.74	102.739	102.72	0.0197743	0.000642361
43	103.01	102.953	102.95	0.00362847	0.0567882
44	103.19	103.208	103.18	0.0277951	-0.0177951
45	103.44	103.431	103.415	0.016441	0.00855903
46	103.62	103.681	103.65	0.030816	-0.0612326
47	103.74	103.819	103.885	-0.0656424	-0.0793576
48	103.82	103.949	104.129	-0.179392	-0.129358
49	103.96	104.111	104.371	-0.26033	-0.150503
50	104.7	104.649	104.604	0.0446701	0.0511632
51	105.13	105.02	104.832	0.187795	0.110122
52	105.26	105.195	105.064	0.130816	0.065434
53	105.44	105.352	105.308	0.0436285	0.0880382
54	105.73	105.578	105.558	0.0197743	0.151892
55	105.83	NA	NA	0.00362847	NA
56	105.97	NA	NA	0.0277951	NA
57	106.13	NA	NA	0.016441	NA
58	106.49	NA	NA	0.030816	NA
59	106.74	NA	NA	-0.0656424	NA
60	106.82	NA	NA	-0.179392	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 93.91 & NA & NA & -0.26033 & NA \tabularnewline
2 & 94.27 & NA & NA & 0.0446701 & NA \tabularnewline
3 & 94.55 & NA & NA & 0.187795 & NA \tabularnewline
4 & 94.66 & NA & NA & 0.130816 & NA \tabularnewline
5 & 94.78 & NA & NA & 0.0436285 & NA \tabularnewline
6 & 94.91 & NA & NA & 0.0197743 & NA \tabularnewline
7 & 95.2 & 95.199 & 95.1954 & 0.00362847 & 0.000954861 \tabularnewline
8 & 95.48 & 95.4199 & 95.3921 & 0.0277951 & 0.0601215 \tabularnewline
9 & 95.56 & 95.6102 & 95.5937 & 0.016441 & -0.050191 \tabularnewline
10 & 95.75 & 95.8366 & 95.8058 & 0.030816 & -0.0866493 \tabularnewline
11 & 95.91 & 95.9598 & 96.0254 & -0.0656424 & -0.0497743 \tabularnewline
12 & 96.16 & 96.0719 & 96.2512 & -0.179392 & 0.0881424 \tabularnewline
13 & 96.32 & 96.2134 & 96.4738 & -0.26033 & 0.10658 \tabularnewline
14 & 96.58 & 96.738 & 96.6933 & 0.0446701 & -0.158003 \tabularnewline
15 & 97.08 & 97.1049 & 96.9171 & 0.187795 & -0.0248785 \tabularnewline
16 & 97.22 & 97.275 & 97.1442 & 0.130816 & -0.0549826 \tabularnewline
17 & 97.49 & 97.4149 & 97.3712 & 0.0436285 & 0.0751215 \tabularnewline
18 & 97.62 & 97.6094 & 97.5896 & 0.0197743 & 0.0106424 \tabularnewline
19 & 97.83 & 97.802 & 97.7983 & 0.00362847 & 0.0280382 \tabularnewline
20 & 98.12 & 98.0382 & 98.0104 & 0.0277951 & 0.0817882 \tabularnewline
21 & 98.29 & 98.2306 & 98.2142 & 0.016441 & 0.0593924 \tabularnewline
22 & 98.47 & 98.4371 & 98.4062 & 0.030816 & 0.032934 \tabularnewline
23 & 98.64 & 98.5223 & 98.5879 & -0.0656424 & 0.117726 \tabularnewline
24 & 98.67 & 98.5831 & 98.7625 & -0.179392 & 0.0868924 \tabularnewline
25 & 98.82 & 98.6826 & 98.9429 & -0.26033 & 0.137413 \tabularnewline
26 & 99.17 & 99.1663 & 99.1217 & 0.0446701 & 0.00366319 \tabularnewline
27 & 99.38 & 99.4911 & 99.3033 & 0.187795 & -0.111128 \tabularnewline
28 & 99.53 & 99.6312 & 99.5004 & 0.130816 & -0.101233 \tabularnewline
