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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 23 May 2014 03:06:59 -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/23/t1400828982zashi4ajocs4wby.htm/, Retrieved Tue, 14 May 2024 01:17:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235203, Retrieved Tue, 14 May 2024 01:17:22 +0000

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-       [Classical Decomposition] [] [2014-05-23 07:06:59] [bdca4dcc63d0690a1e5c4820657ce42d] [Current]

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235203&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]3 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=235203&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235203&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	3 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	8.7	NA	NA	0.190972	NA
2	8.7	NA	NA	0.18125	NA
3	8.6	NA	NA	0.00138889	NA
4	8.5	NA	NA	-0.18125	NA
5	8.3	NA	NA	-0.434722	NA
6	8	NA	NA	-0.424306	NA
7	8.2	8.57222	8.22083	0.351389	-0.372222
8	8.1	8.58333	8.1625	0.420833	-0.483333
9	8.1	8.31181	8.10417	0.207639	-0.211806
10	8	7.99861	8.05417	-0.0555556	0.00138889
11	7.9	7.80486	8.00833	-0.203472	0.0951389
12	7.9	7.89583	7.95	-0.0541667	0.00416667
13	8	8.07847	7.8875	0.190972	-0.0784722
14	8	8.00625	7.825	0.18125	-0.00625
15	7.9	7.74722	7.74583	0.00138889	0.152778
16	8	7.47708	7.65833	-0.18125	0.522917
17	7.7	7.14444	7.57917	-0.434722	0.555556
18	7.2	7.08819	7.5125	-0.424306	0.111806
19	7.5	7.80556	7.45417	0.351389	-0.305556
20	7.3	7.80833	7.3875	0.420833	-0.508333
21	7	7.51181	7.30417	0.207639	-0.511806
22	7	7.13611	7.19167	-0.0555556	-0.136111
23	7	6.85486	7.05833	-0.203472	0.145139
24	7.2	6.90833	6.9625	-0.0541667	0.291667
25	7.3	7.13264	6.94167	0.190972	0.167361
26	7.1	7.15625	6.975	0.18125	-0.05625
27	6.8	7.02222	7.02083	0.00138889	-0.222222
28	6.4	6.85625	7.0375	-0.18125	-0.45625
29	6.1	6.58194	7.01667	-0.434722	-0.481944
30	6.5	6.56319	6.9875	-0.424306	-0.0631944
31	7.7	7.34306	6.99167	0.351389	0.356944
32	7.9	7.46667	7.04583	0.420833	0.433333
33	7.5	7.34097	7.13333	0.207639	0.159028
34	6.9	7.18194	7.2375	-0.0555556	-0.281944
35	6.6	7.13819	7.34167	-0.203472	-0.538194
36	6.9	7.375	7.42917	-0.0541667	-0.475
37	7.7	7.67431	7.48333	0.190972	0.0256944
38	8	7.69792	7.51667	0.18125	0.302083
39	8	7.55972	7.55833	0.00138889	0.440278
40	7.7	7.44375	7.625	-0.18125	0.25625
41	7.3	7.28611	7.72083	-0.434722	0.0138889
42	7.4	7.40903	7.83333	-0.424306	-0.00902778
43	8.1	8.28056	7.92917	0.351389	-0.180556
44	8.3	8.41667	7.99583	0.420833	-0.116667
