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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sat, 29 Nov 2014 10:58:14 +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/2014/Nov/29/t1417258866eyqcxez8hescwkk.htm/, Retrieved Sun, 19 May 2024 15:22:07 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261080, Retrieved Sun, 19 May 2024 15:22:07 +0000

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105

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-       [Classical Decomposition] [paper 10] [2014-11-29 10:58:14] [7e6d0f152da1c8c00143095b938e0e97] [Current]

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

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=261080&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=261080&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261080&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	4.8	NA	NA	0.354963	NA
2	4	NA	NA	-0.145037	NA
3	3.5	3.68805	4.0125	-0.324449	-0.188051
4	4.1	4.01452	3.9	0.114522	0.0854779
5	4.1	4.22996	3.875	0.354963	-0.129963
6	3.8	3.72996	3.875	-0.145037	0.0700368
7	3.5	3.60055	3.925	-0.324449	-0.100551
8	4.1	4.12702	4.0125	0.114522	-0.0270221
9	4.5	4.44246	4.0875	0.354963	0.0575368
10	4.1	4.04246	4.1875	-0.145037	0.0575368
11	3.8	4.01305	4.3375	-0.324449	-0.213051
12	4.6	4.57702	4.4625	0.114522	0.0229779
13	5.2	4.91746	4.5625	0.354963	0.282537
14	4.4	4.49246	4.6375	-0.145037	-0.0924632
15	4.3	4.31305	4.6375	-0.324449	-0.0130515
16	4.7	4.76452	4.65	0.114522	-0.0645221
17	5.1	5.07996	4.725	0.354963	0.0200368
18	4.6	4.65496	4.8	-0.145037	-0.0549632
19	4.7	4.50055	4.825	-0.324449	0.199449
20	4.9	4.93952	4.825	0.114522	-0.0395221
21	5.1	5.16746	4.8125	0.354963	-0.0674632
22	4.6	4.64246	4.7875	-0.145037	-0.0424632
23	4.6	4.45055	4.775	-0.324449	0.149449
24	4.8	4.91452	4.8	0.114522	-0.114522
25	5.1	5.15496	4.8	0.354963	-0.0549632
26	4.8	4.62996	4.775	-0.145037	0.170037
27	4.4	4.40055	4.725	-0.324449	-0.000551471
28	4.8	4.68952	4.575	0.114522	0.110478
29	4.7	4.71746	4.3625	0.354963	-0.0174632
30	4	4.00496	4.15	-0.145037	-0.00496324
31	3.5	3.60055	3.925	-0.324449	-0.100551
32	4	3.80202	3.6875	0.114522	0.197978
33	3.7	3.85496	3.5	0.354963	-0.154963
34	3.1	3.19246	3.3375	-0.145037	-0.0924632
35	2.9	2.90055	3.225	-0.324449	-0.000551471
36	3.3	3.30202	3.1875	0.114522	-0.00202206
37	3.5	3.50496	3.15	0.354963	-0.00496324
38	3	2.96746	3.1125	-0.145037	0.0325368
39	2.7	2.81305	3.1375	-0.324449	-0.113051
40	3.2	3.32702	3.2125	0.114522	-0.127022
41	3.8	3.65496	3.3	0.354963	0.145037
42	3.3	3.24246	3.3875	-0.145037	0.0575368
43	3.1	3.11305	3.4375	-0.324449	-0.0130515
44	3.5	3.57702	3.4625	0.114522	-0.0770221