29 & 99.54 & 99.7449 & 99.7012 & 0.0436285 & -0.204878 \tabularnewline
30 & 99.76 & 99.9189 & 99.8992 & 0.0197743 & -0.158941 \tabularnewline
31 & 100.02 & 100.102 & 100.098 & 0.00362847 & -0.0815451 \tabularnewline
32 & 100.22 & 100.34 & 100.312 & 0.0277951 & -0.119878 \tabularnewline
33 & 100.55 & 100.564 & 100.547 & 0.016441 & -0.0135243 \tabularnewline
34 & 100.94 & 100.821 & 100.79 & 0.030816 & 0.119184 \tabularnewline
35 & 100.99 & 100.974 & 101.04 & -0.0656424 & 0.0156424 \tabularnewline
36 & 101.07 & 101.111 & 101.291 & -0.179392 & -0.041441 \tabularnewline
37 & 101.19 & 101.279 & 101.54 & -0.26033 & -0.0892535 \tabularnewline
38 & 101.94 & 101.833 & 101.788 & 0.0446701 & 0.107413 \tabularnewline
39 & 102.25 & 102.22 & 102.032 & 0.187795 & 0.0301215 \tabularnewline
40 & 102.49 & 102.395 & 102.264 & 0.130816 & 0.0950174 \tabularnewline
41 & 102.58 & 102.534 & 102.49 & 0.0436285 & 0.0459549 \tabularnewline
42 & 102.74 & 102.739 & 102.72 & 0.0197743 & 0.000642361 \tabularnewline
43 & 103.01 & 102.953 & 102.95 & 0.00362847 & 0.0567882 \tabularnewline
44 & 103.19 & 103.208 & 103.18 & 0.0277951 & -0.0177951 \tabularnewline
45 & 103.44 & 103.431 & 103.415 & 0.016441 & 0.00855903 \tabularnewline
46 & 103.62 & 103.681 & 103.65 & 0.030816 & -0.0612326 \tabularnewline
47 & 103.74 & 103.819 & 103.885 & -0.0656424 & -0.0793576 \tabularnewline
48 & 103.82 & 103.949 & 104.129 & -0.179392 & -0.129358 \tabularnewline
49 & 103.96 & 104.111 & 104.371 & -0.26033 & -0.150503 \tabularnewline
50 & 104.7 & 104.649 & 104.604 & 0.0446701 & 0.0511632 \tabularnewline
51 & 105.13 & 105.02 & 104.832 & 0.187795 & 0.110122 \tabularnewline
52 & 105.26 & 105.195 & 105.064 & 0.130816 & 0.065434 \tabularnewline
53 & 105.44 & 105.352 & 105.308 & 0.0436285 & 0.0880382 \tabularnewline
54 & 105.73 & 105.578 & 105.558 & 0.0197743 & 0.151892 \tabularnewline
55 & 105.83 & NA & NA & 0.00362847 & NA \tabularnewline
56 & 105.97 & NA & NA & 0.0277951 & NA \tabularnewline
57 & 106.13 & NA & NA & 0.016441 & NA \tabularnewline
58 & 106.49 & NA & NA & 0.030816 & NA \tabularnewline
59 & 106.74 & NA & NA & -0.0656424 & NA \tabularnewline
60 & 106.82 & NA & NA & -0.179392 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294920&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]93.91[/C][C]NA[/C][C]NA[/C][C]-0.26033[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]94.27[/C][C]NA[/C][C]NA[/C][C]0.0446701[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]94.55[/C][C]NA[/C][C]NA[/C][C]0.187795[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]94.66[/C][C]NA[/C][C]NA[/C][C]0.130816[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]94.78[/C][C]NA[/C][C]NA[/C][C]0.0436285[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]94.91[/C][C]NA[/C][C]NA[/C][C]0.0197743[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]95.2[/C][C]95.199[/C][C]95.1954[/C][C]0.00362847[/C][C]0.000954861[/C][/ROW]