45	8.1	8.25347	8.04583	0.207639	-0.153472
46	7.9	8.03611	8.09167	-0.0555556	-0.136111
47	7.9	7.94236	8.14583	-0.203472	-0.0423611
48	8.3	8.14583	8.2	-0.0541667	0.154167
49	8.6	8.44514	8.25417	0.190972	0.154861
50	8.7	8.48125	8.3	0.18125	0.21875
51	8.5	8.33472	8.33333	0.00138889	0.165278
52	8.3	8.17708	8.35833	-0.18125	0.122917
53	8	7.92778	8.3625	-0.434722	0.0722222
54	8	7.90903	8.33333	-0.424306	0.0909722
55	8.8	8.61389	8.2625	0.351389	0.186111
56	8.7	8.575	8.15417	0.420833	0.125
57	8.5	8.23264	8.025	0.207639	0.267361
58	8.1	7.83194	7.8875	-0.0555556	0.268056
59	7.8	7.55069	7.75417	-0.203472	0.249306
60	7.7	7.57917	7.63333	-0.0541667	0.120833
61	7.5	7.72014	7.52917	0.190972	-0.220139
62	7.2	7.63542	7.45417	0.18125	-0.435417
63	6.9	7.39306	7.39167	0.00138889	-0.493056
64	6.6	7.14375	7.325	-0.18125	-0.54375
65	6.5	6.82361	7.25833	-0.434722	-0.323611
66	6.6	6.77153	7.19583	-0.424306	-0.171528
67	7.7	7.50972	7.15833	0.351389	0.190278
68	8	7.575	7.15417	0.420833	0.425
69	7.7	7.37431	7.16667	0.207639	0.325694
70	7.3	7.14028	7.19583	-0.0555556	0.159722
71	7	7.03403	7.2375	-0.203472	-0.0340278
72	7	7.22083	7.275	-0.0541667	-0.220833
73	7.3	7.47431	7.28333	0.190972	-0.174306
74	7.3	7.44792	7.26667	0.18125	-0.147917
75	7.1	7.26806	7.26667	0.00138889	-0.168056
76	7.1	7.12708	7.30833	-0.18125	-0.0270833
77	7	6.96111	7.39583	-0.434722	0.0388889
78	7	7.08403	7.50833	-0.424306	-0.0840278
79	7.5	NA	NA	0.351389	NA
80	7.8	NA	NA	0.420833	NA
81	7.9	NA	NA	0.207639	NA
82	8.1	NA	NA	-0.0555556	NA
83	8.3	NA	NA	-0.203472	NA
84	8.4	NA	NA	-0.0541667	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 8.7 & NA & NA & 0.190972 & NA \tabularnewline
2 & 8.7 & NA & NA & 0.18125 & NA \tabularnewline
3 & 8.6 & NA & NA & 0.00138889 & NA \tabularnewline
4 & 8.5 & NA & NA & -0.18125 & NA \tabularnewline
5 & 8.3 & NA & NA & -0.434722 & NA \tabularnewline
6 & 8 & NA & NA & -0.424306 & NA \tabularnewline
7 & 8.2 & 8.57222 & 8.22083 & 0.351389 & -0.372222 \tabularnewline
8 & 8.1 & 8.58333 & 8.1625 & 0.420833 & -0.483333 \tabularnewline
9 & 8.1 & 8.31181 & 8.10417 & 0.207639 & -0.211806 \tabularnewline
10 & 8 & 7.99861 & 8.05417 & -0.0555556 & 0.00138889 \tabularnewline
11 & 7.9 & 7.80486 & 8.00833 & -0.203472 & 0.0951389 \tabularnewline
12 & 7.9 & 7.89583 & 7.95 & -0.0541667 & 0.00416667 \tabularnewline
13 & 8 & 8.07847 & 7.8875 & 0.190972 & -0.0784722 \tabularnewline
14 & 8 & 8.00625 & 7.825 & 0.18125 & -0.00625 \tabularnewline
15 & 7.9 & 7.74722 & 7.74583 & 0.00138889 & 0.152778 \tabularnewline
16 & 8 & 7.47708 & 7.65833 & -0.18125 & 0.522917 \tabularnewline