45	3.9	3.84246	3.4875	0.354963	0.0575368
46	3.4	3.36746	3.5125	-0.145037	0.0325368
47	3.2	3.20055	3.525	-0.324449	-0.000551471
48	3.6	3.61452	3.5	0.114522	-0.0145221
49	3.9	3.80496	3.45	0.354963	0.0950368
50	3.2	3.25496	3.4	-0.145037	-0.0549632
51	3	3.01305	3.3375	-0.324449	-0.0130515
52	3.4	3.38952	3.275	0.114522	0.0104779
53	3.6	3.60496	3.25	0.354963	-0.00496324
54	3	3.12996	3.275	-0.145037	-0.129963
55	3	2.97555	3.3	-0.324449	0.0244485
56	3.6	3.45202	3.3375	0.114522	0.147978
57	3.6	3.76746	3.4125	0.354963	-0.167463
58	3.3	3.30496	3.45	-0.145037	-0.00496324
59	3.3	3.15055	3.475	-0.324449	0.149449
60	3.6	3.61452	3.5	0.114522	-0.0145221
61	3.8	3.82996	3.475	0.354963	-0.0299632
62	3.3	3.27996	3.425	-0.145037	0.0200368
63	3.1	3.03805	3.3625	-0.324449	0.0619485
64	3.4	3.41452	3.3	0.114522	-0.0145221
65	3.5	3.61746	3.2625	0.354963	-0.117463
66	3.1	3.09246	3.2375	-0.145037	0.00753676
67	3	2.92555	3.25	-0.324449	0.0744485
68	3.3	3.38952	3.275	0.114522	-0.0895221
69	3.7	3.61746	3.2625	0.354963	0.0825368
70	3.1	3.07996	3.225	-0.145037	0.0200368
71	2.9	2.81305	3.1375	-0.324449	0.0869485
72	3.1	NA	NA	0.114522	NA
73	3.2	NA	NA	0.354963	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 4.8 & NA & NA & 0.354963 & NA \tabularnewline
2 & 4 & NA & NA & -0.145037 & NA \tabularnewline
3 & 3.5 & 3.68805 & 4.0125 & -0.324449 & -0.188051 \tabularnewline
4 & 4.1 & 4.01452 & 3.9 & 0.114522 & 0.0854779 \tabularnewline
5 & 4.1 & 4.22996 & 3.875 & 0.354963 & -0.129963 \tabularnewline
6 & 3.8 & 3.72996 & 3.875 & -0.145037 & 0.0700368 \tabularnewline
7 & 3.5 & 3.60055 & 3.925 & -0.324449 & -0.100551 \tabularnewline
8 & 4.1 & 4.12702 & 4.0125 & 0.114522 & -0.0270221 \tabularnewline
9 & 4.5 & 4.44246 & 4.0875 & 0.354963 & 0.0575368 \tabularnewline
10 & 4.1 & 4.04246 & 4.1875 & -0.145037 & 0.0575368 \tabularnewline
11 & 3.8 & 4.01305 & 4.3375 & -0.324449 & -0.213051 \tabularnewline
12 & 4.6 & 4.57702 & 4.4625 & 0.114522 & 0.0229779 \tabularnewline
13 & 5.2 & 4.91746 & 4.5625 & 0.354963 & 0.282537 \tabularnewline
14 & 4.4 & 4.49246 & 4.6375 & -0.145037 & -0.0924632 \tabularnewline
15 & 4.3 & 4.31305 & 4.6375 & -0.324449 & -0.0130515 \tabularnewline
16 & 4.7 & 4.76452 & 4.65 & 0.114522 & -0.0645221 \tabularnewline
17 & 5.1 & 5.07996 & 4.725 & 0.354963 & 0.0200368 \tabularnewline
18 & 4.6 & 4.65496 & 4.8 & -0.145037 & -0.0549632 \tabularnewline
19 & 4.7 & 4.50055 & 4.825 & -0.324449 & 0.199449 \tabularnewline
20 & 4.9 & 4.93952 & 4.825 & 0.114522 & -0.0395221 \tabularnewline
21 & 5.1 & 5.16746 & 4.8125 & 0.354963 & -0.0674632 \tabularnewline
22 & 4.6 & 4.64246 & 4.7875 & -0.145037 & -0.0424632 \tabularnewline
