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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 31 May 2016 11:04:21 +0100

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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/May/31/t14646891378r92wx65bd82hz9.htm/, Retrieved Mon, 06 May 2024 13:13:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295741, Retrieved Mon, 06 May 2024 13:13:38 +0000

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Estimated Impact

126

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-       [Classical Decomposition] [Opgave 9.2 - werk...] [2016-05-31 10:04:21] [d36d23fecd6ad6dfd447f1d2ea855cae] [Current]

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

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	'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295741&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295741&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295741&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	7.3	NA	NA	0.190799	NA
2	7.1	NA	NA	0.161632	NA
3	6.8	NA	NA	-0.0015625	NA
4	6.4	NA	NA	-0.20434	NA
5	6.1	NA	NA	-0.47934	NA
6	6.5	NA	NA	-0.471007	NA
7	7.7	7.32483	6.99167	0.33316	0.375174
8	7.9	7.50747	7.04583	0.461632	0.392535
9	7.5	7.38802	7.13333	0.254688	0.111979
10	6.9	7.2158	7.2375	-0.0217014	-0.315799
11	6.6	7.17552	7.34167	-0.166146	-0.575521
12	6.9	7.37135	7.42917	-0.0578125	-0.471354
13	7.7	7.67413	7.48333	0.190799	0.0258681
14	8	7.6783	7.51667	0.161632	0.321701
15	8	7.55677	7.55833	-0.0015625	0.443229
16	7.7	7.42066	7.625	-0.20434	0.27934
17	7.3	7.24149	7.72083	-0.47934	0.0585069
18	7.4	7.36233	7.83333	-0.471007	0.0376736
19	8.1	8.26233	7.92917	0.33316	-0.162326
20	8.3	8.45747	7.99583	0.461632	-0.157465
21	8.1	8.30052	8.04583	0.254688	-0.200521
22	7.9	8.06997	8.09167	-0.0217014	-0.169965
23	7.9	7.97969	8.14583	-0.166146	-0.0796875
24	8.3	8.14219	8.2	-0.0578125	0.157813
25	8.6	8.44497	8.25417	0.190799	0.155035
26	8.7	8.46163	8.3	0.161632	0.238368
27	8.5	8.33177	8.33333	-0.0015625	0.168229
28	8.3	8.15399	8.35833	-0.20434	0.146007
29	8	7.88316	8.3625	-0.47934	0.11684
30	8	7.86233	8.33333	-0.471007	0.137674
31	8.8	8.59566	8.2625	0.33316	0.20434
32	8.7	8.6158	8.15417	0.461632	0.0842014
33	8.5	8.27969	8.025	0.254688	0.220313
34	8.1	7.8658	7.8875	-0.0217014	0.234201
35	7.8	7.58802	7.75417	-0.166146	0.211979
36	7.7	7.57552	7.63333	-0.0578125	0.124479
37	7.5	7.71997	7.52917	0.190799	-0.219965
38	7.2	7.6158	7.45417	0.161632	-0.415799
39	6.9	7.3901	7.39167	-0.0015625	-0.490104
40	6.6	7.12066	7.325	-0.20434	-0.52066
41	6.5	6.77899	7.25833	-0.47934	-0.278993
42	6.6	6.72483	7.19583	-0.471007	-0.124826
43	7.7	7.49149	7.15833	0.33316	0.208507
44	8	7.6158	7.15417	0.461632	0.384201
45	7.7	7.42135	7.16667	0.254688	0.278646
