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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 18 May 2014 18:31:20 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/May/18/t14004523637tzlworc91vxl5u.htm/, Retrieved Wed, 15 May 2024 09:27:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234919, Retrieved Wed, 15 May 2024 09:27:51 +0000

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Estimated Impact

167

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-       [Classical Decomposition] [gemiddelde prijs ...] [2014-05-18 22:31:20] [b973758fc1658916c4a7c8f7ddd22f57] [Current]

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Dataseries X:

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2,9
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3,1
3,1
3,1
3,1
3,1
3,1
3,1
3,1
3,1
3,1
3,1
3,1
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,5
3,5
3,5
3,5
3,5
3,5
3,5
3,5
3,5
3,5
3,5

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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234919&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234919&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234919&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	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2.9	NA	NA	-0.0381366	NA
2	3	NA	NA	0.0382523	NA
3	3	NA	NA	0.0313079	NA
4	3	NA	NA	0.0243634	NA
5	3	NA	NA	0.017419	NA
6	3	NA	NA	0.0104745	NA
7	3	2.99867	2.99583	0.00283565	0.00133102
8	3	2.99659	3	-0.00341435	0.00341435
9	3	2.98964	3	-0.0103588	0.0103588
10	3	2.9827	3	-0.0173032	0.0173032
11	3	2.97575	3	-0.0242477	0.0242477
12	3	2.96881	3	-0.0311921	0.0311921
13	3	2.96186	3	-0.0381366	0.0381366
14	3	3.03825	3	0.0382523	-0.0382523
15	3	3.03131	3	0.0313079	-0.0313079
16	3	3.02436	3	0.0243634	-0.0243634
17	3	3.01742	3	0.017419	-0.017419
18	3	3.01047	3	0.0104745	-0.0104745
19	3	3.00284	3	0.00283565	-0.00283565
20	3	3.00075	3.00417	-0.00341435	-0.000752315
21	3	3.00214	3.0125	-0.0103588	-0.0021412
22	3	3.00353	3.02083	-0.0173032	-0.00353009
23	3	3.00492	3.02917	-0.0242477	-0.00491898
24	3	3.00631	3.0375	-0.0311921	-0.00630787
25	3	3.0077	3.04583	-0.0381366	-0.00769676
26	3.1	3.09242	3.05417	0.0382523	0.00758102
27	3.1	3.09381	3.0625	0.0313079	0.00619213
28	3.1	3.0952	3.07083	0.0243634	0.00480324
29	3.1	3.09659	3.07917	0.017419	0.00341435
30	3.1	3.09797	3.0875	0.0104745	0.00202546
31	3.1	3.09867	3.09583	0.00283565	0.00133102
32	3.1	3.10492	3.10833	-0.00341435	-0.00491898
33	3.1	3.11464	3.125	-0.0103588	-0.0146412
34	3.1	3.12436	3.14167	-0.0173032	-0.0243634
35	3.1	3.13409	3.15833	-0.0242477	-0.0340856
36	3.1	3.14381	3.175	-0.0311921	-0.0438079
