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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Tue, 20 May 2014 16:20:20 -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/20/t1400617324s6azvx4brf7gypz.htm/, Retrieved Thu, 16 May 2024 01:02:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235000, Retrieved Thu, 16 May 2024 01:02:29 +0000

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-       [Classical Decomposition] [] [2014-05-20 20:20:20] [96d7fff632246663047c645f81fe87bb] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235000&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235000&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235000&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.005	NA	NA	-0.0253153	NA
2	1.026	NA	NA	-0.0201819	NA
3	1.043	NA	NA	0.00675139	NA
4	1.068	NA	NA	0.0195681	NA
5	1.07	NA	NA	0.0268264	NA
6	1.091	NA	NA	0.0267264	NA
7	1.102	1.13789	1.10471	0.0331847	-0.0358931
8	1.091	1.12543	1.11971	0.00571806	-0.0344264
9	1.121	1.13522	1.13675	-0.00153194	-0.0142181
10	1.134	1.13826	1.15588	-0.0176153	-0.00425972
11	1.225	1.16807	1.17971	-0.0116403	0.0569319
12	1.191	1.16584	1.20833	-0.0424903	0.0251569
13	1.184	1.21243	1.23775	-0.0253153	-0.0284347
14	1.207	1.24378	1.26396	-0.0201819	-0.0367764
15	1.271	1.29063	1.28388	0.00675139	-0.0196264
16	1.299	1.31632	1.29675	0.0195681	-0.0173181
17	1.411	1.32428	1.29746	0.0268264	0.0867153
18	1.437	1.31348	1.28675	0.0267264	0.123524
19	1.462	1.30568	1.2725	0.0331847	0.156315
20	1.36	1.26313	1.25742	0.00571806	0.0968653
21	1.33	1.23651	1.23804	-0.00153194	0.0934903
22	1.234	1.19743	1.21504	-0.0176153	0.0365736
23	1.142	1.17557	1.18721	-0.0116403	-0.0335681
24	1.017	1.11351	1.156	-0.0424903	-0.0965097
25	1.016	1.09864	1.12396	-0.0253153	-0.0826431
26	1.013	1.07561	1.09579	-0.0201819	-0.0626097
27	1	1.08017	1.07342	0.00675139	-0.0801681
28	1.018	1.07553	1.05596	0.0195681	-0.0575264
29	1.024	1.0747	1.04787	0.0268264	-0.0507014
30	1.075	1.07614	1.04942	0.0267264	-0.00114306
31	1.055	1.09102	1.05783	0.0331847	-0.0360181
32	1.091	1.07384	1.06812	0.00571806	0.0171569
33	1.062	1.07934	1.08088	-0.00153194	-0.0173431
34	1.083	1.07934	1.09696	-0.0176153	0.00365694
35	1.099	1.10244	1.11408	-0.0116403	-0.00344306
36	1.097	1.08672	1.12921	-0.0424903	0.0102819
37	1.138	1.11685	1.14217	-0.0253153	0.0211486
38	1.138	1.13332	1.1535	-0.0201819	0.00468194
39	1.181	1.17167	1.16492	0.00675139	0.00933194
40	1.223	1.1969	1.17733	0.0195681	0.0260986
41	1.23	1.21603	1.18921	0.0268264	0.0139653
42	1.232	1.2301	1.20337	0.0267264	0.00189861
43	1.209	1.25277	1.21958	0.0331847	-0.0437681
44	1.209	1.24243	1.23671	0.00571806	-0.0334264
45	1.218	1.25372	1.25525	-0.00153194	-0.0357181
