Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 25 Apr 2016 21:12:09 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/25/t14616152684fmx6tyr92io36u.htm/, Retrieved Sun, 05 May 2024 23:46:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294783, Retrieved Sun, 05 May 2024 23:46:38 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-       [Classical Decomposition] [] [2016-04-25 20:12:09] [409a9d71664281dd1fd3bb0995266dd0] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

\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
R Framework error message & Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294783&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]
[ROW][C]R Framework error message[/C][C]Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294783&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294783&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
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	100.57	NA	NA	-0.134028	NA
2	100.27	NA	NA	-0.457111	NA
3	100.27	NA	NA	-0.386028	NA
4	100.18	NA	NA	-0.292444	NA
5	100.16	NA	NA	-0.165694	NA
6	100.18	NA	NA	-0.137194	NA
7	100.18	100.256	100.563	-0.306444	-0.0764722
8	100.59	100.612	100.61	0.00230556	-0.0223056
9	100.69	100.842	100.66	0.181722	-0.152139
10	101.06	101.203	100.728	0.475139	-0.143056
11	101.15	101.422	100.815	0.607222	-0.271806
12	101.16	101.523	100.91	0.612556	-0.362556
13	101.16	100.873	101.007	-0.134028	0.286944
14	100.81	100.645	101.102	-0.457111	0.165028
15	100.94	100.819	101.205	-0.386028	0.121028
16	101.13	101.028	101.321	-0.292444	0.101611
17	101.29	101.277	101.443	-0.165694	0.0127778
18	101.34	101.434	101.571	-0.137194	-0.0936389
19	101.35	101.395	101.701	-0.306444	-0.0448056
20	101.7	101.826	101.824	0.00230556	-0.126056
21	102.05	102.116	101.934	0.181722	-0.0658889
22	102.48	102.514	102.039	0.475139	-0.0343056
23	102.66	102.75	102.142	0.607222	-0.0897222
24	102.72	102.86	102.247	0.612556	-0.139639
25	102.73	102.219	102.353	-0.134028	0.511111
26	102.18	102.003	102.46	-0.457111	0.177111
27	102.22	102.175	102.561	-0.386028	0.0451944
28	102.37	102.358	102.651	-0.292444	0.0116111
29	102.53	102.571	102.737	-0.165694	-0.0413889
30	102.61	102.685	102.822	-0.137194	-0.0748889
31	102.62	102.426	102.732	-0.306444	0.193944
32	103	102.474	102.472	0.00230556	0.525611
33	103.17	102.397	102.215	0.181722	0.773278
34	103.52	102.436	101.961	0.475139	1.08361
35	103.69	102.321	101.714	0.607222	1.36903
36	103.73	102.081	101.468	0.612556	1.64911
37	99.57	101.093	101.227	-0.134028	-1.52347
38	99.09	100.534	100.991	-0.457111	-1.44414
39	99.14	100.373	100.759	-0.386028	-1.23314
40	99.36	100.244	100.536	-0.292444	-0.883806
41	99.6	100.154	100.32	-0.165694	-0.554306