37	3.1	3.15353	3.19167	-0.0381366	-0.0535301
38	3.3	3.24659	3.20833	0.0382523	0.0534144
39	3.3	3.25631	3.225	0.0313079	0.0436921
40	3.3	3.26603	3.24167	0.0243634	0.0339699
41	3.3	3.27575	3.25833	0.017419	0.0242477
42	3.3	3.28547	3.275	0.0104745	0.0145255
43	3.3	3.2945	3.29167	0.00283565	0.00549769
44	3.3	3.29659	3.3	-0.00341435	0.00341435
45	3.3	3.28964	3.3	-0.0103588	0.0103588
46	3.3	3.2827	3.3	-0.0173032	0.0173032
47	3.3	3.27575	3.3	-0.0242477	0.0242477
48	3.3	3.26881	3.3	-0.0311921	0.0311921
49	3.3	3.26186	3.3	-0.0381366	0.0381366
50	3.3	3.33825	3.3	0.0382523	-0.0382523
51	3.3	3.33131	3.3	0.0313079	-0.0313079
52	3.3	3.32436	3.3	0.0243634	-0.0243634
53	3.3	3.31742	3.3	0.017419	-0.017419
54	3.3	3.31047	3.3	0.0104745	-0.0104745
55	3.3	3.30284	3.3	0.00283565	-0.00283565
56	3.3	3.29659	3.3	-0.00341435	0.00341435
57	3.3	3.28964	3.3	-0.0103588	0.0103588
58	3.3	3.2827	3.3	-0.0173032	0.0173032
59	3.3	3.27575	3.3	-0.0242477	0.0242477
60	3.3	3.26881	3.3	-0.0311921	0.0311921
61	3.3	3.26186	3.3	-0.0381366	0.0381366
62	3.3	3.33825	3.3	0.0382523	-0.0382523
63	3.3	3.33131	3.3	0.0313079	-0.0313079
64	3.3	3.32436	3.3	0.0243634	-0.0243634
65	3.3	3.31742	3.3	0.017419	-0.017419
66	3.3	3.31047	3.3	0.0104745	-0.0104745
67	3.3	3.30284	3.3	0.00283565	-0.00283565
68	3.3	3.30492	3.30833	-0.00341435	-0.00491898
69	3.3	3.31464	3.325	-0.0103588	-0.0146412
70	3.3	3.32436	3.34167	-0.0173032	-0.0243634
71	3.3	3.33409	3.35833	-0.0242477	-0.0340856
72	3.3	3.34381	3.375	-0.0311921	-0.0438079
73	3.3	3.35353	3.39167	-0.0381366	-0.0535301
74	3.5	3.44659	3.40833	0.0382523	0.0534144
75	3.5	3.45631	3.425	0.0313079	0.0436921
76	3.5	3.46603	3.44167	0.0243634	0.0339699
77	3.5	3.47575	3.45833	0.017419	0.0242477
78	3.5	3.48547	3.475	0.0104745	0.0145255
79	3.5	NA	NA	0.00283565	NA
80	3.5	NA	NA	-0.00341435	NA
81	3.5	NA	NA	-0.0103588	NA
82	3.5	NA	NA	-0.0173032	NA
83	3.5	NA	NA	-0.0242477	NA
84	3.5	NA	NA	-0.0311921	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.9 & NA & NA & -0.0381366 & NA \tabularnewline
2 & 3 & NA & NA & 0.0382523 & NA \tabularnewline
3 & 3 & NA & NA & 0.0313079 & NA \tabularnewline
4 & 3 & NA & NA & 0.0243634 & NA \tabularnewline
5 & 3 & NA & NA & 0.017419 & NA \tabularnewline
6 & 3 & NA & NA & 0.0104745 & NA \tabularnewline
7 & 3 & 2.99867 & 2.99583 & 0.00283565 & 0.00133102 \tabularnewline
8 & 3 & 2.99659 & 3 & -0.00341435 & 0.00341435 \tabularnewline
9 & 3 & 2.98964 & 3 & -0.0103588 & 0.0103588 \tabularnewline
10 & 3 & 2.9827 & 3 & -0.0173032 & 0.0173032 \tabularnewline
11 & 3 & 2.97575 & 3 & -0.0242477 & 0.0242477 \tabularnewline
12 & 3 & 2.96881 & 3 & -0.0311921 & 0.0311921 \tabularnewline