46	1.225	1.25526	1.27288	-0.0176153	-0.0302597
47	1.242	1.27594	1.28758	-0.0116403	-0.0339431
48	1.294	1.25763	1.30012	-0.0424903	0.0363653
49	1.33	1.28852	1.31383	-0.0253153	0.0414819
50	1.357	1.30807	1.32825	-0.0201819	0.0489319
51	1.407	1.34904	1.34229	0.00675139	0.0579569
52	1.42	1.37665	1.35708	0.0195681	0.0433486
53	1.386	1.39958	1.37275	0.0268264	-0.0135764
54	1.377	1.41306	1.38633	0.0267264	-0.0360597
55	1.393	1.43077	1.39758	0.0331847	-0.0377681
56	1.371	1.4143	1.40858	0.00571806	-0.0433014
57	1.393	1.41634	1.41787	-0.00153194	-0.0233431
58	1.405	1.40784	1.42546	-0.0176153	-0.00284306
59	1.438	1.42111	1.43275	-0.0116403	0.0168903
60	1.424	1.39643	1.43892	-0.0424903	0.0275736
61	1.47	1.41868	1.444	-0.0253153	0.0513153
62	1.481	1.43236	1.45254	-0.0201819	0.0486403
63	1.506	1.47063	1.46388	0.00675139	0.0353736
64	1.503	1.49473	1.47517	0.0195681	0.00826528
65	1.478	1.51153	1.48471	0.0268264	-0.0335347
66	1.433	1.51835	1.49162	0.0267264	-0.0853514
67	1.459	NA	NA	0.0331847	NA
68	1.51	NA	NA	0.00571806	NA
69	1.526	NA	NA	-0.00153194	NA
70	1.543	NA	NA	-0.0176153	NA
71	1.529	NA	NA	-0.0116403	NA
72	1.499	NA	NA	-0.0424903	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.005 & NA & NA & -0.0253153 & NA \tabularnewline
2 & 1.026 & NA & NA & -0.0201819 & NA \tabularnewline
3 & 1.043 & NA & NA & 0.00675139 & NA \tabularnewline
4 & 1.068 & NA & NA & 0.0195681 & NA \tabularnewline
5 & 1.07 & NA & NA & 0.0268264 & NA \tabularnewline
6 & 1.091 & NA & NA & 0.0267264 & NA \tabularnewline
7 & 1.102 & 1.13789 & 1.10471 & 0.0331847 & -0.0358931 \tabularnewline
8 & 1.091 & 1.12543 & 1.11971 & 0.00571806 & -0.0344264 \tabularnewline
9 & 1.121 & 1.13522 & 1.13675 & -0.00153194 & -0.0142181 \tabularnewline
10 & 1.134 & 1.13826 & 1.15588 & -0.0176153 & -0.00425972 \tabularnewline
11 & 1.225 & 1.16807 & 1.17971 & -0.0116403 & 0.0569319 \tabularnewline
12 & 1.191 & 1.16584 & 1.20833 & -0.0424903 & 0.0251569 \tabularnewline
13 & 1.184 & 1.21243 & 1.23775 & -0.0253153 & -0.0284347 \tabularnewline
14 & 1.207 & 1.24378 & 1.26396 & -0.0201819 & -0.0367764 \tabularnewline
15 & 1.271 & 1.29063 & 1.28388 & 0.00675139 & -0.0196264 \tabularnewline
16 & 1.299 & 1.31632 & 1.29675 & 0.0195681 & -0.0173181 \tabularnewline
17 & 1.411 & 1.32428 & 1.29746 & 0.0268264 & 0.0867153 \tabularnewline
18 & 1.437 & 1.31348 & 1.28675 & 0.0267264 & 0.123524 \tabularnewline
19 & 1.462 & 1.30568 & 1.2725 & 0.0331847 & 0.156315 \tabularnewline
20 & 1.36 & 1.26313 & 1.25742 & 0.00571806 & 0.0968653 \tabularnewline
21 & 1.33 & 1.23651 & 1.23804 & -0.00153194 & 0.0934903 \tabularnewline
22 & 1.234 & 1.19743 & 1.21504 & -0.0176153 & 0.0365736 \tabularnewline
23 & 1.142 & 1.17557 & 1.18721 & -0.0116403 & -0.0335681 \tabularnewline