42	99.65	99.9695	100.107	-0.137194	-0.319472
43	99.8	99.7619	100.068	-0.306444	0.0381111
44	100.15	100.223	100.22	0.00230556	-0.0727222
45	100.45	100.57	100.389	0.181722	-0.120472
46	100.89	101.021	100.546	0.475139	-0.131389
47	101.13	101.293	100.686	0.607222	-0.163056
48	101.17	101.428	100.815	0.612556	-0.257556
49	101.21	100.79	100.924	-0.134028	0.419861
50	101.1	100.553	101.01	-0.457111	0.546694
51	101.17	100.696	101.082	-0.386028	0.473944
52	101.11	100.837	101.129	-0.292444	0.273278
53	101.2	100.989	101.155	-0.165694	0.210694
54	101.15	101.039	101.177	-0.137194	0.110528
55	100.92	100.912	101.218	-0.306444	0.00811111
56	101.1	101.286	101.283	0.00230556	-0.185639
57	101.22	101.536	101.354	0.181722	-0.315889
58	101.25	101.906	101.431	0.475139	-0.655972
59	101.39	102.116	101.508	0.607222	-0.725556
60	101.43	102.2	101.588	0.612556	-0.770472
61	101.95	101.526	101.66	-0.134028	0.424444
62	101.92	101.246	101.703	-0.457111	0.674194
63	102.05	101.338	101.724	-0.386028	0.711861
64	102.07	101.454	101.746	-0.292444	0.616194
65	102.1	101.609	101.775	-0.165694	0.491111
66	102.16	101.664	101.801	-0.137194	0.496361
67	101.63	NA	NA	-0.306444	NA
68	101.43	NA	NA	0.00230556	NA
69	101.4	NA	NA	0.181722	NA
70	101.6	NA	NA	0.475139	NA
71	101.72	NA	NA	0.607222	NA
72	101.73	NA	NA	0.612556	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 100.57 & NA & NA & -0.134028 & NA \tabularnewline
2 & 100.27 & NA & NA & -0.457111 & NA \tabularnewline
3 & 100.27 & NA & NA & -0.386028 & NA \tabularnewline
4 & 100.18 & NA & NA & -0.292444 & NA \tabularnewline
5 & 100.16 & NA & NA & -0.165694 & NA \tabularnewline
6 & 100.18 & NA & NA & -0.137194 & NA \tabularnewline
7 & 100.18 & 100.256 & 100.563 & -0.306444 & -0.0764722 \tabularnewline
8 & 100.59 & 100.612 & 100.61 & 0.00230556 & -0.0223056 \tabularnewline
9 & 100.69 & 100.842 & 100.66 & 0.181722 & -0.152139 \tabularnewline
10 & 101.06 & 101.203 & 100.728 & 0.475139 & -0.143056 \tabularnewline
11 & 101.15 & 101.422 & 100.815 & 0.607222 & -0.271806 \tabularnewline
12 & 101.16 & 101.523 & 100.91 & 0.612556 & -0.362556 \tabularnewline
13 & 101.16 & 100.873 & 101.007 & -0.134028 & 0.286944 \tabularnewline
14 & 100.81 & 100.645 & 101.102 & -0.457111 & 0.165028 \tabularnewline
15 & 100.94 & 100.819 & 101.205 & -0.386028 & 0.121028 \tabularnewline
16 & 101.13 & 101.028 & 101.321 & -0.292444 & 0.101611 \tabularnewline
17 & 101.29 & 101.277 & 101.443 & -0.165694 & 0.0127778 \tabularnewline
18 & 101.34 & 101.434 & 101.571 & -0.137194 & -0.0936389 \tabularnewline
19 & 101.35 & 101.395 & 101.701 & -0.306444 & -0.0448056 \tabularnewline
20 & 101.7 & 101.826 & 101.824 & 0.00230556 & -0.126056 \tabularnewline
21 & 102.05 & 102.116 & 101.934 & 0.181722 & -0.0658889 \tabularnewline