13 & 3 & 2.96186 & 3 & -0.0381366 & 0.0381366 \tabularnewline
14 & 3 & 3.03825 & 3 & 0.0382523 & -0.0382523 \tabularnewline
15 & 3 & 3.03131 & 3 & 0.0313079 & -0.0313079 \tabularnewline
16 & 3 & 3.02436 & 3 & 0.0243634 & -0.0243634 \tabularnewline
17 & 3 & 3.01742 & 3 & 0.017419 & -0.017419 \tabularnewline
18 & 3 & 3.01047 & 3 & 0.0104745 & -0.0104745 \tabularnewline
19 & 3 & 3.00284 & 3 & 0.00283565 & -0.00283565 \tabularnewline
20 & 3 & 3.00075 & 3.00417 & -0.00341435 & -0.000752315 \tabularnewline
21 & 3 & 3.00214 & 3.0125 & -0.0103588 & -0.0021412 \tabularnewline
22 & 3 & 3.00353 & 3.02083 & -0.0173032 & -0.00353009 \tabularnewline
23 & 3 & 3.00492 & 3.02917 & -0.0242477 & -0.00491898 \tabularnewline
24 & 3 & 3.00631 & 3.0375 & -0.0311921 & -0.00630787 \tabularnewline
25 & 3 & 3.0077 & 3.04583 & -0.0381366 & -0.00769676 \tabularnewline
26 & 3.1 & 3.09242 & 3.05417 & 0.0382523 & 0.00758102 \tabularnewline
27 & 3.1 & 3.09381 & 3.0625 & 0.0313079 & 0.00619213 \tabularnewline
28 & 3.1 & 3.0952 & 3.07083 & 0.0243634 & 0.00480324 \tabularnewline
29 & 3.1 & 3.09659 & 3.07917 & 0.017419 & 0.00341435 \tabularnewline
30 & 3.1 & 3.09797 & 3.0875 & 0.0104745 & 0.00202546 \tabularnewline
31 & 3.1 & 3.09867 & 3.09583 & 0.00283565 & 0.00133102 \tabularnewline
32 & 3.1 & 3.10492 & 3.10833 & -0.00341435 & -0.00491898 \tabularnewline
33 & 3.1 & 3.11464 & 3.125 & -0.0103588 & -0.0146412 \tabularnewline
34 & 3.1 & 3.12436 & 3.14167 & -0.0173032 & -0.0243634 \tabularnewline
35 & 3.1 & 3.13409 & 3.15833 & -0.0242477 & -0.0340856 \tabularnewline
36 & 3.1 & 3.14381 & 3.175 & -0.0311921 & -0.0438079 \tabularnewline
37 & 3.1 & 3.15353 & 3.19167 & -0.0381366 & -0.0535301 \tabularnewline
38 & 3.3 & 3.24659 & 3.20833 & 0.0382523 & 0.0534144 \tabularnewline
39 & 3.3 & 3.25631 & 3.225 & 0.0313079 & 0.0436921 \tabularnewline
40 & 3.3 & 3.26603 & 3.24167 & 0.0243634 & 0.0339699 \tabularnewline
41 & 3.3 & 3.27575 & 3.25833 & 0.017419 & 0.0242477 \tabularnewline
42 & 3.3 & 3.28547 & 3.275 & 0.0104745 & 0.0145255 \tabularnewline
43 & 3.3 & 3.2945 & 3.29167 & 0.00283565 & 0.00549769 \tabularnewline
44 & 3.3 & 3.29659 & 3.3 & -0.00341435 & 0.00341435 \tabularnewline
45 & 3.3 & 3.28964 & 3.3 & -0.0103588 & 0.0103588 \tabularnewline
46 & 3.3 & 3.2827 & 3.3 & -0.0173032 & 0.0173032 \tabularnewline
47 & 3.3 & 3.27575 & 3.3 & -0.0242477 & 0.0242477 \tabularnewline
48 & 3.3 & 3.26881 & 3.3 & -0.0311921 & 0.0311921 \tabularnewline
49 & 3.3 & 3.26186 & 3.3 & -0.0381366 & 0.0381366 \tabularnewline
50 & 3.3 & 3.33825 & 3.3 & 0.0382523 & -0.0382523 \tabularnewline
51 & 3.3 & 3.33131 & 3.3 & 0.0313079 & -0.0313079 \tabularnewline