24 & 1.017 & 1.11351 & 1.156 & -0.0424903 & -0.0965097 \tabularnewline
25 & 1.016 & 1.09864 & 1.12396 & -0.0253153 & -0.0826431 \tabularnewline
26 & 1.013 & 1.07561 & 1.09579 & -0.0201819 & -0.0626097 \tabularnewline
27 & 1 & 1.08017 & 1.07342 & 0.00675139 & -0.0801681 \tabularnewline
28 & 1.018 & 1.07553 & 1.05596 & 0.0195681 & -0.0575264 \tabularnewline
29 & 1.024 & 1.0747 & 1.04787 & 0.0268264 & -0.0507014 \tabularnewline
30 & 1.075 & 1.07614 & 1.04942 & 0.0267264 & -0.00114306 \tabularnewline
31 & 1.055 & 1.09102 & 1.05783 & 0.0331847 & -0.0360181 \tabularnewline
32 & 1.091 & 1.07384 & 1.06812 & 0.00571806 & 0.0171569 \tabularnewline
33 & 1.062 & 1.07934 & 1.08088 & -0.00153194 & -0.0173431 \tabularnewline
34 & 1.083 & 1.07934 & 1.09696 & -0.0176153 & 0.00365694 \tabularnewline
35 & 1.099 & 1.10244 & 1.11408 & -0.0116403 & -0.00344306 \tabularnewline
36 & 1.097 & 1.08672 & 1.12921 & -0.0424903 & 0.0102819 \tabularnewline
37 & 1.138 & 1.11685 & 1.14217 & -0.0253153 & 0.0211486 \tabularnewline
38 & 1.138 & 1.13332 & 1.1535 & -0.0201819 & 0.00468194 \tabularnewline
39 & 1.181 & 1.17167 & 1.16492 & 0.00675139 & 0.00933194 \tabularnewline
40 & 1.223 & 1.1969 & 1.17733 & 0.0195681 & 0.0260986 \tabularnewline
41 & 1.23 & 1.21603 & 1.18921 & 0.0268264 & 0.0139653 \tabularnewline
42 & 1.232 & 1.2301 & 1.20337 & 0.0267264 & 0.00189861 \tabularnewline
43 & 1.209 & 1.25277 & 1.21958 & 0.0331847 & -0.0437681 \tabularnewline
44 & 1.209 & 1.24243 & 1.23671 & 0.00571806 & -0.0334264 \tabularnewline
45 & 1.218 & 1.25372 & 1.25525 & -0.00153194 & -0.0357181 \tabularnewline
46 & 1.225 & 1.25526 & 1.27288 & -0.0176153 & -0.0302597 \tabularnewline
47 & 1.242 & 1.27594 & 1.28758 & -0.0116403 & -0.0339431 \tabularnewline
48 & 1.294 & 1.25763 & 1.30012 & -0.0424903 & 0.0363653 \tabularnewline
49 & 1.33 & 1.28852 & 1.31383 & -0.0253153 & 0.0414819 \tabularnewline
50 & 1.357 & 1.30807 & 1.32825 & -0.0201819 & 0.0489319 \tabularnewline
51 & 1.407 & 1.34904 & 1.34229 & 0.00675139 & 0.0579569 \tabularnewline
52 & 1.42 & 1.37665 & 1.35708 & 0.0195681 & 0.0433486 \tabularnewline
53 & 1.386 & 1.39958 & 1.37275 & 0.0268264 & -0.0135764 \tabularnewline
54 & 1.377 & 1.41306 & 1.38633 & 0.0267264 & -0.0360597 \tabularnewline
55 & 1.393 & 1.43077 & 1.39758 & 0.0331847 & -0.0377681 \tabularnewline
56 & 1.371 & 1.4143 & 1.40858 & 0.00571806 & -0.0433014 \tabularnewline
57 & 1.393 & 1.41634 & 1.41787 & -0.00153194 & -0.0233431 \tabularnewline
58 & 1.405 & 1.40784 & 1.42546 & -0.0176153 & -0.00284306 \tabularnewline
59 & 1.438 & 1.42111 & 1.43275 & -0.0116403 & 0.0168903 \tabularnewline
60 & 1.424 & 1.39643 & 1.43892 & -0.0424903 & 0.0275736 \tabularnewline
61 & 1.47 & 1.41868 & 1.444 & -0.0253153 & 0.0513153 \tabularnewline
