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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 30 Dec 2016 11:16:23 +0000

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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/Dec/30/t14830967467yta72s3k0vaop6.htm/, Retrieved Sat, 04 May 2024 06:14:07 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 04 May 2024 06:14:07 +0200

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Dataseries X:

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-0,4
0
0,2
-0,6
0,5
-0,3
-1,2
0
0,9
0,5
-0,5
0,1
-0,9
1,1
-0,6
-0,2
0,1
-0,2
3,5
-0,9
-1,3
-0,3
-0,4
1,3
-0,7
0,5
-0,6
0,8
-0,2
0,3
3,8
-1,1
-1,7
0,1
-0,9
1,9
-1,4
1,4
-0,2
0,6
0,5
0,6
3,4
-1,4
-1,6
-1,2
-1,7
1,9
-0,8
1
-0,9
1,1
-0,6
0,6
4,1
-1,1
-2
-1,3
-1,7
1,6
-1,2
1,2
-0,8
0,7
1,2
-0,2
4,4
-1,1
-2,2
-0,7
-1,7
1,6

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	'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	-0.4	NA	NA	-1.12472	NA
2	0	NA	NA	0.877778	NA
3	0.2	NA	NA	-0.747222	NA
4	-0.6	NA	NA	0.508611	NA
5	0.5	NA	NA	0.128611	NA
6	-0.3	NA	NA	0.146111	NA
7	-1.2	2.58611	-0.0875	2.67361	-3.78611
8	0	-1.01222	-0.0625	-0.949722	1.01222
9	0.9	-1.24139	-0.05	-1.19139	2.14139
10	0.5	-0.560556	-0.0666667	-0.493889	1.06056
11	-0.5	-1.17722	-0.0666667	-1.11056	0.677222
12	0.1	1.20361	-0.0791667	1.28278	-1.10361
13	-0.9	-1.00389	0.120833	-1.12472	0.103889
14	1.1	1.15694	0.279167	0.877778	-0.0569444
15	-0.6	-0.597222	0.15	-0.747222	-0.00277778
16	-0.2	0.533611	0.025	0.508611	-0.733611
17	0.1	0.124444	-0.00416667	0.128611	-0.0244444
18	-0.2	0.196111	0.05	0.146111	-0.396111
19	3.5	2.78194	0.108333	2.67361	0.718056
20	-0.9	-0.858056	0.0916667	-0.949722	-0.0419444
21	-1.3	-1.12472	0.0666667	-1.19139	-0.175278
22	-0.3	-0.385556	0.108333	-0.493889	0.0855556
23	-0.4	-0.973056	0.1375	-1.11056	0.573056
24	1.3	1.42861	0.145833	1.28278	-0.128611
25	-0.7	-0.945556	0.179167	-1.12472	0.245556
26	0.5	1.06111	0.183333	0.877778	-0.561111
27	-0.6	-0.588889	0.158333	-0.747222	-0.0111111
28	0.8	0.666944	0.158333	0.508611	0.133056
29	-0.2	0.282778	0.154167	0.128611	-0.482778
30	0.3	0.304444	0.158333	0.146111	-0.00444444
31	3.8	2.82778	0.154167	2.67361	0.972222
32	-1.1	-0.787222	0.1625	-0.949722	-0.312778
33	-1.7	-0.974722	0.216667	-1.19139	-0.725278
34	0.1	-0.268889	0.225	-0.493889	0.368889
35	-0.9	-0.864722	0.245833	-1.11056	-0.0352778
36	1.9	1.57028	0.2875	1.28278	0.329722
37	-1.4	-0.841389	0.283333	-1.12472	-0.558611
38	1.4	1.13194	0.254167	0.877778	0.268056
39	-0.2	-0.501389	0.245833	-0.747222	0.301389
40	0.6	0.704444	0.195833	0.508611	-0.104444
41	0.5	0.236944	0.108333	0.128611	0.263056