52 & 3.3 & 3.32436 & 3.3 & 0.0243634 & -0.0243634 \tabularnewline
53 & 3.3 & 3.31742 & 3.3 & 0.017419 & -0.017419 \tabularnewline
54 & 3.3 & 3.31047 & 3.3 & 0.0104745 & -0.0104745 \tabularnewline
55 & 3.3 & 3.30284 & 3.3 & 0.00283565 & -0.00283565 \tabularnewline
56 & 3.3 & 3.29659 & 3.3 & -0.00341435 & 0.00341435 \tabularnewline
57 & 3.3 & 3.28964 & 3.3 & -0.0103588 & 0.0103588 \tabularnewline
58 & 3.3 & 3.2827 & 3.3 & -0.0173032 & 0.0173032 \tabularnewline
59 & 3.3 & 3.27575 & 3.3 & -0.0242477 & 0.0242477 \tabularnewline
60 & 3.3 & 3.26881 & 3.3 & -0.0311921 & 0.0311921 \tabularnewline
61 & 3.3 & 3.26186 & 3.3 & -0.0381366 & 0.0381366 \tabularnewline
62 & 3.3 & 3.33825 & 3.3 & 0.0382523 & -0.0382523 \tabularnewline
63 & 3.3 & 3.33131 & 3.3 & 0.0313079 & -0.0313079 \tabularnewline
64 & 3.3 & 3.32436 & 3.3 & 0.0243634 & -0.0243634 \tabularnewline
65 & 3.3 & 3.31742 & 3.3 & 0.017419 & -0.017419 \tabularnewline
66 & 3.3 & 3.31047 & 3.3 & 0.0104745 & -0.0104745 \tabularnewline
67 & 3.3 & 3.30284 & 3.3 & 0.00283565 & -0.00283565 \tabularnewline
68 & 3.3 & 3.30492 & 3.30833 & -0.00341435 & -0.00491898 \tabularnewline
69 & 3.3 & 3.31464 & 3.325 & -0.0103588 & -0.0146412 \tabularnewline
70 & 3.3 & 3.32436 & 3.34167 & -0.0173032 & -0.0243634 \tabularnewline
71 & 3.3 & 3.33409 & 3.35833 & -0.0242477 & -0.0340856 \tabularnewline
72 & 3.3 & 3.34381 & 3.375 & -0.0311921 & -0.0438079 \tabularnewline
73 & 3.3 & 3.35353 & 3.39167 & -0.0381366 & -0.0535301 \tabularnewline
74 & 3.5 & 3.44659 & 3.40833 & 0.0382523 & 0.0534144 \tabularnewline
75 & 3.5 & 3.45631 & 3.425 & 0.0313079 & 0.0436921 \tabularnewline
76 & 3.5 & 3.46603 & 3.44167 & 0.0243634 & 0.0339699 \tabularnewline
77 & 3.5 & 3.47575 & 3.45833 & 0.017419 & 0.0242477 \tabularnewline
78 & 3.5 & 3.48547 & 3.475 & 0.0104745 & 0.0145255 \tabularnewline
79 & 3.5 & NA & NA & 0.00283565 & NA \tabularnewline
80 & 3.5 & NA & NA & -0.00341435 & NA \tabularnewline
81 & 3.5 & NA & NA & -0.0103588 & NA \tabularnewline
82 & 3.5 & NA & NA & -0.0173032 & NA \tabularnewline
83 & 3.5 & NA & NA & -0.0242477 & NA \tabularnewline
84 & 3.5 & NA & NA & -0.0311921 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234919&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]2.9[/C][C]NA[/C][C]NA[/C][C]-0.0381366[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3[/C][C]NA[/C][C]NA[/C][C]0.0382523[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3[/C][C]NA[/C][C]NA[/C][C]0.0313079[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3[/C][C]NA[/C][C]NA[/C][C]0.0243634[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]3[/C][C]NA[/C][C]NA[/C][C]0.017419[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3[/C][C]NA[/C][C]NA[/C][C]0.0104745[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]3[/C][C]2.99867[/C][C]2.99583[/C][C]0.00283565[/C][C]0.00133102[/C][/ROW]