46	7.3	7.17413	7.19583	-0.0217014	0.125868
47	7	7.07135	7.2375	-0.166146	-0.0713542
48	7	7.21719	7.275	-0.0578125	-0.217187
49	7.3	7.47413	7.28333	0.190799	-0.174132
50	7.3	7.4283	7.26667	0.161632	-0.128299
51	7.1	7.2651	7.26667	-0.0015625	-0.165104
52	7.1	7.10399	7.30833	-0.20434	-0.00399306
53	7	6.91649	7.39583	-0.47934	0.0835069
54	7	7.03733	7.50833	-0.471007	-0.0373264
55	7.5	7.95399	7.62083	0.33316	-0.453993
56	7.8	8.18663	7.725	0.461632	-0.386632
57	7.9	8.08385	7.82917	0.254688	-0.183854
58	8.1	7.91163	7.93333	-0.0217014	0.188368
59	8.3	7.85885	8.025	-0.166146	0.441146
60	8.4	8.05052	8.10833	-0.0578125	0.349479
61	8.6	8.3908	8.2	0.190799	0.209201
62	8.5	8.44913	8.2875	0.161632	0.0508681
63	8.4	8.3526	8.35417	-0.0015625	0.0473958
64	8.3	8.19566	8.4	-0.20434	0.10434
65	8	7.94566	8.425	-0.47934	0.0543403
66	8	7.97066	8.44167	-0.471007	0.0293403
67	8.7	8.79149	8.45833	0.33316	-0.0914931
68	8.7	8.93663	8.475	0.461632	-0.236632
69	8.6	8.74635	8.49167	0.254688	-0.146354
70	8.5	8.48247	8.50417	-0.0217014	0.0175347
71	8.5	8.34635	8.5125	-0.166146	0.153646
72	8.6	8.46302	8.52083	-0.0578125	0.136979
73	8.8	8.7158	8.525	0.190799	0.0842014
74	8.7	8.68663	8.525	0.161632	0.0133681
75	8.6	8.52344	8.525	-0.0015625	0.0765625
76	8.4	8.32483	8.52917	-0.20434	0.0751736
77	8.1	8.05399	8.53333	-0.47934	0.0460069
78	8.1	8.06233	8.53333	-0.471007	0.0376736
79	8.7	NA	NA	0.33316	NA
80	8.7	NA	NA	0.461632	NA
81	8.6	NA	NA	0.254688	NA
82	8.6	NA	NA	-0.0217014	NA
83	8.5	NA	NA	-0.166146	NA
84	8.6	NA	NA	-0.0578125	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 7.3 & NA & NA & 0.190799 & NA \tabularnewline
2 & 7.1 & NA & NA & 0.161632 & NA \tabularnewline
3 & 6.8 & NA & NA & -0.0015625 & NA \tabularnewline
4 & 6.4 & NA & NA & -0.20434 & NA \tabularnewline
5 & 6.1 & NA & NA & -0.47934 & NA \tabularnewline
6 & 6.5 & NA & NA & -0.471007 & NA \tabularnewline
7 & 7.7 & 7.32483 & 6.99167 & 0.33316 & 0.375174 \tabularnewline
8 & 7.9 & 7.50747 & 7.04583 & 0.461632 & 0.392535 \tabularnewline
9 & 7.5 & 7.38802 & 7.13333 & 0.254688 & 0.111979 \tabularnewline
10 & 6.9 & 7.2158 & 7.2375 & -0.0217014 & -0.315799 \tabularnewline
11 & 6.6 & 7.17552 & 7.34167 & -0.166146 & -0.575521 \tabularnewline
12 & 6.9 & 7.37135 & 7.42917 & -0.0578125 & -0.471354 \tabularnewline
13 & 7.7 & 7.67413 & 7.48333 & 0.190799 & 0.0258681 \tabularnewline
14 & 8 & 7.6783 & 7.51667 & 0.161632 & 0.321701 \tabularnewline
15 & 8 & 7.55677 & 7.55833 & -0.0015625 & 0.443229 \tabularnewline
16 & 7.7 & 7.42066 & 7.625 & -0.20434 & 0.27934 \tabularnewline
17 & 7.3 & 7.24149 & 7.72083 & -0.47934 & 0.0585069 \tabularnewline
18 & 7.4 & 7.36233 & 7.83333 & -0.471007 & 0.0376736 \tabularnewline
19 & 8.1 & 8.26233 & 7.92917 & 0.33316 & -0.162326 \tabularnewline
20 & 8.3 & 8.45747 & 7.99583 & 0.461632 & -0.157465 \tabularnewline