22 & 102.48 & 102.514 & 102.039 & 0.475139 & -0.0343056 \tabularnewline
23 & 102.66 & 102.75 & 102.142 & 0.607222 & -0.0897222 \tabularnewline
24 & 102.72 & 102.86 & 102.247 & 0.612556 & -0.139639 \tabularnewline
25 & 102.73 & 102.219 & 102.353 & -0.134028 & 0.511111 \tabularnewline
26 & 102.18 & 102.003 & 102.46 & -0.457111 & 0.177111 \tabularnewline
27 & 102.22 & 102.175 & 102.561 & -0.386028 & 0.0451944 \tabularnewline
28 & 102.37 & 102.358 & 102.651 & -0.292444 & 0.0116111 \tabularnewline
29 & 102.53 & 102.571 & 102.737 & -0.165694 & -0.0413889 \tabularnewline
30 & 102.61 & 102.685 & 102.822 & -0.137194 & -0.0748889 \tabularnewline
31 & 102.62 & 102.426 & 102.732 & -0.306444 & 0.193944 \tabularnewline
32 & 103 & 102.474 & 102.472 & 0.00230556 & 0.525611 \tabularnewline
33 & 103.17 & 102.397 & 102.215 & 0.181722 & 0.773278 \tabularnewline
34 & 103.52 & 102.436 & 101.961 & 0.475139 & 1.08361 \tabularnewline
35 & 103.69 & 102.321 & 101.714 & 0.607222 & 1.36903 \tabularnewline
36 & 103.73 & 102.081 & 101.468 & 0.612556 & 1.64911 \tabularnewline
37 & 99.57 & 101.093 & 101.227 & -0.134028 & -1.52347 \tabularnewline
38 & 99.09 & 100.534 & 100.991 & -0.457111 & -1.44414 \tabularnewline
39 & 99.14 & 100.373 & 100.759 & -0.386028 & -1.23314 \tabularnewline
40 & 99.36 & 100.244 & 100.536 & -0.292444 & -0.883806 \tabularnewline
41 & 99.6 & 100.154 & 100.32 & -0.165694 & -0.554306 \tabularnewline
42 & 99.65 & 99.9695 & 100.107 & -0.137194 & -0.319472 \tabularnewline
43 & 99.8 & 99.7619 & 100.068 & -0.306444 & 0.0381111 \tabularnewline
44 & 100.15 & 100.223 & 100.22 & 0.00230556 & -0.0727222 \tabularnewline
45 & 100.45 & 100.57 & 100.389 & 0.181722 & -0.120472 \tabularnewline
46 & 100.89 & 101.021 & 100.546 & 0.475139 & -0.131389 \tabularnewline
47 & 101.13 & 101.293 & 100.686 & 0.607222 & -0.163056 \tabularnewline
48 & 101.17 & 101.428 & 100.815 & 0.612556 & -0.257556 \tabularnewline
49 & 101.21 & 100.79 & 100.924 & -0.134028 & 0.419861 \tabularnewline
50 & 101.1 & 100.553 & 101.01 & -0.457111 & 0.546694 \tabularnewline
51 & 101.17 & 100.696 & 101.082 & -0.386028 & 0.473944 \tabularnewline
52 & 101.11 & 100.837 & 101.129 & -0.292444 & 0.273278 \tabularnewline
53 & 101.2 & 100.989 & 101.155 & -0.165694 & 0.210694 \tabularnewline
54 & 101.15 & 101.039 & 101.177 & -0.137194 & 0.110528 \tabularnewline
55 & 100.92 & 100.912 & 101.218 & -0.306444 & 0.00811111 \tabularnewline
56 & 101.1 & 101.286 & 101.283 & 0.00230556 & -0.185639 \tabularnewline
57 & 101.22 & 101.536 & 101.354 & 0.181722 & -0.315889 \tabularnewline
58 & 101.25 & 101.906 & 101.431 & 0.475139 & -0.655972 \tabularnewline
59 & 101.39 & 102.116 & 101.508 & 0.607222 & -0.725556 \tabularnewline