17 & 7.7 & 7.14444 & 7.57917 & -0.434722 & 0.555556 \tabularnewline
18 & 7.2 & 7.08819 & 7.5125 & -0.424306 & 0.111806 \tabularnewline
19 & 7.5 & 7.80556 & 7.45417 & 0.351389 & -0.305556 \tabularnewline
20 & 7.3 & 7.80833 & 7.3875 & 0.420833 & -0.508333 \tabularnewline
21 & 7 & 7.51181 & 7.30417 & 0.207639 & -0.511806 \tabularnewline
22 & 7 & 7.13611 & 7.19167 & -0.0555556 & -0.136111 \tabularnewline
23 & 7 & 6.85486 & 7.05833 & -0.203472 & 0.145139 \tabularnewline
24 & 7.2 & 6.90833 & 6.9625 & -0.0541667 & 0.291667 \tabularnewline
25 & 7.3 & 7.13264 & 6.94167 & 0.190972 & 0.167361 \tabularnewline
26 & 7.1 & 7.15625 & 6.975 & 0.18125 & -0.05625 \tabularnewline
27 & 6.8 & 7.02222 & 7.02083 & 0.00138889 & -0.222222 \tabularnewline
28 & 6.4 & 6.85625 & 7.0375 & -0.18125 & -0.45625 \tabularnewline
29 & 6.1 & 6.58194 & 7.01667 & -0.434722 & -0.481944 \tabularnewline
30 & 6.5 & 6.56319 & 6.9875 & -0.424306 & -0.0631944 \tabularnewline
31 & 7.7 & 7.34306 & 6.99167 & 0.351389 & 0.356944 \tabularnewline
32 & 7.9 & 7.46667 & 7.04583 & 0.420833 & 0.433333 \tabularnewline
33 & 7.5 & 7.34097 & 7.13333 & 0.207639 & 0.159028 \tabularnewline
34 & 6.9 & 7.18194 & 7.2375 & -0.0555556 & -0.281944 \tabularnewline
35 & 6.6 & 7.13819 & 7.34167 & -0.203472 & -0.538194 \tabularnewline
36 & 6.9 & 7.375 & 7.42917 & -0.0541667 & -0.475 \tabularnewline
37 & 7.7 & 7.67431 & 7.48333 & 0.190972 & 0.0256944 \tabularnewline
38 & 8 & 7.69792 & 7.51667 & 0.18125 & 0.302083 \tabularnewline
39 & 8 & 7.55972 & 7.55833 & 0.00138889 & 0.440278 \tabularnewline
40 & 7.7 & 7.44375 & 7.625 & -0.18125 & 0.25625 \tabularnewline
41 & 7.3 & 7.28611 & 7.72083 & -0.434722 & 0.0138889 \tabularnewline
42 & 7.4 & 7.40903 & 7.83333 & -0.424306 & -0.00902778 \tabularnewline
43 & 8.1 & 8.28056 & 7.92917 & 0.351389 & -0.180556 \tabularnewline
44 & 8.3 & 8.41667 & 7.99583 & 0.420833 & -0.116667 \tabularnewline
45 & 8.1 & 8.25347 & 8.04583 & 0.207639 & -0.153472 \tabularnewline
46 & 7.9 & 8.03611 & 8.09167 & -0.0555556 & -0.136111 \tabularnewline
47 & 7.9 & 7.94236 & 8.14583 & -0.203472 & -0.0423611 \tabularnewline
48 & 8.3 & 8.14583 & 8.2 & -0.0541667 & 0.154167 \tabularnewline
49 & 8.6 & 8.44514 & 8.25417 & 0.190972 & 0.154861 \tabularnewline
50 & 8.7 & 8.48125 & 8.3 & 0.18125 & 0.21875 \tabularnewline
51 & 8.5 & 8.33472 & 8.33333 & 0.00138889 & 0.165278 \tabularnewline
52 & 8.3 & 8.17708 & 8.35833 & -0.18125 & 0.122917 \tabularnewline
53 & 8 & 7.92778 & 8.3625 & -0.434722 & 0.0722222 \tabularnewline
54 & 8 & 7.90903 & 8.33333 & -0.424306 & 0.0909722 \tabularnewline
55 & 8.8 & 8.61389 & 8.2625 & 0.351389 & 0.186111 \tabularnewline