21 & 8.1 & 8.30052 & 8.04583 & 0.254688 & -0.200521 \tabularnewline
22 & 7.9 & 8.06997 & 8.09167 & -0.0217014 & -0.169965 \tabularnewline
23 & 7.9 & 7.97969 & 8.14583 & -0.166146 & -0.0796875 \tabularnewline
24 & 8.3 & 8.14219 & 8.2 & -0.0578125 & 0.157813 \tabularnewline
25 & 8.6 & 8.44497 & 8.25417 & 0.190799 & 0.155035 \tabularnewline
26 & 8.7 & 8.46163 & 8.3 & 0.161632 & 0.238368 \tabularnewline
27 & 8.5 & 8.33177 & 8.33333 & -0.0015625 & 0.168229 \tabularnewline
28 & 8.3 & 8.15399 & 8.35833 & -0.20434 & 0.146007 \tabularnewline
29 & 8 & 7.88316 & 8.3625 & -0.47934 & 0.11684 \tabularnewline
30 & 8 & 7.86233 & 8.33333 & -0.471007 & 0.137674 \tabularnewline
31 & 8.8 & 8.59566 & 8.2625 & 0.33316 & 0.20434 \tabularnewline
32 & 8.7 & 8.6158 & 8.15417 & 0.461632 & 0.0842014 \tabularnewline
33 & 8.5 & 8.27969 & 8.025 & 0.254688 & 0.220313 \tabularnewline
34 & 8.1 & 7.8658 & 7.8875 & -0.0217014 & 0.234201 \tabularnewline
35 & 7.8 & 7.58802 & 7.75417 & -0.166146 & 0.211979 \tabularnewline
36 & 7.7 & 7.57552 & 7.63333 & -0.0578125 & 0.124479 \tabularnewline
37 & 7.5 & 7.71997 & 7.52917 & 0.190799 & -0.219965 \tabularnewline
38 & 7.2 & 7.6158 & 7.45417 & 0.161632 & -0.415799 \tabularnewline
39 & 6.9 & 7.3901 & 7.39167 & -0.0015625 & -0.490104 \tabularnewline
40 & 6.6 & 7.12066 & 7.325 & -0.20434 & -0.52066 \tabularnewline
41 & 6.5 & 6.77899 & 7.25833 & -0.47934 & -0.278993 \tabularnewline
42 & 6.6 & 6.72483 & 7.19583 & -0.471007 & -0.124826 \tabularnewline
43 & 7.7 & 7.49149 & 7.15833 & 0.33316 & 0.208507 \tabularnewline
44 & 8 & 7.6158 & 7.15417 & 0.461632 & 0.384201 \tabularnewline
45 & 7.7 & 7.42135 & 7.16667 & 0.254688 & 0.278646 \tabularnewline
46 & 7.3 & 7.17413 & 7.19583 & -0.0217014 & 0.125868 \tabularnewline
47 & 7 & 7.07135 & 7.2375 & -0.166146 & -0.0713542 \tabularnewline
48 & 7 & 7.21719 & 7.275 & -0.0578125 & -0.217187 \tabularnewline
49 & 7.3 & 7.47413 & 7.28333 & 0.190799 & -0.174132 \tabularnewline
50 & 7.3 & 7.4283 & 7.26667 & 0.161632 & -0.128299 \tabularnewline
51 & 7.1 & 7.2651 & 7.26667 & -0.0015625 & -0.165104 \tabularnewline
52 & 7.1 & 7.10399 & 7.30833 & -0.20434 & -0.00399306 \tabularnewline
53 & 7 & 6.91649 & 7.39583 & -0.47934 & 0.0835069 \tabularnewline
54 & 7 & 7.03733 & 7.50833 & -0.471007 & -0.0373264 \tabularnewline
55 & 7.5 & 7.95399 & 7.62083 & 0.33316 & -0.453993 \tabularnewline
56 & 7.8 & 8.18663 & 7.725 & 0.461632 & -0.386632 \tabularnewline
57 & 7.9 & 8.08385 & 7.82917 & 0.254688 & -0.183854 \tabularnewline
58 & 8.1 & 7.91163 & 7.93333 & -0.0217014 & 0.188368 \tabularnewline
59 & 8.3 & 7.85885 & 8.025 & -0.166146 & 0.441146 \tabularnewline
60 & 8.4 & 8.05052 & 8.10833 & -0.0578125 & 0.349479 \tabularnewline
61 & 8.6 & 8.3908 & 8.2 & 0.190799 & 0.209201 \tabularnewline