[ROW][C]8[/C][C]3[/C][C]2.99659[/C][C]3[/C][C]-0.00341435[/C][C]0.00341435[/C][/ROW]
[ROW][C]9[/C][C]3[/C][C]2.98964[/C][C]3[/C][C]-0.0103588[/C][C]0.0103588[/C][/ROW]
[ROW][C]10[/C][C]3[/C][C]2.9827[/C][C]3[/C][C]-0.0173032[/C][C]0.0173032[/C][/ROW]
[ROW][C]11[/C][C]3[/C][C]2.97575[/C][C]3[/C][C]-0.0242477[/C][C]0.0242477[/C][/ROW]
[ROW][C]12[/C][C]3[/C][C]2.96881[/C][C]3[/C][C]-0.0311921[/C][C]0.0311921[/C][/ROW]
[ROW][C]13[/C][C]3[/C][C]2.96186[/C][C]3[/C][C]-0.0381366[/C][C]0.0381366[/C][/ROW]
[ROW][C]14[/C][C]3[/C][C]3.03825[/C][C]3[/C][C]0.0382523[/C][C]-0.0382523[/C][/ROW]
[ROW][C]15[/C][C]3[/C][C]3.03131[/C][C]3[/C][C]0.0313079[/C][C]-0.0313079[/C][/ROW]
[ROW][C]16[/C][C]3[/C][C]3.02436[/C][C]3[/C][C]0.0243634[/C][C]-0.0243634[/C][/ROW]
[ROW][C]17[/C][C]3[/C][C]3.01742[/C][C]3[/C][C]0.017419[/C][C]-0.017419[/C][/ROW]
[ROW][C]18[/C][C]3[/C][C]3.01047[/C][C]3[/C][C]0.0104745[/C][C]-0.0104745[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]3.00284[/C][C]3[/C][C]0.00283565[/C][C]-0.00283565[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]3.00075[/C][C]3.00417[/C][C]-0.00341435[/C][C]-0.000752315[/C][/ROW]
[ROW][C]21[/C][C]3[/C][C]3.00214[/C][C]3.0125[/C][C]-0.0103588[/C][C]-0.0021412[/C][/ROW]
[ROW][C]22[/C][C]3[/C][C]3.00353[/C][C]3.02083[/C][C]-0.0173032[/C][C]-0.00353009[/C][/ROW]
[ROW][C]23[/C][C]3[/C][C]3.00492[/C][C]3.02917[/C][C]-0.0242477[/C][C]-0.00491898[/C][/ROW]
[ROW][C]24[/C][C]3[/C][C]3.00631[/C][C]3.0375[/C][C]-0.0311921[/C][C]-0.00630787[/C][/ROW]
[ROW][C]25[/C][C]3[/C][C]3.0077[/C][C]3.04583[/C][C]-0.0381366[/C][C]-0.00769676[/C][/ROW]
[ROW][C]26[/C][C]3.1[/C][C]3.09242[/C][C]3.05417[/C][C]0.0382523[/C][C]0.00758102[/C][/ROW]
[ROW][C]27[/C][C]3.1[/C][C]3.09381[/C][C]3.0625[/C][C]0.0313079[/C][C]0.00619213[/C][/ROW]
[ROW][C]28[/C][C]3.1[/C][C]3.0952[/C][C]3.07083[/C][C]0.0243634[/C][C]0.00480324[/C][/ROW]
[ROW][C]29[/C][C]3.1[/C][C]3.09659[/C][C]3.07917[/C][C]0.017419[/C][C]0.00341435[/C][/ROW]
[ROW][C]30[/C][C]3.1[/C][C]3.09797[/C][C]3.0875[/C][C]0.0104745[/C][C]0.00202546[/C][/ROW]
[ROW][C]31[/C][C]3.1[/C][C]3.09867[/C][C]3.09583[/C][C]0.00283565[/C][C]0.00133102[/C][/ROW]
[ROW][C]32[/C][C]3.1[/C][C]3.10492[/C][C]3.10833[/C][C]-0.00341435[/C][C]-0.00491898[/C][/ROW]
[ROW][C]33[/C][C]3.1[/C][C]3.11464[/C][C]3.125[/C][C]-0.0103588[/C][C]-0.0146412[/C][/ROW]
[ROW][C]34[/C][C]3.1[/C][C]3.12436[/C][C]3.14167[/C][C]-0.0173032[/C][C]-0.0243634[/C][/ROW]