23 & 4.6 & 4.45055 & 4.775 & -0.324449 & 0.149449 \tabularnewline
24 & 4.8 & 4.91452 & 4.8 & 0.114522 & -0.114522 \tabularnewline
25 & 5.1 & 5.15496 & 4.8 & 0.354963 & -0.0549632 \tabularnewline
26 & 4.8 & 4.62996 & 4.775 & -0.145037 & 0.170037 \tabularnewline
27 & 4.4 & 4.40055 & 4.725 & -0.324449 & -0.000551471 \tabularnewline
28 & 4.8 & 4.68952 & 4.575 & 0.114522 & 0.110478 \tabularnewline
29 & 4.7 & 4.71746 & 4.3625 & 0.354963 & -0.0174632 \tabularnewline
30 & 4 & 4.00496 & 4.15 & -0.145037 & -0.00496324 \tabularnewline
31 & 3.5 & 3.60055 & 3.925 & -0.324449 & -0.100551 \tabularnewline
32 & 4 & 3.80202 & 3.6875 & 0.114522 & 0.197978 \tabularnewline
33 & 3.7 & 3.85496 & 3.5 & 0.354963 & -0.154963 \tabularnewline
34 & 3.1 & 3.19246 & 3.3375 & -0.145037 & -0.0924632 \tabularnewline
35 & 2.9 & 2.90055 & 3.225 & -0.324449 & -0.000551471 \tabularnewline
36 & 3.3 & 3.30202 & 3.1875 & 0.114522 & -0.00202206 \tabularnewline
37 & 3.5 & 3.50496 & 3.15 & 0.354963 & -0.00496324 \tabularnewline
38 & 3 & 2.96746 & 3.1125 & -0.145037 & 0.0325368 \tabularnewline
39 & 2.7 & 2.81305 & 3.1375 & -0.324449 & -0.113051 \tabularnewline
40 & 3.2 & 3.32702 & 3.2125 & 0.114522 & -0.127022 \tabularnewline
41 & 3.8 & 3.65496 & 3.3 & 0.354963 & 0.145037 \tabularnewline
42 & 3.3 & 3.24246 & 3.3875 & -0.145037 & 0.0575368 \tabularnewline
43 & 3.1 & 3.11305 & 3.4375 & -0.324449 & -0.0130515 \tabularnewline
44 & 3.5 & 3.57702 & 3.4625 & 0.114522 & -0.0770221 \tabularnewline
45 & 3.9 & 3.84246 & 3.4875 & 0.354963 & 0.0575368 \tabularnewline
46 & 3.4 & 3.36746 & 3.5125 & -0.145037 & 0.0325368 \tabularnewline
47 & 3.2 & 3.20055 & 3.525 & -0.324449 & -0.000551471 \tabularnewline
48 & 3.6 & 3.61452 & 3.5 & 0.114522 & -0.0145221 \tabularnewline
49 & 3.9 & 3.80496 & 3.45 & 0.354963 & 0.0950368 \tabularnewline
50 & 3.2 & 3.25496 & 3.4 & -0.145037 & -0.0549632 \tabularnewline
51 & 3 & 3.01305 & 3.3375 & -0.324449 & -0.0130515 \tabularnewline
52 & 3.4 & 3.38952 & 3.275 & 0.114522 & 0.0104779 \tabularnewline
53 & 3.6 & 3.60496 & 3.25 & 0.354963 & -0.00496324 \tabularnewline
54 & 3 & 3.12996 & 3.275 & -0.145037 & -0.129963 \tabularnewline
55 & 3 & 2.97555 & 3.3 & -0.324449 & 0.0244485 \tabularnewline
56 & 3.6 & 3.45202 & 3.3375 & 0.114522 & 0.147978 \tabularnewline
57 & 3.6 & 3.76746 & 3.4125 & 0.354963 & -0.167463 \tabularnewline
58 & 3.3 & 3.30496 & 3.45 & -0.145037 & -0.00496324 \tabularnewline
59 & 3.3 & 3.15055 & 3.475 & -0.324449 & 0.149449 \tabularnewline
60 & 3.6 & 3.61452 & 3.5 & 0.114522 & -0.0145221 \tabularnewline
61 & 3.8 & 3.82996 & 3.475 & 0.354963 & -0.0299632 \tabularnewline
62 & 3.3 & 3.27996 & 3.425 & -0.145037 & 0.0200368 \tabularnewline