60 & 101.43 & 102.2 & 101.588 & 0.612556 & -0.770472 \tabularnewline
61 & 101.95 & 101.526 & 101.66 & -0.134028 & 0.424444 \tabularnewline
62 & 101.92 & 101.246 & 101.703 & -0.457111 & 0.674194 \tabularnewline
63 & 102.05 & 101.338 & 101.724 & -0.386028 & 0.711861 \tabularnewline
64 & 102.07 & 101.454 & 101.746 & -0.292444 & 0.616194 \tabularnewline
65 & 102.1 & 101.609 & 101.775 & -0.165694 & 0.491111 \tabularnewline
66 & 102.16 & 101.664 & 101.801 & -0.137194 & 0.496361 \tabularnewline
67 & 101.63 & NA & NA & -0.306444 & NA \tabularnewline
68 & 101.43 & NA & NA & 0.00230556 & NA \tabularnewline
69 & 101.4 & NA & NA & 0.181722 & NA \tabularnewline
70 & 101.6 & NA & NA & 0.475139 & NA \tabularnewline
71 & 101.72 & NA & NA & 0.607222 & NA \tabularnewline
72 & 101.73 & NA & NA & 0.612556 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294783&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]100.57[/C][C]NA[/C][C]NA[/C][C]-0.134028[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]100.27[/C][C]NA[/C][C]NA[/C][C]-0.457111[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]100.27[/C][C]NA[/C][C]NA[/C][C]-0.386028[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]100.18[/C][C]NA[/C][C]NA[/C][C]-0.292444[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]100.16[/C][C]NA[/C][C]NA[/C][C]-0.165694[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]100.18[/C][C]NA[/C][C]NA[/C][C]-0.137194[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]100.18[/C][C]100.256[/C][C]100.563[/C][C]-0.306444[/C][C]-0.0764722[/C][/ROW]
[ROW][C]8[/C][C]100.59[/C][C]100.612[/C][C]100.61[/C][C]0.00230556[/C][C]-0.0223056[/C][/ROW]
[ROW][C]9[/C][C]100.69[/C][C]100.842[/C][C]100.66[/C][C]0.181722[/C][C]-0.152139[/C][/ROW]
[ROW][C]10[/C][C]101.06[/C][C]101.203[/C][C]100.728[/C][C]0.475139[/C][C]-0.143056[/C][/ROW]
[ROW][C]11[/C][C]101.15[/C][C]101.422[/C][C]100.815[/C][C]0.607222[/C][C]-0.271806[/C][/ROW]
[ROW][C]12[/C][C]101.16[/C][C]101.523[/C][C]100.91[/C][C]0.612556[/C][C]-0.362556[/C][/ROW]
[ROW][C]13[/C][C]101.16[/C][C]100.873[/C][C]101.007[/C][C]-0.134028[/C][C]0.286944[/C][/ROW]
[ROW][C]14[/C][C]100.81[/C][C]100.645[/C][C]101.102[/C][C]-0.457111[/C][C]0.165028[/C][/ROW]
[ROW][C]15[/C][C]100.94[/C][C]100.819[/C][C]101.205[/C][C]-0.386028[/C][C]0.121028[/C][/ROW]
[ROW][C]16[/C][C]101.13[/C][C]101.028[/C][C]101.321[/C][C]-0.292444[/C][C]0.101611[/C][/ROW]
[ROW][C]17[/C][C]101.29[/C][C]101.277[/C][C]101.443[/C][C]-0.165694[/C][C]0.0127778[/C][/ROW]
[ROW][C]18[/C][C]101.34[/C][C]101.434[/C][C]101.571[/C][C]-0.137194[/C][C]-0.0936389[/C][/ROW]
[ROW][C]19[/C][C]101.35[/C][C]101.395[/C][C]101.701[/C][C]-0.306444[/C][C]-0.0448056[/C][/ROW]
[ROW][C]20[/C][C]101.7[/C][C]101.826[/C][C]101.824[/C][C]0.00230556[/C][C]-0.126056[/C][/ROW]