[ROW][C]35[/C][C]3.1[/C][C]3.13409[/C][C]3.15833[/C][C]-0.0242477[/C][C]-0.0340856[/C][/ROW]
[ROW][C]36[/C][C]3.1[/C][C]3.14381[/C][C]3.175[/C][C]-0.0311921[/C][C]-0.0438079[/C][/ROW]
[ROW][C]37[/C][C]3.1[/C][C]3.15353[/C][C]3.19167[/C][C]-0.0381366[/C][C]-0.0535301[/C][/ROW]
[ROW][C]38[/C][C]3.3[/C][C]3.24659[/C][C]3.20833[/C][C]0.0382523[/C][C]0.0534144[/C][/ROW]
[ROW][C]39[/C][C]3.3[/C][C]3.25631[/C][C]3.225[/C][C]0.0313079[/C][C]0.0436921[/C][/ROW]
[ROW][C]40[/C][C]3.3[/C][C]3.26603[/C][C]3.24167[/C][C]0.0243634[/C][C]0.0339699[/C][/ROW]
[ROW][C]41[/C][C]3.3[/C][C]3.27575[/C][C]3.25833[/C][C]0.017419[/C][C]0.0242477[/C][/ROW]
[ROW][C]42[/C][C]3.3[/C][C]3.28547[/C][C]3.275[/C][C]0.0104745[/C][C]0.0145255[/C][/ROW]
[ROW][C]43[/C][C]3.3[/C][C]3.2945[/C][C]3.29167[/C][C]0.00283565[/C][C]0.00549769[/C][/ROW]
[ROW][C]44[/C][C]3.3[/C][C]3.29659[/C][C]3.3[/C][C]-0.00341435[/C][C]0.00341435[/C][/ROW]
[ROW][C]45[/C][C]3.3[/C][C]3.28964[/C][C]3.3[/C][C]-0.0103588[/C][C]0.0103588[/C][/ROW]
[ROW][C]46[/C][C]3.3[/C][C]3.2827[/C][C]3.3[/C][C]-0.0173032[/C][C]0.0173032[/C][/ROW]
[ROW][C]47[/C][C]3.3[/C][C]3.27575[/C][C]3.3[/C][C]-0.0242477[/C][C]0.0242477[/C][/ROW]
[ROW][C]48[/C][C]3.3[/C][C]3.26881[/C][C]3.3[/C][C]-0.0311921[/C][C]0.0311921[/C][/ROW]
[ROW][C]49[/C][C]3.3[/C][C]3.26186[/C][C]3.3[/C][C]-0.0381366[/C][C]0.0381366[/C][/ROW]
[ROW][C]50[/C][C]3.3[/C][C]3.33825[/C][C]3.3[/C][C]0.0382523[/C][C]-0.0382523[/C][/ROW]
[ROW][C]51[/C][C]3.3[/C][C]3.33131[/C][C]3.3[/C][C]0.0313079[/C][C]-0.0313079[/C][/ROW]
[ROW][C]52[/C][C]3.3[/C][C]3.32436[/C][C]3.3[/C][C]0.0243634[/C][C]-0.0243634[/C][/ROW]
[ROW][C]53[/C][C]3.3[/C][C]3.31742[/C][C]3.3[/C][C]0.017419[/C][C]-0.017419[/C][/ROW]
[ROW][C]54[/C][C]3.3[/C][C]3.31047[/C][C]3.3[/C][C]0.0104745[/C][C]-0.0104745[/C][/ROW]
[ROW][C]55[/C][C]3.3[/C][C]3.30284[/C][C]3.3[/C][C]0.00283565[/C][C]-0.00283565[/C][/ROW]
[ROW][C]56[/C][C]3.3[/C][C]3.29659[/C][C]3.3[/C][C]-0.00341435[/C][C]0.00341435[/C][/ROW]
[ROW][C]57[/C][C]3.3[/C][C]3.28964[/C][C]3.3[/C][C]-0.0103588[/C][C]0.0103588[/C][/ROW]
[ROW][C]58[/C][C]3.3[/C][C]3.2827[/C][C]3.3[/C][C]-0.0173032[/C][C]0.0173032[/C][/ROW]
[ROW][C]59[/C][C]3.3[/C][C]3.27575[/C][C]3.3[/C][C]-0.0242477[/C][C]0.0242477[/C][/ROW]
[ROW][C]60[/C][C]3.3[/C][C]3.26881[/C][C]3.3[/C][C]-0.0311921[/C][C]0.0311921[/C][/ROW]
[ROW][C]61[/C][C]3.3[/C][C]3.26186[/C][C]3.3[/C][C]-0.0381366[/C][C]0.0381366[/C][/ROW]
[ROW][C]62[/C][C]3.3[/C][C]3.33825[/C][C]3.3[/C][C]0.0382523[/C][C]-0.0382523[/C][/ROW]
[ROW][C]63[/C][C]3.3[/C][C]3.33131[/C][C]3.3[/C][C]0.0313079[/C][C]-0.0313079[/C][/ROW]
[ROW][C]64[/C][C]3.3[/C][C]3.32436[/C][C]3.3[/C][C]0.0243634[/C][C]-0.0243634[/C][/ROW]