42	0.6	0.221111	0.075	0.146111	0.378889
43	3.4	2.77361	0.1	2.67361	0.626389
44	-1.4	-0.841389	0.108333	-0.949722	-0.558611
45	-1.6	-1.12889	0.0625	-1.19139	-0.471111
46	-1.2	-0.439722	0.0541667	-0.493889	-0.760278
47	-1.7	-1.08139	0.0291667	-1.11056	-0.618611
48	1.9	1.26611	-0.0166667	1.28278	0.633889
49	-0.8	-1.11222	0.0125	-1.12472	0.312222
50	1	0.931944	0.0541667	0.877778	0.0680556
51	-0.9	-0.697222	0.05	-0.747222	-0.202778
52	1.1	0.537778	0.0291667	0.508611	0.562222
53	-0.6	0.153611	0.025	0.128611	-0.753611
54	0.6	0.158611	0.0125	0.146111	0.441389
55	4.1	2.65694	-0.0166667	2.67361	1.44306
56	-1.1	-0.974722	-0.025	-0.949722	-0.125278
57	-2	-1.20389	-0.0125	-1.19139	-0.796111
58	-1.3	-0.518889	-0.025	-0.493889	-0.781111
59	-1.7	-1.07722	0.0333333	-1.11056	-0.622778
60	1.6	1.35778	0.075	1.28278	0.242222
61	-1.2	-1.07056	0.0541667	-1.12472	-0.129444
62	1.2	0.944444	0.0666667	0.877778	0.255556
63	-0.8	-0.688889	0.0583333	-0.747222	-0.111111
64	0.7	0.583611	0.075	0.508611	0.116389
65	1.2	0.228611	0.1	0.128611	0.971389
66	-0.2	0.246111	0.1	0.146111	-0.446111
67	4.4	NA	NA	2.67361	NA
68	-1.1	NA	NA	-0.949722	NA
69	-2.2	NA	NA	-1.19139	NA
70	-0.7	NA	NA	-0.493889	NA
71	-1.7	NA	NA	-1.11056	NA
72	1.6	NA	NA	1.28278	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & -0.4 & NA & NA & -1.12472 & NA \tabularnewline
2 & 0 & NA & NA & 0.877778 & NA \tabularnewline
3 & 0.2 & NA & NA & -0.747222 & NA \tabularnewline
4 & -0.6 & NA & NA & 0.508611 & NA \tabularnewline
5 & 0.5 & NA & NA & 0.128611 & NA \tabularnewline
6 & -0.3 & NA & NA & 0.146111 & NA \tabularnewline
7 & -1.2 & 2.58611 & -0.0875 & 2.67361 & -3.78611 \tabularnewline
8 & 0 & -1.01222 & -0.0625 & -0.949722 & 1.01222 \tabularnewline
9 & 0.9 & -1.24139 & -0.05 & -1.19139 & 2.14139 \tabularnewline
10 & 0.5 & -0.560556 & -0.0666667 & -0.493889 & 1.06056 \tabularnewline
11 & -0.5 & -1.17722 & -0.0666667 & -1.11056 & 0.677222 \tabularnewline
12 & 0.1 & 1.20361 & -0.0791667 & 1.28278 & -1.10361 \tabularnewline
13 & -0.9 & -1.00389 & 0.120833 & -1.12472 & 0.103889 \tabularnewline
14 & 1.1 & 1.15694 & 0.279167 & 0.877778 & -0.0569444 \tabularnewline
15 & -0.6 & -0.597222 & 0.15 & -0.747222 & -0.00277778 \tabularnewline
16 & -0.2 & 0.533611 & 0.025 & 0.508611 & -0.733611 \tabularnewline
17 & 0.1 & 0.124444 & -0.00416667 & 0.128611 & -0.0244444 \tabularnewline
18 & -0.2 & 0.196111 & 0.05 & 0.146111 & -0.396111 \tabularnewline
19 & 3.5 & 2.78194 & 0.108333 & 2.67361 & 0.718056 \tabularnewline
20 & -0.9 & -0.858056 & 0.0916667 & -0.949722 & -0.0419444 \tabularnewline
21 & -1.3 & -1.12472 & 0.0666667 & -1.19139 & -0.175278 \tabularnewline