62 & 1.481 & 1.43236 & 1.45254 & -0.0201819 & 0.0486403 \tabularnewline
63 & 1.506 & 1.47063 & 1.46388 & 0.00675139 & 0.0353736 \tabularnewline
64 & 1.503 & 1.49473 & 1.47517 & 0.0195681 & 0.00826528 \tabularnewline
65 & 1.478 & 1.51153 & 1.48471 & 0.0268264 & -0.0335347 \tabularnewline
66 & 1.433 & 1.51835 & 1.49162 & 0.0267264 & -0.0853514 \tabularnewline
67 & 1.459 & NA & NA & 0.0331847 & NA \tabularnewline
68 & 1.51 & NA & NA & 0.00571806 & NA \tabularnewline
69 & 1.526 & NA & NA & -0.00153194 & NA \tabularnewline
70 & 1.543 & NA & NA & -0.0176153 & NA \tabularnewline
71 & 1.529 & NA & NA & -0.0116403 & NA \tabularnewline
72 & 1.499 & NA & NA & -0.0424903 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235000&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]1.005[/C][C]NA[/C][C]NA[/C][C]-0.0253153[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.026[/C][C]NA[/C][C]NA[/C][C]-0.0201819[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.043[/C][C]NA[/C][C]NA[/C][C]0.00675139[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.068[/C][C]NA[/C][C]NA[/C][C]0.0195681[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.07[/C][C]NA[/C][C]NA[/C][C]0.0268264[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.091[/C][C]NA[/C][C]NA[/C][C]0.0267264[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.102[/C][C]1.13789[/C][C]1.10471[/C][C]0.0331847[/C][C]-0.0358931[/C][/ROW]
[ROW][C]8[/C][C]1.091[/C][C]1.12543[/C][C]1.11971[/C][C]0.00571806[/C][C]-0.0344264[/C][/ROW]
[ROW][C]9[/C][C]1.121[/C][C]1.13522[/C][C]1.13675[/C][C]-0.00153194[/C][C]-0.0142181[/C][/ROW]
[ROW][C]10[/C][C]1.134[/C][C]1.13826[/C][C]1.15588[/C][C]-0.0176153[/C][C]-0.00425972[/C][/ROW]
[ROW][C]11[/C][C]1.225[/C][C]1.16807[/C][C]1.17971[/C][C]-0.0116403[/C][C]0.0569319[/C][/ROW]
[ROW][C]12[/C][C]1.191[/C][C]1.16584[/C][C]1.20833[/C][C]-0.0424903[/C][C]0.0251569[/C][/ROW]
[ROW][C]13[/C][C]1.184[/C][C]1.21243[/C][C]1.23775[/C][C]-0.0253153[/C][C]-0.0284347[/C][/ROW]
[ROW][C]14[/C][C]1.207[/C][C]1.24378[/C][C]1.26396[/C][C]-0.0201819[/C][C]-0.0367764[/C][/ROW]
[ROW][C]15[/C][C]1.271[/C][C]1.29063[/C][C]1.28388[/C][C]0.00675139[/C][C]-0.0196264[/C][/ROW]
[ROW][C]16[/C][C]1.299[/C][C]1.31632[/C][C]1.29675[/C][C]0.0195681[/C][C]-0.0173181[/C][/ROW]
[ROW][C]17[/C][C]1.411[/C][C]1.32428[/C][C]1.29746[/C][C]0.0268264[/C][C]0.0867153[/C][/ROW]
[ROW][C]18[/C][C]1.437[/C][C]1.31348[/C][C]1.28675[/C][C]0.0267264[/C][C]0.123524[/C][/ROW]
[ROW][C]19[/C][C]1.462[/C][C]1.30568[/C][C]1.2725[/C][C]0.0331847[/C][C]0.156315[/C][/ROW]
[ROW][C]20[/C][C]1.36[/C][C]1.26313[/C][C]1.25742[/C][C]0.00571806[/C][C]0.0968653[/C][/ROW]
[ROW][C]21[/C][C]1.33[/C][C]1.23651[/C][C]1.23804[/C][C]-0.00153194[/C][C]0.0934903[/C][/ROW]