63 & 3.1 & 3.03805 & 3.3625 & -0.324449 & 0.0619485 \tabularnewline
64 & 3.4 & 3.41452 & 3.3 & 0.114522 & -0.0145221 \tabularnewline
65 & 3.5 & 3.61746 & 3.2625 & 0.354963 & -0.117463 \tabularnewline
66 & 3.1 & 3.09246 & 3.2375 & -0.145037 & 0.00753676 \tabularnewline
67 & 3 & 2.92555 & 3.25 & -0.324449 & 0.0744485 \tabularnewline
68 & 3.3 & 3.38952 & 3.275 & 0.114522 & -0.0895221 \tabularnewline
69 & 3.7 & 3.61746 & 3.2625 & 0.354963 & 0.0825368 \tabularnewline
70 & 3.1 & 3.07996 & 3.225 & -0.145037 & 0.0200368 \tabularnewline
71 & 2.9 & 2.81305 & 3.1375 & -0.324449 & 0.0869485 \tabularnewline
72 & 3.1 & NA & NA & 0.114522 & NA \tabularnewline
73 & 3.2 & NA & NA & 0.354963 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261080&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]4.8[/C][C]NA[/C][C]NA[/C][C]0.354963[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]4[/C][C]NA[/C][C]NA[/C][C]-0.145037[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3.5[/C][C]3.68805[/C][C]4.0125[/C][C]-0.324449[/C][C]-0.188051[/C][/ROW]
[ROW][C]4[/C][C]4.1[/C][C]4.01452[/C][C]3.9[/C][C]0.114522[/C][C]0.0854779[/C][/ROW]
[ROW][C]5[/C][C]4.1[/C][C]4.22996[/C][C]3.875[/C][C]0.354963[/C][C]-0.129963[/C][/ROW]
[ROW][C]6[/C][C]3.8[/C][C]3.72996[/C][C]3.875[/C][C]-0.145037[/C][C]0.0700368[/C][/ROW]
[ROW][C]7[/C][C]3.5[/C][C]3.60055[/C][C]3.925[/C][C]-0.324449[/C][C]-0.100551[/C][/ROW]
[ROW][C]8[/C][C]4.1[/C][C]4.12702[/C][C]4.0125[/C][C]0.114522[/C][C]-0.0270221[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]4.44246[/C][C]4.0875[/C][C]0.354963[/C][C]0.0575368[/C][/ROW]
[ROW][C]10[/C][C]4.1[/C][C]4.04246[/C][C]4.1875[/C][C]-0.145037[/C][C]0.0575368[/C][/ROW]
[ROW][C]11[/C][C]3.8[/C][C]4.01305[/C][C]4.3375[/C][C]-0.324449[/C][C]-0.213051[/C][/ROW]
[ROW][C]12[/C][C]4.6[/C][C]4.57702[/C][C]4.4625[/C][C]0.114522[/C][C]0.0229779[/C][/ROW]
[ROW][C]13[/C][C]5.2[/C][C]4.91746[/C][C]4.5625[/C][C]0.354963[/C][C]0.282537[/C][/ROW]
[ROW][C]14[/C][C]4.4[/C][C]4.49246[/C][C]4.6375[/C][C]-0.145037[/C][C]-0.0924632[/C][/ROW]
[ROW][C]15[/C][C]4.3[/C][C]4.31305[/C][C]4.6375[/C][C]-0.324449[/C][C]-0.0130515[/C][/ROW]
[ROW][C]16[/C][C]4.7[/C][C]4.76452[/C][C]4.65[/C][C]0.114522[/C][C]-0.0645221[/C][/ROW]
[ROW][C]17[/C][C]5.1[/C][C]5.07996[/C][C]4.725[/C][C]0.354963[/C][C]0.0200368[/C][/ROW]
[ROW][C]18[/C][C]4.6[/C][C]4.65496[/C][C]4.8[/C][C]-0.145037[/C][C]-0.0549632[/C][/ROW]
[ROW][C]19[/C][C]4.7[/C][C]4.50055[/C][C]4.825[/C][C]-0.324449[/C][C]0.199449[/C][/ROW]
[ROW][C]20[/C][C]4.9[/C][C]4.93952[/C][C]4.825[/C][C]0.114522[/C][C]-0.0395221[/C][/ROW]