22 & -0.3 & -0.385556 & 0.108333 & -0.493889 & 0.0855556 \tabularnewline
23 & -0.4 & -0.973056 & 0.1375 & -1.11056 & 0.573056 \tabularnewline
24 & 1.3 & 1.42861 & 0.145833 & 1.28278 & -0.128611 \tabularnewline
25 & -0.7 & -0.945556 & 0.179167 & -1.12472 & 0.245556 \tabularnewline
26 & 0.5 & 1.06111 & 0.183333 & 0.877778 & -0.561111 \tabularnewline
27 & -0.6 & -0.588889 & 0.158333 & -0.747222 & -0.0111111 \tabularnewline
28 & 0.8 & 0.666944 & 0.158333 & 0.508611 & 0.133056 \tabularnewline
29 & -0.2 & 0.282778 & 0.154167 & 0.128611 & -0.482778 \tabularnewline
30 & 0.3 & 0.304444 & 0.158333 & 0.146111 & -0.00444444 \tabularnewline
31 & 3.8 & 2.82778 & 0.154167 & 2.67361 & 0.972222 \tabularnewline
32 & -1.1 & -0.787222 & 0.1625 & -0.949722 & -0.312778 \tabularnewline
33 & -1.7 & -0.974722 & 0.216667 & -1.19139 & -0.725278 \tabularnewline
34 & 0.1 & -0.268889 & 0.225 & -0.493889 & 0.368889 \tabularnewline
35 & -0.9 & -0.864722 & 0.245833 & -1.11056 & -0.0352778 \tabularnewline
36 & 1.9 & 1.57028 & 0.2875 & 1.28278 & 0.329722 \tabularnewline
37 & -1.4 & -0.841389 & 0.283333 & -1.12472 & -0.558611 \tabularnewline
38 & 1.4 & 1.13194 & 0.254167 & 0.877778 & 0.268056 \tabularnewline
39 & -0.2 & -0.501389 & 0.245833 & -0.747222 & 0.301389 \tabularnewline
40 & 0.6 & 0.704444 & 0.195833 & 0.508611 & -0.104444 \tabularnewline
41 & 0.5 & 0.236944 & 0.108333 & 0.128611 & 0.263056 \tabularnewline
42 & 0.6 & 0.221111 & 0.075 & 0.146111 & 0.378889 \tabularnewline
43 & 3.4 & 2.77361 & 0.1 & 2.67361 & 0.626389 \tabularnewline
44 & -1.4 & -0.841389 & 0.108333 & -0.949722 & -0.558611 \tabularnewline
45 & -1.6 & -1.12889 & 0.0625 & -1.19139 & -0.471111 \tabularnewline
46 & -1.2 & -0.439722 & 0.0541667 & -0.493889 & -0.760278 \tabularnewline
47 & -1.7 & -1.08139 & 0.0291667 & -1.11056 & -0.618611 \tabularnewline
48 & 1.9 & 1.26611 & -0.0166667 & 1.28278 & 0.633889 \tabularnewline
49 & -0.8 & -1.11222 & 0.0125 & -1.12472 & 0.312222 \tabularnewline
50 & 1 & 0.931944 & 0.0541667 & 0.877778 & 0.0680556 \tabularnewline
51 & -0.9 & -0.697222 & 0.05 & -0.747222 & -0.202778 \tabularnewline
52 & 1.1 & 0.537778 & 0.0291667 & 0.508611 & 0.562222 \tabularnewline
53 & -0.6 & 0.153611 & 0.025 & 0.128611 & -0.753611 \tabularnewline
54 & 0.6 & 0.158611 & 0.0125 & 0.146111 & 0.441389 \tabularnewline
55 & 4.1 & 2.65694 & -0.0166667 & 2.67361 & 1.44306 \tabularnewline
56 & -1.1 & -0.974722 & -0.025 & -0.949722 & -0.125278 \tabularnewline
57 & -2 & -1.20389 & -0.0125 & -1.19139 & -0.796111 \tabularnewline
58 & -1.3 & -0.518889 & -0.025 & -0.493889 & -0.781111 \tabularnewline