56 & 8.7 & 8.575 & 8.15417 & 0.420833 & 0.125 \tabularnewline
57 & 8.5 & 8.23264 & 8.025 & 0.207639 & 0.267361 \tabularnewline
58 & 8.1 & 7.83194 & 7.8875 & -0.0555556 & 0.268056 \tabularnewline
59 & 7.8 & 7.55069 & 7.75417 & -0.203472 & 0.249306 \tabularnewline
60 & 7.7 & 7.57917 & 7.63333 & -0.0541667 & 0.120833 \tabularnewline
61 & 7.5 & 7.72014 & 7.52917 & 0.190972 & -0.220139 \tabularnewline
62 & 7.2 & 7.63542 & 7.45417 & 0.18125 & -0.435417 \tabularnewline
63 & 6.9 & 7.39306 & 7.39167 & 0.00138889 & -0.493056 \tabularnewline
64 & 6.6 & 7.14375 & 7.325 & -0.18125 & -0.54375 \tabularnewline
65 & 6.5 & 6.82361 & 7.25833 & -0.434722 & -0.323611 \tabularnewline
66 & 6.6 & 6.77153 & 7.19583 & -0.424306 & -0.171528 \tabularnewline
67 & 7.7 & 7.50972 & 7.15833 & 0.351389 & 0.190278 \tabularnewline
68 & 8 & 7.575 & 7.15417 & 0.420833 & 0.425 \tabularnewline
69 & 7.7 & 7.37431 & 7.16667 & 0.207639 & 0.325694 \tabularnewline
70 & 7.3 & 7.14028 & 7.19583 & -0.0555556 & 0.159722 \tabularnewline
71 & 7 & 7.03403 & 7.2375 & -0.203472 & -0.0340278 \tabularnewline
72 & 7 & 7.22083 & 7.275 & -0.0541667 & -0.220833 \tabularnewline
73 & 7.3 & 7.47431 & 7.28333 & 0.190972 & -0.174306 \tabularnewline
74 & 7.3 & 7.44792 & 7.26667 & 0.18125 & -0.147917 \tabularnewline
75 & 7.1 & 7.26806 & 7.26667 & 0.00138889 & -0.168056 \tabularnewline
76 & 7.1 & 7.12708 & 7.30833 & -0.18125 & -0.0270833 \tabularnewline
77 & 7 & 6.96111 & 7.39583 & -0.434722 & 0.0388889 \tabularnewline
78 & 7 & 7.08403 & 7.50833 & -0.424306 & -0.0840278 \tabularnewline
79 & 7.5 & NA & NA & 0.351389 & NA \tabularnewline
80 & 7.8 & NA & NA & 0.420833 & NA \tabularnewline
81 & 7.9 & NA & NA & 0.207639 & NA \tabularnewline
82 & 8.1 & NA & NA & -0.0555556 & NA \tabularnewline
83 & 8.3 & NA & NA & -0.203472 & NA \tabularnewline
84 & 8.4 & NA & NA & -0.0541667 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235203&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]8.7[/C][C]NA[/C][C]NA[/C][C]0.190972[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]8.7[/C][C]NA[/C][C]NA[/C][C]0.18125[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]8.6[/C][C]NA[/C][C]NA[/C][C]0.00138889[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]8.5[/C][C]NA[/C][C]NA[/C][C]-0.18125[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]8.3[/C][C]NA[/C][C]NA[/C][C]-0.434722[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]8[/C][C]NA[/C][C]NA[/C][C]-0.424306[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]8.2[/C][C]8.57222[/C][C]8.22083[/C][C]0.351389[/C][C]-0.372222[/C][/ROW]