[ROW][C]8[/C][C]95.48[/C][C]95.4199[/C][C]95.3921[/C][C]0.0277951[/C][C]0.0601215[/C][/ROW]
[ROW][C]9[/C][C]95.56[/C][C]95.6102[/C][C]95.5937[/C][C]0.016441[/C][C]-0.050191[/C][/ROW]
[ROW][C]10[/C][C]95.75[/C][C]95.8366[/C][C]95.8058[/C][C]0.030816[/C][C]-0.0866493[/C][/ROW]
[ROW][C]11[/C][C]95.91[/C][C]95.9598[/C][C]96.0254[/C][C]-0.0656424[/C][C]-0.0497743[/C][/ROW]
[ROW][C]12[/C][C]96.16[/C][C]96.0719[/C][C]96.2512[/C][C]-0.179392[/C][C]0.0881424[/C][/ROW]
[ROW][C]13[/C][C]96.32[/C][C]96.2134[/C][C]96.4738[/C][C]-0.26033[/C][C]0.10658[/C][/ROW]
[ROW][C]14[/C][C]96.58[/C][C]96.738[/C][C]96.6933[/C][C]0.0446701[/C][C]-0.158003[/C][/ROW]
[ROW][C]15[/C][C]97.08[/C][C]97.1049[/C][C]96.9171[/C][C]0.187795[/C][C]-0.0248785[/C][/ROW]
[ROW][C]16[/C][C]97.22[/C][C]97.275[/C][C]97.1442[/C][C]0.130816[/C][C]-0.0549826[/C][/ROW]
[ROW][C]17[/C][C]97.49[/C][C]97.4149[/C][C]97.3712[/C][C]0.0436285[/C][C]0.0751215[/C][/ROW]
[ROW][C]18[/C][C]97.62[/C][C]97.6094[/C][C]97.5896[/C][C]0.0197743[/C][C]0.0106424[/C][/ROW]
[ROW][C]19[/C][C]97.83[/C][C]97.802[/C][C]97.7983[/C][C]0.00362847[/C][C]0.0280382[/C][/ROW]
[ROW][C]20[/C][C]98.12[/C][C]98.0382[/C][C]98.0104[/C][C]0.0277951[/C][C]0.0817882[/C][/ROW]
[ROW][C]21[/C][C]98.29[/C][C]98.2306[/C][C]98.2142[/C][C]0.016441[/C][C]0.0593924[/C][/ROW]
[ROW][C]22[/C][C]98.47[/C][C]98.4371[/C][C]98.4062[/C][C]0.030816[/C][C]0.032934[/C][/ROW]
[ROW][C]23[/C][C]98.64[/C][C]98.5223[/C][C]98.5879[/C][C]-0.0656424[/C][C]0.117726[/C][/ROW]
[ROW][C]24[/C][C]98.67[/C][C]98.5831[/C][C]98.7625[/C][C]-0.179392[/C][C]0.0868924[/C][/ROW]
[ROW][C]25[/C][C]98.82[/C][C]98.6826[/C][C]98.9429[/C][C]-0.26033[/C][C]0.137413[/C][/ROW]
[ROW][C]26[/C][C]99.17[/C][C]99.1663[/C][C]99.1217[/C][C]0.0446701[/C][C]0.00366319[/C][/ROW]
[ROW][C]27[/C][C]99.38[/C][C]99.4911[/C][C]99.3033[/C][C]0.187795[/C][C]-0.111128[/C][/ROW]
[ROW][C]28[/C][C]99.53[/C][C]99.6312[/C][C]99.5004[/C][C]0.130816[/C][C]-0.101233[/C][/ROW]
[ROW][C]29[/C][C]99.54[/C][C]99.7449[/C][C]99.7012[/C][C]0.0436285[/C][C]-0.204878[/C][/ROW]
[ROW][C]30[/C][C]99.76[/C][C]99.9189[/C][C]99.8992[/C][C]0.0197743[/C][C]-0.158941[/C][/ROW]
[ROW][C]31[/C][C]100.02[/C][C]100.102[/C][C]100.098[/C][C]0.00362847[/C][C]-0.0815451[/C][/ROW]
[ROW][C]32[/C][C]100.22[/C][C]100.34[/C][C]100.312[/C][C]0.0277951[/C][C]-0.119878[/C][/ROW]