59 & -1.7 & -1.07722 & 0.0333333 & -1.11056 & -0.622778 \tabularnewline
60 & 1.6 & 1.35778 & 0.075 & 1.28278 & 0.242222 \tabularnewline
61 & -1.2 & -1.07056 & 0.0541667 & -1.12472 & -0.129444 \tabularnewline
62 & 1.2 & 0.944444 & 0.0666667 & 0.877778 & 0.255556 \tabularnewline
63 & -0.8 & -0.688889 & 0.0583333 & -0.747222 & -0.111111 \tabularnewline
64 & 0.7 & 0.583611 & 0.075 & 0.508611 & 0.116389 \tabularnewline
65 & 1.2 & 0.228611 & 0.1 & 0.128611 & 0.971389 \tabularnewline
66 & -0.2 & 0.246111 & 0.1 & 0.146111 & -0.446111 \tabularnewline
67 & 4.4 & NA & NA & 2.67361 & NA \tabularnewline
68 & -1.1 & NA & NA & -0.949722 & NA \tabularnewline
69 & -2.2 & NA & NA & -1.19139 & NA \tabularnewline
70 & -0.7 & NA & NA & -0.493889 & NA \tabularnewline
71 & -1.7 & NA & NA & -1.11056 & NA \tabularnewline
72 & 1.6 & NA & NA & 1.28278 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]-0.4[/C][C]NA[/C][C]NA[/C][C]-1.12472[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]0[/C][C]NA[/C][C]NA[/C][C]0.877778[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]0.2[/C][C]NA[/C][C]NA[/C][C]-0.747222[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]-0.6[/C][C]NA[/C][C]NA[/C][C]0.508611[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]0.5[/C][C]NA[/C][C]NA[/C][C]0.128611[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]-0.3[/C][C]NA[/C][C]NA[/C][C]0.146111[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]-1.2[/C][C]2.58611[/C][C]-0.0875[/C][C]2.67361[/C][C]-3.78611[/C][/ROW]
[ROW][C]8[/C][C]0[/C][C]-1.01222[/C][C]-0.0625[/C][C]-0.949722[/C][C]1.01222[/C][/ROW]
[ROW][C]9[/C][C]0.9[/C][C]-1.24139[/C][C]-0.05[/C][C]-1.19139[/C][C]2.14139[/C][/ROW]
[ROW][C]10[/C][C]0.5[/C][C]-0.560556[/C][C]-0.0666667[/C][C]-0.493889[/C][C]1.06056[/C][/ROW]
[ROW][C]11[/C][C]-0.5[/C][C]-1.17722[/C][C]-0.0666667[/C][C]-1.11056[/C][C]0.677222[/C][/ROW]
[ROW][C]12[/C][C]0.1[/C][C]1.20361[/C][C]-0.0791667[/C][C]1.28278[/C][C]-1.10361[/C][/ROW]
[ROW][C]13[/C][C]-0.9[/C][C]-1.00389[/C][C]0.120833[/C][C]-1.12472[/C][C]0.103889[/C][/ROW]
[ROW][C]14[/C][C]1.1[/C][C]1.15694[/C][C]0.279167[/C][C]0.877778[/C][C]-0.0569444[/C][/ROW]
[ROW][C]15[/C][C]-0.6[/C][C]-0.597222[/C][C]0.15[/C][C]-0.747222[/C][C]-0.00277778[/C][/ROW]
[ROW][C]16[/C][C]-0.2[/C][C]0.533611[/C][C]0.025[/C][C]0.508611[/C][C]-0.733611[/C][/ROW]
[ROW][C]17[/C][C]0.1[/C][C]0.124444[/C][C]-0.00416667[/C][C]0.128611[/C][C]-0.0244444[/C][/ROW]
[ROW][C]18[/C][C]-0.2[/C][C]0.196111[/C][C]0.05[/C][C]0.146111[/C][C]-0.396111[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]2.78194[/C][C]0.108333[/C][C]2.67361[/C][C]0.718056[/C][/ROW]