[ROW][C]8[/C][C]8.1[/C][C]8.58333[/C][C]8.1625[/C][C]0.420833[/C][C]-0.483333[/C][/ROW]
[ROW][C]9[/C][C]8.1[/C][C]8.31181[/C][C]8.10417[/C][C]0.207639[/C][C]-0.211806[/C][/ROW]
[ROW][C]10[/C][C]8[/C][C]7.99861[/C][C]8.05417[/C][C]-0.0555556[/C][C]0.00138889[/C][/ROW]
[ROW][C]11[/C][C]7.9[/C][C]7.80486[/C][C]8.00833[/C][C]-0.203472[/C][C]0.0951389[/C][/ROW]
[ROW][C]12[/C][C]7.9[/C][C]7.89583[/C][C]7.95[/C][C]-0.0541667[/C][C]0.00416667[/C][/ROW]
[ROW][C]13[/C][C]8[/C][C]8.07847[/C][C]7.8875[/C][C]0.190972[/C][C]-0.0784722[/C][/ROW]
[ROW][C]14[/C][C]8[/C][C]8.00625[/C][C]7.825[/C][C]0.18125[/C][C]-0.00625[/C][/ROW]
[ROW][C]15[/C][C]7.9[/C][C]7.74722[/C][C]7.74583[/C][C]0.00138889[/C][C]0.152778[/C][/ROW]
[ROW][C]16[/C][C]8[/C][C]7.47708[/C][C]7.65833[/C][C]-0.18125[/C][C]0.522917[/C][/ROW]
[ROW][C]17[/C][C]7.7[/C][C]7.14444[/C][C]7.57917[/C][C]-0.434722[/C][C]0.555556[/C][/ROW]
[ROW][C]18[/C][C]7.2[/C][C]7.08819[/C][C]7.5125[/C][C]-0.424306[/C][C]0.111806[/C][/ROW]
[ROW][C]19[/C][C]7.5[/C][C]7.80556[/C][C]7.45417[/C][C]0.351389[/C][C]-0.305556[/C][/ROW]
[ROW][C]20[/C][C]7.3[/C][C]7.80833[/C][C]7.3875[/C][C]0.420833[/C][C]-0.508333[/C][/ROW]
[ROW][C]21[/C][C]7[/C][C]7.51181[/C][C]7.30417[/C][C]0.207639[/C][C]-0.511806[/C][/ROW]
[ROW][C]22[/C][C]7[/C][C]7.13611[/C][C]7.19167[/C][C]-0.0555556[/C][C]-0.136111[/C][/ROW]
[ROW][C]23[/C][C]7[/C][C]6.85486[/C][C]7.05833[/C][C]-0.203472[/C][C]0.145139[/C][/ROW]
[ROW][C]24[/C][C]7.2[/C][C]6.90833[/C][C]6.9625[/C][C]-0.0541667[/C][C]0.291667[/C][/ROW]
[ROW][C]25[/C][C]7.3[/C][C]7.13264[/C][C]6.94167[/C][C]0.190972[/C][C]0.167361[/C][/ROW]
[ROW][C]26[/C][C]7.1[/C][C]7.15625[/C][C]6.975[/C][C]0.18125[/C][C]-0.05625[/C][/ROW]
[ROW][C]27[/C][C]6.8[/C][C]7.02222[/C][C]7.02083[/C][C]0.00138889[/C][C]-0.222222[/C][/ROW]
[ROW][C]28[/C][C]6.4[/C][C]6.85625[/C][C]7.0375[/C][C]-0.18125[/C][C]-0.45625[/C][/ROW]
[ROW][C]29[/C][C]6.1[/C][C]6.58194[/C][C]7.01667[/C][C]-0.434722[/C][C]-0.481944[/C][/ROW]
[ROW][C]30[/C][C]6.5[/C][C]6.56319[/C][C]6.9875[/C][C]-0.424306[/C][C]-0.0631944[/C][/ROW]
[ROW][C]31[/C][C]7.7[/C][C]7.34306[/C][C]6.99167[/C][C]0.351389[/C][C]0.356944[/C][/ROW]
[ROW][C]32[/C][C]7.9[/C][C]7.46667[/C][C]7.04583[/C][C]0.420833[/C][C]0.433333[/C][/ROW]
[ROW][C]33[/C][C]7.5[/C][C]7.34097[/C][C]7.13333[/C][C]0.207639[/C][C]0.159028[/C][/ROW]
[ROW][C]34[/C][C]6.9[/C][C]7.18194[/C][C]7.2375[/C][C]-0.0555556[/C][C]-0.281944[/C][/ROW]
[ROW][C]35[/C][C]6.6[/C][C]7.13819[/C][C]7.34167[/C][C]-0.203472[/C][C]-0.538194[/C][/ROW]
[ROW][C]36[/C][C]6.9[/C][C]7.375[/C][C]7.42917[/C][C]-0.0541667[/C][C]-0.475[/C][/ROW]