[ROW][C]65[/C][C]3.3[/C][C]3.31742[/C][C]3.3[/C][C]0.017419[/C][C]-0.017419[/C][/ROW]
[ROW][C]66[/C][C]3.3[/C][C]3.31047[/C][C]3.3[/C][C]0.0104745[/C][C]-0.0104745[/C][/ROW]
[ROW][C]67[/C][C]3.3[/C][C]3.30284[/C][C]3.3[/C][C]0.00283565[/C][C]-0.00283565[/C][/ROW]
[ROW][C]68[/C][C]3.3[/C][C]3.30492[/C][C]3.30833[/C][C]-0.00341435[/C][C]-0.00491898[/C][/ROW]
[ROW][C]69[/C][C]3.3[/C][C]3.31464[/C][C]3.325[/C][C]-0.0103588[/C][C]-0.0146412[/C][/ROW]
[ROW][C]70[/C][C]3.3[/C][C]3.32436[/C][C]3.34167[/C][C]-0.0173032[/C][C]-0.0243634[/C][/ROW]
[ROW][C]71[/C][C]3.3[/C][C]3.33409[/C][C]3.35833[/C][C]-0.0242477[/C][C]-0.0340856[/C][/ROW]
[ROW][C]72[/C][C]3.3[/C][C]3.34381[/C][C]3.375[/C][C]-0.0311921[/C][C]-0.0438079[/C][/ROW]
[ROW][C]73[/C][C]3.3[/C][C]3.35353[/C][C]3.39167[/C][C]-0.0381366[/C][C]-0.0535301[/C][/ROW]
[ROW][C]74[/C][C]3.5[/C][C]3.44659[/C][C]3.40833[/C][C]0.0382523[/C][C]0.0534144[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]3.45631[/C][C]3.425[/C][C]0.0313079[/C][C]0.0436921[/C][/ROW]
[ROW][C]76[/C][C]3.5[/C][C]3.46603[/C][C]3.44167[/C][C]0.0243634[/C][C]0.0339699[/C][/ROW]
[ROW][C]77[/C][C]3.5[/C][C]3.47575[/C][C]3.45833[/C][C]0.017419[/C][C]0.0242477[/C][/ROW]
[ROW][C]78[/C][C]3.5[/C][C]3.48547[/C][C]3.475[/C][C]0.0104745[/C][C]0.0145255[/C][/ROW]
[ROW][C]79[/C][C]3.5[/C][C]NA[/C][C]NA[/C][C]0.00283565[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]NA[/C][C]NA[/C][C]-0.00341435[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]3.5[/C][C]NA[/C][C]NA[/C][C]-0.0103588[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]3.5[/C][C]NA[/C][C]NA[/C][C]-0.0173032[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]3.5[/C][C]NA[/C][C]NA[/C][C]-0.0242477[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]3.5[/C][C]NA[/C][C]NA[/C][C]-0.0311921[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234919&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234919&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	2.9	NA	NA	-0.0381366	NA
2	3	NA	NA	0.0382523	NA
3	3	NA	NA	0.0313079	NA
4	3	NA	NA	0.0243634	NA
5	3	NA	NA	0.017419	NA
6	3	NA	NA	0.0104745	NA
7	3	2.99867	2.99583	0.00283565	0.00133102
8	3	2.99659	3	-0.00341435	0.00341435
9	3	2.98964	3	-0.0103588	0.0103588
10	3	2.9827	3	-0.0173032	0.0173032
11	3	2.97575	3	-0.0242477	0.0242477
12	3	2.96881	3	-0.0311921	0.0311921
13	3	2.96186	3	-0.0381366	0.0381366
14	3	3.03825	3	0.0382523	-0.0382523
15	3	3.03131	3	0.0313079	-0.0313079
16	3	3.02436	3	0.0243634	-0.0243634
17	3	3.01742	3	0.017419	-0.017419
18	3	3.01047	3	0.0104745	-0.0104745
19	3	3.00284	3	0.00283565	-0.00283565
20	3	3.00075	3.00417	-0.00341435	-0.000752315