[ROW][C]22[/C][C]1.234[/C][C]1.19743[/C][C]1.21504[/C][C]-0.0176153[/C][C]0.0365736[/C][/ROW]
[ROW][C]23[/C][C]1.142[/C][C]1.17557[/C][C]1.18721[/C][C]-0.0116403[/C][C]-0.0335681[/C][/ROW]
[ROW][C]24[/C][C]1.017[/C][C]1.11351[/C][C]1.156[/C][C]-0.0424903[/C][C]-0.0965097[/C][/ROW]
[ROW][C]25[/C][C]1.016[/C][C]1.09864[/C][C]1.12396[/C][C]-0.0253153[/C][C]-0.0826431[/C][/ROW]
[ROW][C]26[/C][C]1.013[/C][C]1.07561[/C][C]1.09579[/C][C]-0.0201819[/C][C]-0.0626097[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]1.08017[/C][C]1.07342[/C][C]0.00675139[/C][C]-0.0801681[/C][/ROW]
[ROW][C]28[/C][C]1.018[/C][C]1.07553[/C][C]1.05596[/C][C]0.0195681[/C][C]-0.0575264[/C][/ROW]
[ROW][C]29[/C][C]1.024[/C][C]1.0747[/C][C]1.04787[/C][C]0.0268264[/C][C]-0.0507014[/C][/ROW]
[ROW][C]30[/C][C]1.075[/C][C]1.07614[/C][C]1.04942[/C][C]0.0267264[/C][C]-0.00114306[/C][/ROW]
[ROW][C]31[/C][C]1.055[/C][C]1.09102[/C][C]1.05783[/C][C]0.0331847[/C][C]-0.0360181[/C][/ROW]
[ROW][C]32[/C][C]1.091[/C][C]1.07384[/C][C]1.06812[/C][C]0.00571806[/C][C]0.0171569[/C][/ROW]
[ROW][C]33[/C][C]1.062[/C][C]1.07934[/C][C]1.08088[/C][C]-0.00153194[/C][C]-0.0173431[/C][/ROW]
[ROW][C]34[/C][C]1.083[/C][C]1.07934[/C][C]1.09696[/C][C]-0.0176153[/C][C]0.00365694[/C][/ROW]
[ROW][C]35[/C][C]1.099[/C][C]1.10244[/C][C]1.11408[/C][C]-0.0116403[/C][C]-0.00344306[/C][/ROW]
[ROW][C]36[/C][C]1.097[/C][C]1.08672[/C][C]1.12921[/C][C]-0.0424903[/C][C]0.0102819[/C][/ROW]
[ROW][C]37[/C][C]1.138[/C][C]1.11685[/C][C]1.14217[/C][C]-0.0253153[/C][C]0.0211486[/C][/ROW]
[ROW][C]38[/C][C]1.138[/C][C]1.13332[/C][C]1.1535[/C][C]-0.0201819[/C][C]0.00468194[/C][/ROW]
[ROW][C]39[/C][C]1.181[/C][C]1.17167[/C][C]1.16492[/C][C]0.00675139[/C][C]0.00933194[/C][/ROW]
[ROW][C]40[/C][C]1.223[/C][C]1.1969[/C][C]1.17733[/C][C]0.0195681[/C][C]0.0260986[/C][/ROW]
[ROW][C]41[/C][C]1.23[/C][C]1.21603[/C][C]1.18921[/C][C]0.0268264[/C][C]0.0139653[/C][/ROW]
[ROW][C]42[/C][C]1.232[/C][C]1.2301[/C][C]1.20337[/C][C]0.0267264[/C][C]0.00189861[/C][/ROW]
[ROW][C]43[/C][C]1.209[/C][C]1.25277[/C][C]1.21958[/C][C]0.0331847[/C][C]-0.0437681[/C][/ROW]
[ROW][C]44[/C][C]1.209[/C][C]1.24243[/C][C]1.23671[/C][C]0.00571806[/C][C]-0.0334264[/C][/ROW]
[ROW][C]45[/C][C]1.218[/C][C]1.25372[/C][C]1.25525[/C][C]-0.00153194[/C][C]-0.0357181[/C][/ROW]
[ROW][C]46[/C][C]1.225[/C][C]1.25526[/C][C]1.27288[/C][C]-0.0176153[/C][C]-0.0302597[/C][/ROW]
[ROW][C]47[/C][C]1.242[/C][C]1.27594[/C][C]1.28758[/C][C]-0.0116403[/C][C]-0.0339431[/C][/ROW]
[ROW][C]48[/C][C]1.294[/C][C]1.25763[/C][C]1.30012[/C][C]-0.0424903[/C][C]0.0363653[/C][/ROW]
[ROW][C]49[/C][C]1.33[/C][C]1.28852[/C][C]1.31383[/C][C]-0.0253153[/C][C]0.0414819[/C][/ROW]