[ROW][C]37[/C][C]7.7[/C][C]7.67431[/C][C]7.48333[/C][C]0.190972[/C][C]0.0256944[/C][/ROW]
[ROW][C]38[/C][C]8[/C][C]7.69792[/C][C]7.51667[/C][C]0.18125[/C][C]0.302083[/C][/ROW]
[ROW][C]39[/C][C]8[/C][C]7.55972[/C][C]7.55833[/C][C]0.00138889[/C][C]0.440278[/C][/ROW]
[ROW][C]40[/C][C]7.7[/C][C]7.44375[/C][C]7.625[/C][C]-0.18125[/C][C]0.25625[/C][/ROW]
[ROW][C]41[/C][C]7.3[/C][C]7.28611[/C][C]7.72083[/C][C]-0.434722[/C][C]0.0138889[/C][/ROW]
[ROW][C]42[/C][C]7.4[/C][C]7.40903[/C][C]7.83333[/C][C]-0.424306[/C][C]-0.00902778[/C][/ROW]
[ROW][C]43[/C][C]8.1[/C][C]8.28056[/C][C]7.92917[/C][C]0.351389[/C][C]-0.180556[/C][/ROW]
[ROW][C]44[/C][C]8.3[/C][C]8.41667[/C][C]7.99583[/C][C]0.420833[/C][C]-0.116667[/C][/ROW]
[ROW][C]45[/C][C]8.1[/C][C]8.25347[/C][C]8.04583[/C][C]0.207639[/C][C]-0.153472[/C][/ROW]
[ROW][C]46[/C][C]7.9[/C][C]8.03611[/C][C]8.09167[/C][C]-0.0555556[/C][C]-0.136111[/C][/ROW]
[ROW][C]47[/C][C]7.9[/C][C]7.94236[/C][C]8.14583[/C][C]-0.203472[/C][C]-0.0423611[/C][/ROW]
[ROW][C]48[/C][C]8.3[/C][C]8.14583[/C][C]8.2[/C][C]-0.0541667[/C][C]0.154167[/C][/ROW]
[ROW][C]49[/C][C]8.6[/C][C]8.44514[/C][C]8.25417[/C][C]0.190972[/C][C]0.154861[/C][/ROW]
[ROW][C]50[/C][C]8.7[/C][C]8.48125[/C][C]8.3[/C][C]0.18125[/C][C]0.21875[/C][/ROW]
[ROW][C]51[/C][C]8.5[/C][C]8.33472[/C][C]8.33333[/C][C]0.00138889[/C][C]0.165278[/C][/ROW]
[ROW][C]52[/C][C]8.3[/C][C]8.17708[/C][C]8.35833[/C][C]-0.18125[/C][C]0.122917[/C][/ROW]
[ROW][C]53[/C][C]8[/C][C]7.92778[/C][C]8.3625[/C][C]-0.434722[/C][C]0.0722222[/C][/ROW]
[ROW][C]54[/C][C]8[/C][C]7.90903[/C][C]8.33333[/C][C]-0.424306[/C][C]0.0909722[/C][/ROW]
[ROW][C]55[/C][C]8.8[/C][C]8.61389[/C][C]8.2625[/C][C]0.351389[/C][C]0.186111[/C][/ROW]
[ROW][C]56[/C][C]8.7[/C][C]8.575[/C][C]8.15417[/C][C]0.420833[/C][C]0.125[/C][/ROW]
[ROW][C]57[/C][C]8.5[/C][C]8.23264[/C][C]8.025[/C][C]0.207639[/C][C]0.267361[/C][/ROW]
[ROW][C]58[/C][C]8.1[/C][C]7.83194[/C][C]7.8875[/C][C]-0.0555556[/C][C]0.268056[/C][/ROW]
[ROW][C]59[/C][C]7.8[/C][C]7.55069[/C][C]7.75417[/C][C]-0.203472[/C][C]0.249306[/C][/ROW]
[ROW][C]60[/C][C]7.7[/C][C]7.57917[/C][C]7.63333[/C][C]-0.0541667[/C][C]0.120833[/C][/ROW]
[ROW][C]61[/C][C]7.5[/C][C]7.72014[/C][C]7.52917[/C][C]0.190972[/C][C]-0.220139[/C][/ROW]
[ROW][C]62[/C][C]7.2[/C][C]7.63542[/C][C]7.45417[/C][C]0.18125[/C][C]-0.435417[/C][/ROW]
[ROW][C]63[/C][C]6.9[/C][C]7.39306[/C][C]7.39167[/C][C]0.00138889[/C][C]-0.493056[/C][/ROW]
[ROW][C]64[/C][C]6.6[/C][C]7.14375[/C][C]7.325[/C][C]-0.18125[/C][C]-0.54375[/C][/ROW]
[ROW][C]65[/C][C]6.5[/C][C]6.82361[/C][C]7.25833[/C][C]-0.434722[/C][C]-0.323611[/C][/ROW]