[ROW][C]21[/C][C]102.05[/C][C]102.116[/C][C]101.934[/C][C]0.181722[/C][C]-0.0658889[/C][/ROW]
[ROW][C]22[/C][C]102.48[/C][C]102.514[/C][C]102.039[/C][C]0.475139[/C][C]-0.0343056[/C][/ROW]
[ROW][C]23[/C][C]102.66[/C][C]102.75[/C][C]102.142[/C][C]0.607222[/C][C]-0.0897222[/C][/ROW]
[ROW][C]24[/C][C]102.72[/C][C]102.86[/C][C]102.247[/C][C]0.612556[/C][C]-0.139639[/C][/ROW]
[ROW][C]25[/C][C]102.73[/C][C]102.219[/C][C]102.353[/C][C]-0.134028[/C][C]0.511111[/C][/ROW]
[ROW][C]26[/C][C]102.18[/C][C]102.003[/C][C]102.46[/C][C]-0.457111[/C][C]0.177111[/C][/ROW]
[ROW][C]27[/C][C]102.22[/C][C]102.175[/C][C]102.561[/C][C]-0.386028[/C][C]0.0451944[/C][/ROW]
[ROW][C]28[/C][C]102.37[/C][C]102.358[/C][C]102.651[/C][C]-0.292444[/C][C]0.0116111[/C][/ROW]
[ROW][C]29[/C][C]102.53[/C][C]102.571[/C][C]102.737[/C][C]-0.165694[/C][C]-0.0413889[/C][/ROW]
[ROW][C]30[/C][C]102.61[/C][C]102.685[/C][C]102.822[/C][C]-0.137194[/C][C]-0.0748889[/C][/ROW]
[ROW][C]31[/C][C]102.62[/C][C]102.426[/C][C]102.732[/C][C]-0.306444[/C][C]0.193944[/C][/ROW]
[ROW][C]32[/C][C]103[/C][C]102.474[/C][C]102.472[/C][C]0.00230556[/C][C]0.525611[/C][/ROW]
[ROW][C]33[/C][C]103.17[/C][C]102.397[/C][C]102.215[/C][C]0.181722[/C][C]0.773278[/C][/ROW]
[ROW][C]34[/C][C]103.52[/C][C]102.436[/C][C]101.961[/C][C]0.475139[/C][C]1.08361[/C][/ROW]
[ROW][C]35[/C][C]103.69[/C][C]102.321[/C][C]101.714[/C][C]0.607222[/C][C]1.36903[/C][/ROW]
[ROW][C]36[/C][C]103.73[/C][C]102.081[/C][C]101.468[/C][C]0.612556[/C][C]1.64911[/C][/ROW]
[ROW][C]37[/C][C]99.57[/C][C]101.093[/C][C]101.227[/C][C]-0.134028[/C][C]-1.52347[/C][/ROW]
[ROW][C]38[/C][C]99.09[/C][C]100.534[/C][C]100.991[/C][C]-0.457111[/C][C]-1.44414[/C][/ROW]
[ROW][C]39[/C][C]99.14[/C][C]100.373[/C][C]100.759[/C][C]-0.386028[/C][C]-1.23314[/C][/ROW]
[ROW][C]40[/C][C]99.36[/C][C]100.244[/C][C]100.536[/C][C]-0.292444[/C][C]-0.883806[/C][/ROW]
[ROW][C]41[/C][C]99.6[/C][C]100.154[/C][C]100.32[/C][C]-0.165694[/C][C]-0.554306[/C][/ROW]
[ROW][C]42[/C][C]99.65[/C][C]99.9695[/C][C]100.107[/C][C]-0.137194[/C][C]-0.319472[/C][/ROW]
[ROW][C]43[/C][C]99.8[/C][C]99.7619[/C][C]100.068[/C][C]-0.306444[/C][C]0.0381111[/C][/ROW]
[ROW][C]44[/C][C]100.15[/C][C]100.223[/C][C]100.22[/C][C]0.00230556[/C][C]-0.0727222[/C][/ROW]
[ROW][C]45[/C][C]100.45[/C][C]100.57[/C][C]100.389[/C][C]0.181722[/C][C]-0.120472[/C][/ROW]
[ROW][C]46[/C][C]100.89[/C][C]101.021[/C][C]100.546[/C][C]0.475139[/C][C]-0.131389[/C][/ROW]
[ROW][C]47[/C][C]101.13[/C][C]101.293[/C][C]100.686[/C][C]0.607222[/C][C]-0.163056[/C][/ROW]
[ROW][C]48[/C][C]101.17[/C][C]101.428[/C][C]100.815[/C][C]0.612556[/C][C]-0.257556[/C][/ROW]
[ROW][C]49[/C][C]101.21[/C][C]100.79[/C][C]100.924[/C][C]-0.134028[/C][C]0.419861[/C][/ROW]