[ROW][C]20[/C][C]-0.9[/C][C]-0.858056[/C][C]0.0916667[/C][C]-0.949722[/C][C]-0.0419444[/C][/ROW]
[ROW][C]21[/C][C]-1.3[/C][C]-1.12472[/C][C]0.0666667[/C][C]-1.19139[/C][C]-0.175278[/C][/ROW]
[ROW][C]22[/C][C]-0.3[/C][C]-0.385556[/C][C]0.108333[/C][C]-0.493889[/C][C]0.0855556[/C][/ROW]
[ROW][C]23[/C][C]-0.4[/C][C]-0.973056[/C][C]0.1375[/C][C]-1.11056[/C][C]0.573056[/C][/ROW]
[ROW][C]24[/C][C]1.3[/C][C]1.42861[/C][C]0.145833[/C][C]1.28278[/C][C]-0.128611[/C][/ROW]
[ROW][C]25[/C][C]-0.7[/C][C]-0.945556[/C][C]0.179167[/C][C]-1.12472[/C][C]0.245556[/C][/ROW]
[ROW][C]26[/C][C]0.5[/C][C]1.06111[/C][C]0.183333[/C][C]0.877778[/C][C]-0.561111[/C][/ROW]
[ROW][C]27[/C][C]-0.6[/C][C]-0.588889[/C][C]0.158333[/C][C]-0.747222[/C][C]-0.0111111[/C][/ROW]
[ROW][C]28[/C][C]0.8[/C][C]0.666944[/C][C]0.158333[/C][C]0.508611[/C][C]0.133056[/C][/ROW]
[ROW][C]29[/C][C]-0.2[/C][C]0.282778[/C][C]0.154167[/C][C]0.128611[/C][C]-0.482778[/C][/ROW]
[ROW][C]30[/C][C]0.3[/C][C]0.304444[/C][C]0.158333[/C][C]0.146111[/C][C]-0.00444444[/C][/ROW]
[ROW][C]31[/C][C]3.8[/C][C]2.82778[/C][C]0.154167[/C][C]2.67361[/C][C]0.972222[/C][/ROW]
[ROW][C]32[/C][C]-1.1[/C][C]-0.787222[/C][C]0.1625[/C][C]-0.949722[/C][C]-0.312778[/C][/ROW]
[ROW][C]33[/C][C]-1.7[/C][C]-0.974722[/C][C]0.216667[/C][C]-1.19139[/C][C]-0.725278[/C][/ROW]
[ROW][C]34[/C][C]0.1[/C][C]-0.268889[/C][C]0.225[/C][C]-0.493889[/C][C]0.368889[/C][/ROW]
[ROW][C]35[/C][C]-0.9[/C][C]-0.864722[/C][C]0.245833[/C][C]-1.11056[/C][C]-0.0352778[/C][/ROW]
[ROW][C]36[/C][C]1.9[/C][C]1.57028[/C][C]0.2875[/C][C]1.28278[/C][C]0.329722[/C][/ROW]
[ROW][C]37[/C][C]-1.4[/C][C]-0.841389[/C][C]0.283333[/C][C]-1.12472[/C][C]-0.558611[/C][/ROW]
[ROW][C]38[/C][C]1.4[/C][C]1.13194[/C][C]0.254167[/C][C]0.877778[/C][C]0.268056[/C][/ROW]
[ROW][C]39[/C][C]-0.2[/C][C]-0.501389[/C][C]0.245833[/C][C]-0.747222[/C][C]0.301389[/C][/ROW]
[ROW][C]40[/C][C]0.6[/C][C]0.704444[/C][C]0.195833[/C][C]0.508611[/C][C]-0.104444[/C][/ROW]
[ROW][C]41[/C][C]0.5[/C][C]0.236944[/C][C]0.108333[/C][C]0.128611[/C][C]0.263056[/C][/ROW]
[ROW][C]42[/C][C]0.6[/C][C]0.221111[/C][C]0.075[/C][C]0.146111[/C][C]0.378889[/C][/ROW]
[ROW][C]43[/C][C]3.4[/C][C]2.77361[/C][C]0.1[/C][C]2.67361[/C][C]0.626389[/C][/ROW]
[ROW][C]44[/C][C]-1.4[/C][C]-0.841389[/C][C]0.108333[/C][C]-0.949722[/C][C]-0.558611[/C][/ROW]
[ROW][C]45[/C][C]-1.6[/C][C]-1.12889[/C][C]0.0625[/C][C]-1.19139[/C][C]-0.471111[/C][/ROW]
[ROW][C]46[/C][C]-1.2[/C][C]-0.439722[/C][C]0.0541667[/C][C]-0.493889[/C][C]-0.760278[/C][/ROW]
[ROW][C]47[/C][C]-1.7[/C][C]-1.08139[/C][C]0.0291667[/C][C]-1.11056[/C][C]-0.618611[/C][/ROW]