[ROW][C]66[/C][C]6.6[/C][C]6.77153[/C][C]7.19583[/C][C]-0.424306[/C][C]-0.171528[/C][/ROW]
[ROW][C]67[/C][C]7.7[/C][C]7.50972[/C][C]7.15833[/C][C]0.351389[/C][C]0.190278[/C][/ROW]
[ROW][C]68[/C][C]8[/C][C]7.575[/C][C]7.15417[/C][C]0.420833[/C][C]0.425[/C][/ROW]
[ROW][C]69[/C][C]7.7[/C][C]7.37431[/C][C]7.16667[/C][C]0.207639[/C][C]0.325694[/C][/ROW]
[ROW][C]70[/C][C]7.3[/C][C]7.14028[/C][C]7.19583[/C][C]-0.0555556[/C][C]0.159722[/C][/ROW]
[ROW][C]71[/C][C]7[/C][C]7.03403[/C][C]7.2375[/C][C]-0.203472[/C][C]-0.0340278[/C][/ROW]
[ROW][C]72[/C][C]7[/C][C]7.22083[/C][C]7.275[/C][C]-0.0541667[/C][C]-0.220833[/C][/ROW]
[ROW][C]73[/C][C]7.3[/C][C]7.47431[/C][C]7.28333[/C][C]0.190972[/C][C]-0.174306[/C][/ROW]
[ROW][C]74[/C][C]7.3[/C][C]7.44792[/C][C]7.26667[/C][C]0.18125[/C][C]-0.147917[/C][/ROW]
[ROW][C]75[/C][C]7.1[/C][C]7.26806[/C][C]7.26667[/C][C]0.00138889[/C][C]-0.168056[/C][/ROW]
[ROW][C]76[/C][C]7.1[/C][C]7.12708[/C][C]7.30833[/C][C]-0.18125[/C][C]-0.0270833[/C][/ROW]
[ROW][C]77[/C][C]7[/C][C]6.96111[/C][C]7.39583[/C][C]-0.434722[/C][C]0.0388889[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]7.08403[/C][C]7.50833[/C][C]-0.424306[/C][C]-0.0840278[/C][/ROW]
[ROW][C]79[/C][C]7.5[/C][C]NA[/C][C]NA[/C][C]0.351389[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]7.8[/C][C]NA[/C][C]NA[/C][C]0.420833[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]7.9[/C][C]NA[/C][C]NA[/C][C]0.207639[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]8.1[/C][C]NA[/C][C]NA[/C][C]-0.0555556[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]8.3[/C][C]NA[/C][C]NA[/C][C]-0.203472[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]8.4[/C][C]NA[/C][C]NA[/C][C]-0.0541667[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235203&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235203&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	8.7	NA	NA	0.190972	NA
2	8.7	NA	NA	0.18125	NA
3	8.6	NA	NA	0.00138889	NA
4	8.5	NA	NA	-0.18125	NA
5	8.3	NA	NA	-0.434722	NA
6	8	NA	NA	-0.424306	NA
7	8.2	8.57222	8.22083	0.351389	-0.372222
8	8.1	8.58333	8.1625	0.420833	-0.483333
9	8.1	8.31181	8.10417	0.207639	-0.211806
10	8	7.99861	8.05417	-0.0555556	0.00138889
11	7.9	7.80486	8.00833	-0.203472	0.0951389
12	7.9	7.89583	7.95	-0.0541667	0.00416667
13	8	8.07847	7.8875	0.190972	-0.0784722
14	8	8.00625	7.825	0.18125	-0.00625
15	7.9	7.74722	7.74583	0.00138889	0.152778
16	8	7.47708	7.65833	-0.18125	0.522917
17	7.7	7.14444	7.57917	-0.434722	0.555556
18	7.2	7.08819	7.5125	-0.424306	0.111806
19	7.5	7.80556	7.45417	0.351389	-0.305556
20	7.3	7.80833	7.3875	0.420833	-0.508333