[ROW][C]21[/C][C]5.1[/C][C]5.16746[/C][C]4.8125[/C][C]0.354963[/C][C]-0.0674632[/C][/ROW]
[ROW][C]22[/C][C]4.6[/C][C]4.64246[/C][C]4.7875[/C][C]-0.145037[/C][C]-0.0424632[/C][/ROW]
[ROW][C]23[/C][C]4.6[/C][C]4.45055[/C][C]4.775[/C][C]-0.324449[/C][C]0.149449[/C][/ROW]
[ROW][C]24[/C][C]4.8[/C][C]4.91452[/C][C]4.8[/C][C]0.114522[/C][C]-0.114522[/C][/ROW]
[ROW][C]25[/C][C]5.1[/C][C]5.15496[/C][C]4.8[/C][C]0.354963[/C][C]-0.0549632[/C][/ROW]
[ROW][C]26[/C][C]4.8[/C][C]4.62996[/C][C]4.775[/C][C]-0.145037[/C][C]0.170037[/C][/ROW]
[ROW][C]27[/C][C]4.4[/C][C]4.40055[/C][C]4.725[/C][C]-0.324449[/C][C]-0.000551471[/C][/ROW]
[ROW][C]28[/C][C]4.8[/C][C]4.68952[/C][C]4.575[/C][C]0.114522[/C][C]0.110478[/C][/ROW]
[ROW][C]29[/C][C]4.7[/C][C]4.71746[/C][C]4.3625[/C][C]0.354963[/C][C]-0.0174632[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]4.00496[/C][C]4.15[/C][C]-0.145037[/C][C]-0.00496324[/C][/ROW]
[ROW][C]31[/C][C]3.5[/C][C]3.60055[/C][C]3.925[/C][C]-0.324449[/C][C]-0.100551[/C][/ROW]
[ROW][C]32[/C][C]4[/C][C]3.80202[/C][C]3.6875[/C][C]0.114522[/C][C]0.197978[/C][/ROW]
[ROW][C]33[/C][C]3.7[/C][C]3.85496[/C][C]3.5[/C][C]0.354963[/C][C]-0.154963[/C][/ROW]
[ROW][C]34[/C][C]3.1[/C][C]3.19246[/C][C]3.3375[/C][C]-0.145037[/C][C]-0.0924632[/C][/ROW]
[ROW][C]35[/C][C]2.9[/C][C]2.90055[/C][C]3.225[/C][C]-0.324449[/C][C]-0.000551471[/C][/ROW]
[ROW][C]36[/C][C]3.3[/C][C]3.30202[/C][C]3.1875[/C][C]0.114522[/C][C]-0.00202206[/C][/ROW]
[ROW][C]37[/C][C]3.5[/C][C]3.50496[/C][C]3.15[/C][C]0.354963[/C][C]-0.00496324[/C][/ROW]
[ROW][C]38[/C][C]3[/C][C]2.96746[/C][C]3.1125[/C][C]-0.145037[/C][C]0.0325368[/C][/ROW]
[ROW][C]39[/C][C]2.7[/C][C]2.81305[/C][C]3.1375[/C][C]-0.324449[/C][C]-0.113051[/C][/ROW]
[ROW][C]40[/C][C]3.2[/C][C]3.32702[/C][C]3.2125[/C][C]0.114522[/C][C]-0.127022[/C][/ROW]
[ROW][C]41[/C][C]3.8[/C][C]3.65496[/C][C]3.3[/C][C]0.354963[/C][C]0.145037[/C][/ROW]
[ROW][C]42[/C][C]3.3[/C][C]3.24246[/C][C]3.3875[/C][C]-0.145037[/C][C]0.0575368[/C][/ROW]
[ROW][C]43[/C][C]3.1[/C][C]3.11305[/C][C]3.4375[/C][C]-0.324449[/C][C]-0.0130515[/C][/ROW]
[ROW][C]44[/C][C]3.5[/C][C]3.57702[/C][C]3.4625[/C][C]0.114522[/C][C]-0.0770221[/C][/ROW]
[ROW][C]45[/C][C]3.9[/C][C]3.84246[/C][C]3.4875[/C][C]0.354963[/C][C]0.0575368[/C][/ROW]
[ROW][C]46[/C][C]3.4[/C][C]3.36746[/C][C]3.5125[/C][C]-0.145037[/C][C]0.0325368[/C][/ROW]
[ROW][C]47[/C][C]3.2[/C][C]3.20055[/C][C]3.525[/C][C]-0.324449[/C][C]-0.000551471[/C][/ROW]
[ROW][C]48[/C][C]3.6[/C][C]3.61452[/C][C]3.5[/C][C]0.114522[/C][C]-0.0145221[/C][/ROW]
[ROW][C]49[/C][C]3.9[/C][C]3.80496[/C][C]3.45[/C][C]0.354963[/C][C]0.0950368[/C][/ROW]
[ROW][C]50[/C][C]3.2[/C][C]3.25496[/C][C]3.4[/C][C]-0.145037[/C][C]-0.0549632[/C][/ROW]