[ROW][C]50[/C][C]101.1[/C][C]100.553[/C][C]101.01[/C][C]-0.457111[/C][C]0.546694[/C][/ROW]
[ROW][C]51[/C][C]101.17[/C][C]100.696[/C][C]101.082[/C][C]-0.386028[/C][C]0.473944[/C][/ROW]
[ROW][C]52[/C][C]101.11[/C][C]100.837[/C][C]101.129[/C][C]-0.292444[/C][C]0.273278[/C][/ROW]
[ROW][C]53[/C][C]101.2[/C][C]100.989[/C][C]101.155[/C][C]-0.165694[/C][C]0.210694[/C][/ROW]
[ROW][C]54[/C][C]101.15[/C][C]101.039[/C][C]101.177[/C][C]-0.137194[/C][C]0.110528[/C][/ROW]
[ROW][C]55[/C][C]100.92[/C][C]100.912[/C][C]101.218[/C][C]-0.306444[/C][C]0.00811111[/C][/ROW]
[ROW][C]56[/C][C]101.1[/C][C]101.286[/C][C]101.283[/C][C]0.00230556[/C][C]-0.185639[/C][/ROW]
[ROW][C]57[/C][C]101.22[/C][C]101.536[/C][C]101.354[/C][C]0.181722[/C][C]-0.315889[/C][/ROW]
[ROW][C]58[/C][C]101.25[/C][C]101.906[/C][C]101.431[/C][C]0.475139[/C][C]-0.655972[/C][/ROW]
[ROW][C]59[/C][C]101.39[/C][C]102.116[/C][C]101.508[/C][C]0.607222[/C][C]-0.725556[/C][/ROW]
[ROW][C]60[/C][C]101.43[/C][C]102.2[/C][C]101.588[/C][C]0.612556[/C][C]-0.770472[/C][/ROW]
[ROW][C]61[/C][C]101.95[/C][C]101.526[/C][C]101.66[/C][C]-0.134028[/C][C]0.424444[/C][/ROW]
[ROW][C]62[/C][C]101.92[/C][C]101.246[/C][C]101.703[/C][C]-0.457111[/C][C]0.674194[/C][/ROW]
[ROW][C]63[/C][C]102.05[/C][C]101.338[/C][C]101.724[/C][C]-0.386028[/C][C]0.711861[/C][/ROW]
[ROW][C]64[/C][C]102.07[/C][C]101.454[/C][C]101.746[/C][C]-0.292444[/C][C]0.616194[/C][/ROW]
[ROW][C]65[/C][C]102.1[/C][C]101.609[/C][C]101.775[/C][C]-0.165694[/C][C]0.491111[/C][/ROW]
[ROW][C]66[/C][C]102.16[/C][C]101.664[/C][C]101.801[/C][C]-0.137194[/C][C]0.496361[/C][/ROW]
[ROW][C]67[/C][C]101.63[/C][C]NA[/C][C]NA[/C][C]-0.306444[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.43[/C][C]NA[/C][C]NA[/C][C]0.00230556[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]101.4[/C][C]NA[/C][C]NA[/C][C]0.181722[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]101.6[/C][C]NA[/C][C]NA[/C][C]0.475139[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]101.72[/C][C]NA[/C][C]NA[/C][C]0.607222[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]101.73[/C][C]NA[/C][C]NA[/C][C]0.612556[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294783&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294783&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	100.57	NA	NA	-0.134028	NA
2	100.27	NA	NA	-0.457111	NA
3	100.27	NA	NA	-0.386028	NA
4	100.18	NA	NA	-0.292444	NA
5	100.16	NA	NA	-0.165694	NA
6	100.18	NA	NA	-0.137194	NA
7	100.18	100.256	100.563	-0.306444	-0.0764722
8	100.59	100.612	100.61	0.00230556	-0.0223056
9	100.69	100.842	100.66	0.181722	-0.152139
10	101.06	101.203	100.728	0.475139	-0.143056
11	101.15	101.422	100.815	0.607222	-0.271806
12	101.16	101.523	100.91	0.612556	-0.362556