21	7	7.51181	7.30417	0.207639	-0.511806
22	7	7.13611	7.19167	-0.0555556	-0.136111
23	7	6.85486	7.05833	-0.203472	0.145139
24	7.2	6.90833	6.9625	-0.0541667	0.291667
25	7.3	7.13264	6.94167	0.190972	0.167361
26	7.1	7.15625	6.975	0.18125	-0.05625
27	6.8	7.02222	7.02083	0.00138889	-0.222222
28	6.4	6.85625	7.0375	-0.18125	-0.45625
29	6.1	6.58194	7.01667	-0.434722	-0.481944
30	6.5	6.56319	6.9875	-0.424306	-0.0631944
31	7.7	7.34306	6.99167	0.351389	0.356944
32	7.9	7.46667	7.04583	0.420833	0.433333
33	7.5	7.34097	7.13333	0.207639	0.159028
34	6.9	7.18194	7.2375	-0.0555556	-0.281944
35	6.6	7.13819	7.34167	-0.203472	-0.538194
36	6.9	7.375	7.42917	-0.0541667	-0.475
37	7.7	7.67431	7.48333	0.190972	0.0256944
38	8	7.69792	7.51667	0.18125	0.302083
39	8	7.55972	7.55833	0.00138889	0.440278
40	7.7	7.44375	7.625	-0.18125	0.25625
41	7.3	7.28611	7.72083	-0.434722	0.0138889
42	7.4	7.40903	7.83333	-0.424306	-0.00902778
43	8.1	8.28056	7.92917	0.351389	-0.180556
44	8.3	8.41667	7.99583	0.420833	-0.116667
45	8.1	8.25347	8.04583	0.207639	-0.153472
46	7.9	8.03611	8.09167	-0.0555556	-0.136111
47	7.9	7.94236	8.14583	-0.203472	-0.0423611
48	8.3	8.14583	8.2	-0.0541667	0.154167
49	8.6	8.44514	8.25417	0.190972	0.154861
50	8.7	8.48125	8.3	0.18125	0.21875
51	8.5	8.33472	8.33333	0.00138889	0.165278
52	8.3	8.17708	8.35833	-0.18125	0.122917
53	8	7.92778	8.3625	-0.434722	0.0722222
54	8	7.90903	8.33333	-0.424306	0.0909722
55	8.8	8.61389	8.2625	0.351389	0.186111
56	8.7	8.575	8.15417	0.420833	0.125
57	8.5	8.23264	8.025	0.207639	0.267361
58	8.1	7.83194	7.8875	-0.0555556	0.268056
59	7.8	7.55069	7.75417	-0.203472	0.249306
60	7.7	7.57917	7.63333	-0.0541667	0.120833
61	7.5	7.72014	7.52917	0.190972	-0.220139
62	7.2	7.63542	7.45417	0.18125	-0.435417
63	6.9	7.39306	7.39167	0.00138889	-0.493056
64	6.6	7.14375	7.325	-0.18125	-0.54375
65	6.5	6.82361	7.25833	-0.434722	-0.323611
66	6.6	6.77153	7.19583	-0.424306	-0.171528
67	7.7	7.50972	7.15833	0.351389	0.190278
68	8	7.575	7.15417	0.420833	0.425
69	7.7	7.37431	7.16667	0.207639	0.325694
70	7.3	7.14028	7.19583	-0.0555556	0.159722
71	7	7.03403	7.2375	-0.203472	-0.0340278
72	7	7.22083	7.275	-0.0541667	-0.220833
73	7.3	7.47431	7.28333	0.190972	-0.174306
74	7.3	7.44792	7.26667	0.18125	-0.147917
75	7.1	7.26806	7.26667	0.00138889	-0.168056
76	7.1	7.12708	7.30833	-0.18125	-0.0270833
77	7	6.96111	7.39583	-0.434722	0.0388889
78	7	7.08403	7.50833	-0.424306	-0.0840278
79	7.5	NA	NA	0.351389	NA
80	7.8	NA	NA	0.420833	NA
81	7.9	NA	NA	0.207639	NA
82	8.1	NA	NA	-0.0555556	NA
83	8.3	NA	NA	-0.203472	NA
84	8.4	NA	NA	-0.0541667	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