[ROW][C]51[/C][C]3[/C][C]3.01305[/C][C]3.3375[/C][C]-0.324449[/C][C]-0.0130515[/C][/ROW]
[ROW][C]52[/C][C]3.4[/C][C]3.38952[/C][C]3.275[/C][C]0.114522[/C][C]0.0104779[/C][/ROW]
[ROW][C]53[/C][C]3.6[/C][C]3.60496[/C][C]3.25[/C][C]0.354963[/C][C]-0.00496324[/C][/ROW]
[ROW][C]54[/C][C]3[/C][C]3.12996[/C][C]3.275[/C][C]-0.145037[/C][C]-0.129963[/C][/ROW]
[ROW][C]55[/C][C]3[/C][C]2.97555[/C][C]3.3[/C][C]-0.324449[/C][C]0.0244485[/C][/ROW]
[ROW][C]56[/C][C]3.6[/C][C]3.45202[/C][C]3.3375[/C][C]0.114522[/C][C]0.147978[/C][/ROW]
[ROW][C]57[/C][C]3.6[/C][C]3.76746[/C][C]3.4125[/C][C]0.354963[/C][C]-0.167463[/C][/ROW]
[ROW][C]58[/C][C]3.3[/C][C]3.30496[/C][C]3.45[/C][C]-0.145037[/C][C]-0.00496324[/C][/ROW]
[ROW][C]59[/C][C]3.3[/C][C]3.15055[/C][C]3.475[/C][C]-0.324449[/C][C]0.149449[/C][/ROW]
[ROW][C]60[/C][C]3.6[/C][C]3.61452[/C][C]3.5[/C][C]0.114522[/C][C]-0.0145221[/C][/ROW]
[ROW][C]61[/C][C]3.8[/C][C]3.82996[/C][C]3.475[/C][C]0.354963[/C][C]-0.0299632[/C][/ROW]
[ROW][C]62[/C][C]3.3[/C][C]3.27996[/C][C]3.425[/C][C]-0.145037[/C][C]0.0200368[/C][/ROW]
[ROW][C]63[/C][C]3.1[/C][C]3.03805[/C][C]3.3625[/C][C]-0.324449[/C][C]0.0619485[/C][/ROW]
[ROW][C]64[/C][C]3.4[/C][C]3.41452[/C][C]3.3[/C][C]0.114522[/C][C]-0.0145221[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]3.61746[/C][C]3.2625[/C][C]0.354963[/C][C]-0.117463[/C][/ROW]
[ROW][C]66[/C][C]3.1[/C][C]3.09246[/C][C]3.2375[/C][C]-0.145037[/C][C]0.00753676[/C][/ROW]
[ROW][C]67[/C][C]3[/C][C]2.92555[/C][C]3.25[/C][C]-0.324449[/C][C]0.0744485[/C][/ROW]
[ROW][C]68[/C][C]3.3[/C][C]3.38952[/C][C]3.275[/C][C]0.114522[/C][C]-0.0895221[/C][/ROW]
[ROW][C]69[/C][C]3.7[/C][C]3.61746[/C][C]3.2625[/C][C]0.354963[/C][C]0.0825368[/C][/ROW]
[ROW][C]70[/C][C]3.1[/C][C]3.07996[/C][C]3.225[/C][C]-0.145037[/C][C]0.0200368[/C][/ROW]
[ROW][C]71[/C][C]2.9[/C][C]2.81305[/C][C]3.1375[/C][C]-0.324449[/C][C]0.0869485[/C][/ROW]
[ROW][C]72[/C][C]3.1[/C][C]NA[/C][C]NA[/C][C]0.114522[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]3.2[/C][C]NA[/C][C]NA[/C][C]0.354963[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261080&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261080&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	4.8	NA	NA	0.354963	NA
2	4	NA	NA	-0.145037	NA
3	3.5	3.68805	4.0125	-0.324449	-0.188051
4	4.1	4.01452	3.9	0.114522	0.0854779
5	4.1	4.22996	3.875	0.354963	-0.129963
6	3.8	3.72996	3.875	-0.145037	0.0700368
7	3.5	3.60055	3.925	-0.324449	-0.100551
8	4.1	4.12702	4.0125	0.114522	-0.0270221
9	4.5	4.44246	4.0875	0.354963	0.0575368
10	4.1	4.04246	4.1875	-0.145037	0.0575368
11	3.8	4.01305	4.3375	-0.324449	-0.213051
12	4.6	4.57702	4.4625	0.114522	0.0229779