13	101.16	100.873	101.007	-0.134028	0.286944
14	100.81	100.645	101.102	-0.457111	0.165028
15	100.94	100.819	101.205	-0.386028	0.121028
16	101.13	101.028	101.321	-0.292444	0.101611
17	101.29	101.277	101.443	-0.165694	0.0127778
18	101.34	101.434	101.571	-0.137194	-0.0936389
19	101.35	101.395	101.701	-0.306444	-0.0448056
20	101.7	101.826	101.824	0.00230556	-0.126056
21	102.05	102.116	101.934	0.181722	-0.0658889
22	102.48	102.514	102.039	0.475139	-0.0343056
23	102.66	102.75	102.142	0.607222	-0.0897222
24	102.72	102.86	102.247	0.612556	-0.139639
25	102.73	102.219	102.353	-0.134028	0.511111
26	102.18	102.003	102.46	-0.457111	0.177111
27	102.22	102.175	102.561	-0.386028	0.0451944
28	102.37	102.358	102.651	-0.292444	0.0116111
29	102.53	102.571	102.737	-0.165694	-0.0413889
30	102.61	102.685	102.822	-0.137194	-0.0748889
31	102.62	102.426	102.732	-0.306444	0.193944
32	103	102.474	102.472	0.00230556	0.525611
33	103.17	102.397	102.215	0.181722	0.773278
34	103.52	102.436	101.961	0.475139	1.08361
35	103.69	102.321	101.714	0.607222	1.36903
36	103.73	102.081	101.468	0.612556	1.64911
37	99.57	101.093	101.227	-0.134028	-1.52347
38	99.09	100.534	100.991	-0.457111	-1.44414
39	99.14	100.373	100.759	-0.386028	-1.23314
40	99.36	100.244	100.536	-0.292444	-0.883806
41	99.6	100.154	100.32	-0.165694	-0.554306
42	99.65	99.9695	100.107	-0.137194	-0.319472
43	99.8	99.7619	100.068	-0.306444	0.0381111
44	100.15	100.223	100.22	0.00230556	-0.0727222
45	100.45	100.57	100.389	0.181722	-0.120472
46	100.89	101.021	100.546	0.475139	-0.131389
47	101.13	101.293	100.686	0.607222	-0.163056
48	101.17	101.428	100.815	0.612556	-0.257556
49	101.21	100.79	100.924	-0.134028	0.419861
50	101.1	100.553	101.01	-0.457111	0.546694
51	101.17	100.696	101.082	-0.386028	0.473944
52	101.11	100.837	101.129	-0.292444	0.273278
53	101.2	100.989	101.155	-0.165694	0.210694
54	101.15	101.039	101.177	-0.137194	0.110528
55	100.92	100.912	101.218	-0.306444	0.00811111
56	101.1	101.286	101.283	0.00230556	-0.185639
57	101.22	101.536	101.354	0.181722	-0.315889
58	101.25	101.906	101.431	0.475139	-0.655972
59	101.39	102.116	101.508	0.607222	-0.725556
60	101.43	102.2	101.588	0.612556	-0.770472
61	101.95	101.526	101.66	-0.134028	0.424444
62	101.92	101.246	101.703	-0.457111	0.674194
63	102.05	101.338	101.724	-0.386028	0.711861
64	102.07	101.454	101.746	-0.292444	0.616194
65	102.1	101.609	101.775	-0.165694	0.491111
66	102.16	101.664	101.801	-0.137194	0.496361
67	101.63	NA	NA	-0.306444	NA
68	101.43	NA	NA	0.00230556	NA
69	101.4	NA	NA	0.181722	NA
70	101.6	NA	NA	0.475139	NA
71	101.72	NA	NA	0.607222	NA
72	101.73	NA	NA	0.612556	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 <- 'additive'
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