[ROW][C]48[/C][C]1.9[/C][C]1.26611[/C][C]-0.0166667[/C][C]1.28278[/C][C]0.633889[/C][/ROW]
[ROW][C]49[/C][C]-0.8[/C][C]-1.11222[/C][C]0.0125[/C][C]-1.12472[/C][C]0.312222[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.931944[/C][C]0.0541667[/C][C]0.877778[/C][C]0.0680556[/C][/ROW]
[ROW][C]51[/C][C]-0.9[/C][C]-0.697222[/C][C]0.05[/C][C]-0.747222[/C][C]-0.202778[/C][/ROW]
[ROW][C]52[/C][C]1.1[/C][C]0.537778[/C][C]0.0291667[/C][C]0.508611[/C][C]0.562222[/C][/ROW]
[ROW][C]53[/C][C]-0.6[/C][C]0.153611[/C][C]0.025[/C][C]0.128611[/C][C]-0.753611[/C][/ROW]
[ROW][C]54[/C][C]0.6[/C][C]0.158611[/C][C]0.0125[/C][C]0.146111[/C][C]0.441389[/C][/ROW]
[ROW][C]55[/C][C]4.1[/C][C]2.65694[/C][C]-0.0166667[/C][C]2.67361[/C][C]1.44306[/C][/ROW]
[ROW][C]56[/C][C]-1.1[/C][C]-0.974722[/C][C]-0.025[/C][C]-0.949722[/C][C]-0.125278[/C][/ROW]
[ROW][C]57[/C][C]-2[/C][C]-1.20389[/C][C]-0.0125[/C][C]-1.19139[/C][C]-0.796111[/C][/ROW]
[ROW][C]58[/C][C]-1.3[/C][C]-0.518889[/C][C]-0.025[/C][C]-0.493889[/C][C]-0.781111[/C][/ROW]
[ROW][C]59[/C][C]-1.7[/C][C]-1.07722[/C][C]0.0333333[/C][C]-1.11056[/C][C]-0.622778[/C][/ROW]
[ROW][C]60[/C][C]1.6[/C][C]1.35778[/C][C]0.075[/C][C]1.28278[/C][C]0.242222[/C][/ROW]
[ROW][C]61[/C][C]-1.2[/C][C]-1.07056[/C][C]0.0541667[/C][C]-1.12472[/C][C]-0.129444[/C][/ROW]
[ROW][C]62[/C][C]1.2[/C][C]0.944444[/C][C]0.0666667[/C][C]0.877778[/C][C]0.255556[/C][/ROW]
[ROW][C]63[/C][C]-0.8[/C][C]-0.688889[/C][C]0.0583333[/C][C]-0.747222[/C][C]-0.111111[/C][/ROW]
[ROW][C]64[/C][C]0.7[/C][C]0.583611[/C][C]0.075[/C][C]0.508611[/C][C]0.116389[/C][/ROW]
[ROW][C]65[/C][C]1.2[/C][C]0.228611[/C][C]0.1[/C][C]0.128611[/C][C]0.971389[/C][/ROW]
[ROW][C]66[/C][C]-0.2[/C][C]0.246111[/C][C]0.1[/C][C]0.146111[/C][C]-0.446111[/C][/ROW]
[ROW][C]67[/C][C]4.4[/C][C]NA[/C][C]NA[/C][C]2.67361[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]-1.1[/C][C]NA[/C][C]NA[/C][C]-0.949722[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]-2.2[/C][C]NA[/C][C]NA[/C][C]-1.19139[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]-0.7[/C][C]NA[/C][C]NA[/C][C]-0.493889[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]-1.7[/C][C]NA[/C][C]NA[/C][C]-1.11056[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.6[/C][C]NA[/C][C]NA[/C][C]1.28278[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	-0.4	NA	NA	-1.12472	NA
2	0	NA	NA	0.877778	NA
3	0.2	NA	NA	-0.747222	NA
4	-0.6	NA	NA	0.508611	NA
5	0.5	NA	NA	0.128611	NA
6	-0.3	NA	NA	0.146111	NA
7	-1.2	2.58611	-0.0875	2.67361	-3.78611
8	0	-1.01222	-0.0625	-0.949722	1.01222
9	0.9	-1.24139	-0.05	-1.19139	2.14139
10	0.5	-0.560556	-0.0666667	-0.493889	1.06056
11	-0.5	-1.17722	-0.0666667	-1.11056	0.677222