13	5.2	4.91746	4.5625	0.354963	0.282537
14	4.4	4.49246	4.6375	-0.145037	-0.0924632
15	4.3	4.31305	4.6375	-0.324449	-0.0130515
16	4.7	4.76452	4.65	0.114522	-0.0645221
17	5.1	5.07996	4.725	0.354963	0.0200368
18	4.6	4.65496	4.8	-0.145037	-0.0549632
19	4.7	4.50055	4.825	-0.324449	0.199449
20	4.9	4.93952	4.825	0.114522	-0.0395221
21	5.1	5.16746	4.8125	0.354963	-0.0674632
22	4.6	4.64246	4.7875	-0.145037	-0.0424632
23	4.6	4.45055	4.775	-0.324449	0.149449
24	4.8	4.91452	4.8	0.114522	-0.114522
25	5.1	5.15496	4.8	0.354963	-0.0549632
26	4.8	4.62996	4.775	-0.145037	0.170037
27	4.4	4.40055	4.725	-0.324449	-0.000551471
28	4.8	4.68952	4.575	0.114522	0.110478
29	4.7	4.71746	4.3625	0.354963	-0.0174632
30	4	4.00496	4.15	-0.145037	-0.00496324
31	3.5	3.60055	3.925	-0.324449	-0.100551
32	4	3.80202	3.6875	0.114522	0.197978
33	3.7	3.85496	3.5	0.354963	-0.154963
34	3.1	3.19246	3.3375	-0.145037	-0.0924632
35	2.9	2.90055	3.225	-0.324449	-0.000551471
36	3.3	3.30202	3.1875	0.114522	-0.00202206
37	3.5	3.50496	3.15	0.354963	-0.00496324
38	3	2.96746	3.1125	-0.145037	0.0325368
39	2.7	2.81305	3.1375	-0.324449	-0.113051
40	3.2	3.32702	3.2125	0.114522	-0.127022
41	3.8	3.65496	3.3	0.354963	0.145037
42	3.3	3.24246	3.3875	-0.145037	0.0575368
43	3.1	3.11305	3.4375	-0.324449	-0.0130515
44	3.5	3.57702	3.4625	0.114522	-0.0770221
45	3.9	3.84246	3.4875	0.354963	0.0575368
46	3.4	3.36746	3.5125	-0.145037	0.0325368
47	3.2	3.20055	3.525	-0.324449	-0.000551471
48	3.6	3.61452	3.5	0.114522	-0.0145221
49	3.9	3.80496	3.45	0.354963	0.0950368
50	3.2	3.25496	3.4	-0.145037	-0.0549632
51	3	3.01305	3.3375	-0.324449	-0.0130515
52	3.4	3.38952	3.275	0.114522	0.0104779
53	3.6	3.60496	3.25	0.354963	-0.00496324
54	3	3.12996	3.275	-0.145037	-0.129963
55	3	2.97555	3.3	-0.324449	0.0244485
56	3.6	3.45202	3.3375	0.114522	0.147978
57	3.6	3.76746	3.4125	0.354963	-0.167463
58	3.3	3.30496	3.45	-0.145037	-0.00496324
59	3.3	3.15055	3.475	-0.324449	0.149449
60	3.6	3.61452	3.5	0.114522	-0.0145221
61	3.8	3.82996	3.475	0.354963	-0.0299632
62	3.3	3.27996	3.425	-0.145037	0.0200368
63	3.1	3.03805	3.3625	-0.324449	0.0619485
64	3.4	3.41452	3.3	0.114522	-0.0145221
65	3.5	3.61746	3.2625	0.354963	-0.117463
66	3.1	3.09246	3.2375	-0.145037	0.00753676
67	3	2.92555	3.25	-0.324449	0.0744485
68	3.3	3.38952	3.275	0.114522	-0.0895221
69	3.7	3.61746	3.2625	0.354963	0.0825368
70	3.1	3.07996	3.225	-0.145037	0.0200368
71	2.9	2.81305	3.1375	-0.324449	0.0869485
72	3.1	NA	NA	0.114522	NA
73	3.2	NA	NA	0.354963	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 = 4 ;

Parameters (R input):

par1 = additive ; par2 = 4 ;

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