21	3	3.00214	3.0125	-0.0103588	-0.0021412
22	3	3.00353	3.02083	-0.0173032	-0.00353009
23	3	3.00492	3.02917	-0.0242477	-0.00491898
24	3	3.00631	3.0375	-0.0311921	-0.00630787
25	3	3.0077	3.04583	-0.0381366	-0.00769676
26	3.1	3.09242	3.05417	0.0382523	0.00758102
27	3.1	3.09381	3.0625	0.0313079	0.00619213
28	3.1	3.0952	3.07083	0.0243634	0.00480324
29	3.1	3.09659	3.07917	0.017419	0.00341435
30	3.1	3.09797	3.0875	0.0104745	0.00202546
31	3.1	3.09867	3.09583	0.00283565	0.00133102
32	3.1	3.10492	3.10833	-0.00341435	-0.00491898
33	3.1	3.11464	3.125	-0.0103588	-0.0146412
34	3.1	3.12436	3.14167	-0.0173032	-0.0243634
35	3.1	3.13409	3.15833	-0.0242477	-0.0340856
36	3.1	3.14381	3.175	-0.0311921	-0.0438079
37	3.1	3.15353	3.19167	-0.0381366	-0.0535301
38	3.3	3.24659	3.20833	0.0382523	0.0534144
39	3.3	3.25631	3.225	0.0313079	0.0436921
40	3.3	3.26603	3.24167	0.0243634	0.0339699
41	3.3	3.27575	3.25833	0.017419	0.0242477
42	3.3	3.28547	3.275	0.0104745	0.0145255
43	3.3	3.2945	3.29167	0.00283565	0.00549769
44	3.3	3.29659	3.3	-0.00341435	0.00341435
45	3.3	3.28964	3.3	-0.0103588	0.0103588
46	3.3	3.2827	3.3	-0.0173032	0.0173032
47	3.3	3.27575	3.3	-0.0242477	0.0242477
48	3.3	3.26881	3.3	-0.0311921	0.0311921
49	3.3	3.26186	3.3	-0.0381366	0.0381366
50	3.3	3.33825	3.3	0.0382523	-0.0382523
51	3.3	3.33131	3.3	0.0313079	-0.0313079
52	3.3	3.32436	3.3	0.0243634	-0.0243634
53	3.3	3.31742	3.3	0.017419	-0.017419
54	3.3	3.31047	3.3	0.0104745	-0.0104745
55	3.3	3.30284	3.3	0.00283565	-0.00283565
56	3.3	3.29659	3.3	-0.00341435	0.00341435
57	3.3	3.28964	3.3	-0.0103588	0.0103588
58	3.3	3.2827	3.3	-0.0173032	0.0173032
59	3.3	3.27575	3.3	-0.0242477	0.0242477
60	3.3	3.26881	3.3	-0.0311921	0.0311921
61	3.3	3.26186	3.3	-0.0381366	0.0381366
62	3.3	3.33825	3.3	0.0382523	-0.0382523
63	3.3	3.33131	3.3	0.0313079	-0.0313079
64	3.3	3.32436	3.3	0.0243634	-0.0243634
65	3.3	3.31742	3.3	0.017419	-0.017419
66	3.3	3.31047	3.3	0.0104745	-0.0104745
67	3.3	3.30284	3.3	0.00283565	-0.00283565
68	3.3	3.30492	3.30833	-0.00341435	-0.00491898
69	3.3	3.31464	3.325	-0.0103588	-0.0146412
70	3.3	3.32436	3.34167	-0.0173032	-0.0243634
71	3.3	3.33409	3.35833	-0.0242477	-0.0340856
72	3.3	3.34381	3.375	-0.0311921	-0.0438079
73	3.3	3.35353	3.39167	-0.0381366	-0.0535301
74	3.5	3.44659	3.40833	0.0382523	0.0534144
75	3.5	3.45631	3.425	0.0313079	0.0436921
76	3.5	3.46603	3.44167	0.0243634	0.0339699
77	3.5	3.47575	3.45833	0.017419	0.0242477
78	3.5	3.48547	3.475	0.0104745	0.0145255
79	3.5	NA	NA	0.00283565	NA
80	3.5	NA	NA	-0.00341435	NA
81	3.5	NA	NA	-0.0103588	NA
82	3.5	NA	NA	-0.0173032	NA
83	3.5	NA	NA	-0.0242477	NA
84	3.5	NA	NA	-0.0311921	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