12	0.1	1.20361	-0.0791667	1.28278	-1.10361
13	-0.9	-1.00389	0.120833	-1.12472	0.103889
14	1.1	1.15694	0.279167	0.877778	-0.0569444
15	-0.6	-0.597222	0.15	-0.747222	-0.00277778
16	-0.2	0.533611	0.025	0.508611	-0.733611
17	0.1	0.124444	-0.00416667	0.128611	-0.0244444
18	-0.2	0.196111	0.05	0.146111	-0.396111
19	3.5	2.78194	0.108333	2.67361	0.718056
20	-0.9	-0.858056	0.0916667	-0.949722	-0.0419444
21	-1.3	-1.12472	0.0666667	-1.19139	-0.175278
22	-0.3	-0.385556	0.108333	-0.493889	0.0855556
23	-0.4	-0.973056	0.1375	-1.11056	0.573056
24	1.3	1.42861	0.145833	1.28278	-0.128611
25	-0.7	-0.945556	0.179167	-1.12472	0.245556
26	0.5	1.06111	0.183333	0.877778	-0.561111
27	-0.6	-0.588889	0.158333	-0.747222	-0.0111111
28	0.8	0.666944	0.158333	0.508611	0.133056
29	-0.2	0.282778	0.154167	0.128611	-0.482778
30	0.3	0.304444	0.158333	0.146111	-0.00444444
31	3.8	2.82778	0.154167	2.67361	0.972222
32	-1.1	-0.787222	0.1625	-0.949722	-0.312778
33	-1.7	-0.974722	0.216667	-1.19139	-0.725278
34	0.1	-0.268889	0.225	-0.493889	0.368889
35	-0.9	-0.864722	0.245833	-1.11056	-0.0352778
36	1.9	1.57028	0.2875	1.28278	0.329722
37	-1.4	-0.841389	0.283333	-1.12472	-0.558611
38	1.4	1.13194	0.254167	0.877778	0.268056
39	-0.2	-0.501389	0.245833	-0.747222	0.301389
40	0.6	0.704444	0.195833	0.508611	-0.104444
41	0.5	0.236944	0.108333	0.128611	0.263056
42	0.6	0.221111	0.075	0.146111	0.378889
43	3.4	2.77361	0.1	2.67361	0.626389
44	-1.4	-0.841389	0.108333	-0.949722	-0.558611
45	-1.6	-1.12889	0.0625	-1.19139	-0.471111
46	-1.2	-0.439722	0.0541667	-0.493889	-0.760278
47	-1.7	-1.08139	0.0291667	-1.11056	-0.618611
48	1.9	1.26611	-0.0166667	1.28278	0.633889
49	-0.8	-1.11222	0.0125	-1.12472	0.312222
50	1	0.931944	0.0541667	0.877778	0.0680556
51	-0.9	-0.697222	0.05	-0.747222	-0.202778
52	1.1	0.537778	0.0291667	0.508611	0.562222
53	-0.6	0.153611	0.025	0.128611	-0.753611
54	0.6	0.158611	0.0125	0.146111	0.441389
55	4.1	2.65694	-0.0166667	2.67361	1.44306
56	-1.1	-0.974722	-0.025	-0.949722	-0.125278
57	-2	-1.20389	-0.0125	-1.19139	-0.796111
58	-1.3	-0.518889	-0.025	-0.493889	-0.781111
59	-1.7	-1.07722	0.0333333	-1.11056	-0.622778
60	1.6	1.35778	0.075	1.28278	0.242222
61	-1.2	-1.07056	0.0541667	-1.12472	-0.129444
62	1.2	0.944444	0.0666667	0.877778	0.255556
63	-0.8	-0.688889	0.0583333	-0.747222	-0.111111
64	0.7	0.583611	0.075	0.508611	0.116389
65	1.2	0.228611	0.1	0.128611	0.971389
66	-0.2	0.246111	0.1	0.146111	-0.446111
67	4.4	NA	NA	2.67361	NA
68	-1.1	NA	NA	-0.949722	NA
69	-2.2	NA	NA	-1.19139	NA
70	-0.7	NA	NA	-0.493889	NA
71	-1.7	NA	NA	-1.11056	NA
72	1.6	NA	NA	1.28278	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