[ROW][C]33[/C][C]100.55[/C][C]100.564[/C][C]100.547[/C][C]0.016441[/C][C]-0.0135243[/C][/ROW]
[ROW][C]34[/C][C]100.94[/C][C]100.821[/C][C]100.79[/C][C]0.030816[/C][C]0.119184[/C][/ROW]
[ROW][C]35[/C][C]100.99[/C][C]100.974[/C][C]101.04[/C][C]-0.0656424[/C][C]0.0156424[/C][/ROW]
[ROW][C]36[/C][C]101.07[/C][C]101.111[/C][C]101.291[/C][C]-0.179392[/C][C]-0.041441[/C][/ROW]
[ROW][C]37[/C][C]101.19[/C][C]101.279[/C][C]101.54[/C][C]-0.26033[/C][C]-0.0892535[/C][/ROW]
[ROW][C]38[/C][C]101.94[/C][C]101.833[/C][C]101.788[/C][C]0.0446701[/C][C]0.107413[/C][/ROW]
[ROW][C]39[/C][C]102.25[/C][C]102.22[/C][C]102.032[/C][C]0.187795[/C][C]0.0301215[/C][/ROW]
[ROW][C]40[/C][C]102.49[/C][C]102.395[/C][C]102.264[/C][C]0.130816[/C][C]0.0950174[/C][/ROW]
[ROW][C]41[/C][C]102.58[/C][C]102.534[/C][C]102.49[/C][C]0.0436285[/C][C]0.0459549[/C][/ROW]
[ROW][C]42[/C][C]102.74[/C][C]102.739[/C][C]102.72[/C][C]0.0197743[/C][C]0.000642361[/C][/ROW]
[ROW][C]43[/C][C]103.01[/C][C]102.953[/C][C]102.95[/C][C]0.00362847[/C][C]0.0567882[/C][/ROW]
[ROW][C]44[/C][C]103.19[/C][C]103.208[/C][C]103.18[/C][C]0.0277951[/C][C]-0.0177951[/C][/ROW]
[ROW][C]45[/C][C]103.44[/C][C]103.431[/C][C]103.415[/C][C]0.016441[/C][C]0.00855903[/C][/ROW]
[ROW][C]46[/C][C]103.62[/C][C]103.681[/C][C]103.65[/C][C]0.030816[/C][C]-0.0612326[/C][/ROW]
[ROW][C]47[/C][C]103.74[/C][C]103.819[/C][C]103.885[/C][C]-0.0656424[/C][C]-0.0793576[/C][/ROW]
[ROW][C]48[/C][C]103.82[/C][C]103.949[/C][C]104.129[/C][C]-0.179392[/C][C]-0.129358[/C][/ROW]
[ROW][C]49[/C][C]103.96[/C][C]104.111[/C][C]104.371[/C][C]-0.26033[/C][C]-0.150503[/C][/ROW]
[ROW][C]50[/C][C]104.7[/C][C]104.649[/C][C]104.604[/C][C]0.0446701[/C][C]0.0511632[/C][/ROW]
[ROW][C]51[/C][C]105.13[/C][C]105.02[/C][C]104.832[/C][C]0.187795[/C][C]0.110122[/C][/ROW]
[ROW][C]52[/C][C]105.26[/C][C]105.195[/C][C]105.064[/C][C]0.130816[/C][C]0.065434[/C][/ROW]
[ROW][C]53[/C][C]105.44[/C][C]105.352[/C][C]105.308[/C][C]0.0436285[/C][C]0.0880382[/C][/ROW]
[ROW][C]54[/C][C]105.73[/C][C]105.578[/C][C]105.558[/C][C]0.0197743[/C][C]0.151892[/C][/ROW]
[ROW][C]55[/C][C]105.83[/C][C]NA[/C][C]NA[/C][C]0.00362847[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]105.97[/C][C]NA[/C][C]NA[/C][C]0.0277951[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]106.13[/C][C]NA[/C][C]NA[/C][C]0.016441[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]106.49[/C][C]NA[/C][C]NA[/C][C]0.030816[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]106.74[/C][C]NA[/C][C]NA[/C][C]-0.0656424[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]106.82[/C][C]NA[/C][C]NA[/C][C]-0.179392[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294920&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294920&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	93.91	NA	NA	-0.26033	NA