[ROW][C]50[/C][C]1.357[/C][C]1.30807[/C][C]1.32825[/C][C]-0.0201819[/C][C]0.0489319[/C][/ROW]
[ROW][C]51[/C][C]1.407[/C][C]1.34904[/C][C]1.34229[/C][C]0.00675139[/C][C]0.0579569[/C][/ROW]
[ROW][C]52[/C][C]1.42[/C][C]1.37665[/C][C]1.35708[/C][C]0.0195681[/C][C]0.0433486[/C][/ROW]
[ROW][C]53[/C][C]1.386[/C][C]1.39958[/C][C]1.37275[/C][C]0.0268264[/C][C]-0.0135764[/C][/ROW]
[ROW][C]54[/C][C]1.377[/C][C]1.41306[/C][C]1.38633[/C][C]0.0267264[/C][C]-0.0360597[/C][/ROW]
[ROW][C]55[/C][C]1.393[/C][C]1.43077[/C][C]1.39758[/C][C]0.0331847[/C][C]-0.0377681[/C][/ROW]
[ROW][C]56[/C][C]1.371[/C][C]1.4143[/C][C]1.40858[/C][C]0.00571806[/C][C]-0.0433014[/C][/ROW]
[ROW][C]57[/C][C]1.393[/C][C]1.41634[/C][C]1.41787[/C][C]-0.00153194[/C][C]-0.0233431[/C][/ROW]
[ROW][C]58[/C][C]1.405[/C][C]1.40784[/C][C]1.42546[/C][C]-0.0176153[/C][C]-0.00284306[/C][/ROW]
[ROW][C]59[/C][C]1.438[/C][C]1.42111[/C][C]1.43275[/C][C]-0.0116403[/C][C]0.0168903[/C][/ROW]
[ROW][C]60[/C][C]1.424[/C][C]1.39643[/C][C]1.43892[/C][C]-0.0424903[/C][C]0.0275736[/C][/ROW]
[ROW][C]61[/C][C]1.47[/C][C]1.41868[/C][C]1.444[/C][C]-0.0253153[/C][C]0.0513153[/C][/ROW]
[ROW][C]62[/C][C]1.481[/C][C]1.43236[/C][C]1.45254[/C][C]-0.0201819[/C][C]0.0486403[/C][/ROW]
[ROW][C]63[/C][C]1.506[/C][C]1.47063[/C][C]1.46388[/C][C]0.00675139[/C][C]0.0353736[/C][/ROW]
[ROW][C]64[/C][C]1.503[/C][C]1.49473[/C][C]1.47517[/C][C]0.0195681[/C][C]0.00826528[/C][/ROW]
[ROW][C]65[/C][C]1.478[/C][C]1.51153[/C][C]1.48471[/C][C]0.0268264[/C][C]-0.0335347[/C][/ROW]
[ROW][C]66[/C][C]1.433[/C][C]1.51835[/C][C]1.49162[/C][C]0.0267264[/C][C]-0.0853514[/C][/ROW]
[ROW][C]67[/C][C]1.459[/C][C]NA[/C][C]NA[/C][C]0.0331847[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.51[/C][C]NA[/C][C]NA[/C][C]0.00571806[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.526[/C][C]NA[/C][C]NA[/C][C]-0.00153194[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.543[/C][C]NA[/C][C]NA[/C][C]-0.0176153[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.529[/C][C]NA[/C][C]NA[/C][C]-0.0116403[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.499[/C][C]NA[/C][C]NA[/C][C]-0.0424903[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235000&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235000&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	1.005	NA	NA	-0.0253153	NA
2	1.026	NA	NA	-0.0201819	NA
3	1.043	NA	NA	0.00675139	NA
4	1.068	NA	NA	0.0195681	NA
5	1.07	NA	NA	0.0268264	NA
6	1.091	NA	NA	0.0267264	NA
7	1.102	1.13789	1.10471	0.0331847	-0.0358931
8	1.091	1.12543	1.11971	0.00571806	-0.0344264
9	1.121	1.13522	1.13675	-0.00153194	-0.0142181
10	1.134	1.13826	1.15588	-0.0176153	-0.00425972
11	1.225	1.16807	1.17971	-0.0116403	0.0569319
12	1.191	1.16584	1.20833	-0.0424903	0.0251569