2	94.27	NA	NA	0.0446701	NA
3	94.55	NA	NA	0.187795	NA
4	94.66	NA	NA	0.130816	NA
5	94.78	NA	NA	0.0436285	NA
6	94.91	NA	NA	0.0197743	NA
7	95.2	95.199	95.1954	0.00362847	0.000954861
8	95.48	95.4199	95.3921	0.0277951	0.0601215
9	95.56	95.6102	95.5937	0.016441	-0.050191
10	95.75	95.8366	95.8058	0.030816	-0.0866493
11	95.91	95.9598	96.0254	-0.0656424	-0.0497743
12	96.16	96.0719	96.2512	-0.179392	0.0881424
13	96.32	96.2134	96.4738	-0.26033	0.10658
14	96.58	96.738	96.6933	0.0446701	-0.158003
15	97.08	97.1049	96.9171	0.187795	-0.0248785
16	97.22	97.275	97.1442	0.130816	-0.0549826
17	97.49	97.4149	97.3712	0.0436285	0.0751215
18	97.62	97.6094	97.5896	0.0197743	0.0106424
19	97.83	97.802	97.7983	0.00362847	0.0280382
20	98.12	98.0382	98.0104	0.0277951	0.0817882
21	98.29	98.2306	98.2142	0.016441	0.0593924
22	98.47	98.4371	98.4062	0.030816	0.032934
23	98.64	98.5223	98.5879	-0.0656424	0.117726
24	98.67	98.5831	98.7625	-0.179392	0.0868924
25	98.82	98.6826	98.9429	-0.26033	0.137413
26	99.17	99.1663	99.1217	0.0446701	0.00366319
27	99.38	99.4911	99.3033	0.187795	-0.111128
28	99.53	99.6312	99.5004	0.130816	-0.101233
29	99.54	99.7449	99.7012	0.0436285	-0.204878
30	99.76	99.9189	99.8992	0.0197743	-0.158941
31	100.02	100.102	100.098	0.00362847	-0.0815451
32	100.22	100.34	100.312	0.0277951	-0.119878
33	100.55	100.564	100.547	0.016441	-0.0135243
34	100.94	100.821	100.79	0.030816	0.119184
35	100.99	100.974	101.04	-0.0656424	0.0156424
36	101.07	101.111	101.291	-0.179392	-0.041441
37	101.19	101.279	101.54	-0.26033	-0.0892535
38	101.94	101.833	101.788	0.0446701	0.107413
39	102.25	102.22	102.032	0.187795	0.0301215
40	102.49	102.395	102.264	0.130816	0.0950174
41	102.58	102.534	102.49	0.0436285	0.0459549
42	102.74	102.739	102.72	0.0197743	0.000642361
43	103.01	102.953	102.95	0.00362847	0.0567882
44	103.19	103.208	103.18	0.0277951	-0.0177951
45	103.44	103.431	103.415	0.016441	0.00855903
46	103.62	103.681	103.65	0.030816	-0.0612326
47	103.74	103.819	103.885	-0.0656424	-0.0793576
48	103.82	103.949	104.129	-0.179392	-0.129358
49	103.96	104.111	104.371	-0.26033	-0.150503
50	104.7	104.649	104.604	0.0446701	0.0511632
51	105.13	105.02	104.832	0.187795	0.110122
52	105.26	105.195	105.064	0.130816	0.065434
53	105.44	105.352	105.308	0.0436285	0.0880382
54	105.73	105.578	105.558	0.0197743	0.151892
55	105.83	NA	NA	0.00362847	NA
56	105.97	NA	NA	0.0277951	NA
57	106.13	NA	NA	0.016441	NA
58	106.49	NA	NA	0.030816	NA
59	106.74	NA	NA	-0.0656424	NA
60	106.82	NA	NA	-0.179392	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