13	1.184	1.21243	1.23775	-0.0253153	-0.0284347
14	1.207	1.24378	1.26396	-0.0201819	-0.0367764
15	1.271	1.29063	1.28388	0.00675139	-0.0196264
16	1.299	1.31632	1.29675	0.0195681	-0.0173181
17	1.411	1.32428	1.29746	0.0268264	0.0867153
18	1.437	1.31348	1.28675	0.0267264	0.123524
19	1.462	1.30568	1.2725	0.0331847	0.156315
20	1.36	1.26313	1.25742	0.00571806	0.0968653
21	1.33	1.23651	1.23804	-0.00153194	0.0934903
22	1.234	1.19743	1.21504	-0.0176153	0.0365736
23	1.142	1.17557	1.18721	-0.0116403	-0.0335681
24	1.017	1.11351	1.156	-0.0424903	-0.0965097
25	1.016	1.09864	1.12396	-0.0253153	-0.0826431
26	1.013	1.07561	1.09579	-0.0201819	-0.0626097
27	1	1.08017	1.07342	0.00675139	-0.0801681
28	1.018	1.07553	1.05596	0.0195681	-0.0575264
29	1.024	1.0747	1.04787	0.0268264	-0.0507014
30	1.075	1.07614	1.04942	0.0267264	-0.00114306
31	1.055	1.09102	1.05783	0.0331847	-0.0360181
32	1.091	1.07384	1.06812	0.00571806	0.0171569
33	1.062	1.07934	1.08088	-0.00153194	-0.0173431
34	1.083	1.07934	1.09696	-0.0176153	0.00365694
35	1.099	1.10244	1.11408	-0.0116403	-0.00344306
36	1.097	1.08672	1.12921	-0.0424903	0.0102819
37	1.138	1.11685	1.14217	-0.0253153	0.0211486
38	1.138	1.13332	1.1535	-0.0201819	0.00468194
39	1.181	1.17167	1.16492	0.00675139	0.00933194
40	1.223	1.1969	1.17733	0.0195681	0.0260986
41	1.23	1.21603	1.18921	0.0268264	0.0139653
42	1.232	1.2301	1.20337	0.0267264	0.00189861
43	1.209	1.25277	1.21958	0.0331847	-0.0437681
44	1.209	1.24243	1.23671	0.00571806	-0.0334264
45	1.218	1.25372	1.25525	-0.00153194	-0.0357181
46	1.225	1.25526	1.27288	-0.0176153	-0.0302597
47	1.242	1.27594	1.28758	-0.0116403	-0.0339431
48	1.294	1.25763	1.30012	-0.0424903	0.0363653
49	1.33	1.28852	1.31383	-0.0253153	0.0414819
50	1.357	1.30807	1.32825	-0.0201819	0.0489319
51	1.407	1.34904	1.34229	0.00675139	0.0579569
52	1.42	1.37665	1.35708	0.0195681	0.0433486
53	1.386	1.39958	1.37275	0.0268264	-0.0135764
54	1.377	1.41306	1.38633	0.0267264	-0.0360597
55	1.393	1.43077	1.39758	0.0331847	-0.0377681
56	1.371	1.4143	1.40858	0.00571806	-0.0433014
57	1.393	1.41634	1.41787	-0.00153194	-0.0233431
58	1.405	1.40784	1.42546	-0.0176153	-0.00284306
59	1.438	1.42111	1.43275	-0.0116403	0.0168903
60	1.424	1.39643	1.43892	-0.0424903	0.0275736
61	1.47	1.41868	1.444	-0.0253153	0.0513153
62	1.481	1.43236	1.45254	-0.0201819	0.0486403
63	1.506	1.47063	1.46388	0.00675139	0.0353736
64	1.503	1.49473	1.47517	0.0195681	0.00826528
65	1.478	1.51153	1.48471	0.0268264	-0.0335347
66	1.433	1.51835	1.49162	0.0267264	-0.0853514
67	1.459	NA	NA	0.0331847	NA
68	1.51	NA	NA	0.00571806	NA
69	1.526	NA	NA	-0.00153194	NA
70	1.543	NA	NA	-0.0176153	NA
71	1.529	NA	NA	-0.0116403	NA
72	1.499	NA	NA	-0.0424903	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