62 & 8.5 & 8.44913 & 8.2875 & 0.161632 & 0.0508681 \tabularnewline
63 & 8.4 & 8.3526 & 8.35417 & -0.0015625 & 0.0473958 \tabularnewline
64 & 8.3 & 8.19566 & 8.4 & -0.20434 & 0.10434 \tabularnewline
65 & 8 & 7.94566 & 8.425 & -0.47934 & 0.0543403 \tabularnewline
66 & 8 & 7.97066 & 8.44167 & -0.471007 & 0.0293403 \tabularnewline
67 & 8.7 & 8.79149 & 8.45833 & 0.33316 & -0.0914931 \tabularnewline
68 & 8.7 & 8.93663 & 8.475 & 0.461632 & -0.236632 \tabularnewline
69 & 8.6 & 8.74635 & 8.49167 & 0.254688 & -0.146354 \tabularnewline
70 & 8.5 & 8.48247 & 8.50417 & -0.0217014 & 0.0175347 \tabularnewline
71 & 8.5 & 8.34635 & 8.5125 & -0.166146 & 0.153646 \tabularnewline
72 & 8.6 & 8.46302 & 8.52083 & -0.0578125 & 0.136979 \tabularnewline
73 & 8.8 & 8.7158 & 8.525 & 0.190799 & 0.0842014 \tabularnewline
74 & 8.7 & 8.68663 & 8.525 & 0.161632 & 0.0133681 \tabularnewline
75 & 8.6 & 8.52344 & 8.525 & -0.0015625 & 0.0765625 \tabularnewline
76 & 8.4 & 8.32483 & 8.52917 & -0.20434 & 0.0751736 \tabularnewline
77 & 8.1 & 8.05399 & 8.53333 & -0.47934 & 0.0460069 \tabularnewline
78 & 8.1 & 8.06233 & 8.53333 & -0.471007 & 0.0376736 \tabularnewline
79 & 8.7 & NA & NA & 0.33316 & NA \tabularnewline
80 & 8.7 & NA & NA & 0.461632 & NA \tabularnewline
81 & 8.6 & NA & NA & 0.254688 & NA \tabularnewline
82 & 8.6 & NA & NA & -0.0217014 & NA \tabularnewline
83 & 8.5 & NA & NA & -0.166146 & NA \tabularnewline
84 & 8.6 & NA & NA & -0.0578125 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295741&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]7.3[/C][C]NA[/C][C]NA[/C][C]0.190799[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]7.1[/C][C]NA[/C][C]NA[/C][C]0.161632[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]6.8[/C][C]NA[/C][C]NA[/C][C]-0.0015625[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]6.4[/C][C]NA[/C][C]NA[/C][C]-0.20434[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]6.1[/C][C]NA[/C][C]NA[/C][C]-0.47934[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]6.5[/C][C]NA[/C][C]NA[/C][C]-0.471007[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]7.7[/C][C]7.32483[/C][C]6.99167[/C][C]0.33316[/C][C]0.375174[/C][/ROW]
[ROW][C]8[/C][C]7.9[/C][C]7.50747[/C][C]7.04583[/C][C]0.461632[/C][C]0.392535[/C][/ROW]
[ROW][C]9[/C][C]7.5[/C][C]7.38802[/C][C]7.13333[/C][C]0.254688[/C][C]0.111979[/C][/ROW]
[ROW][C]10[/C][C]6.9[/C][C]7.2158[/C][C]7.2375[/C][C]-0.0217014[/C][C]-0.315799[/C][/ROW]
[ROW][C]11[/C][C]6.6[/C][C]7.17552[/C][C]7.34167[/C][C]-0.166146[/C][C]-0.575521[/C][/ROW]
[ROW][C]12[/C][C]6.9[/C][C]7.37135[/C][C]7.42917[/C][C]-0.0578125[/C][C]-0.471354[/C][/ROW]
[ROW][C]13[/C][C]7.7[/C][C]7.67413[/C][C]7.48333[/C][C]0.190799[/C][C]0.0258681[/C][/ROW]
[ROW][C]14[/C][C]8[/C][C]7.6783[/C][C]7.51667[/C][C]0.161632[/C][C]0.321701[/C][/ROW]
[ROW][C]15[/C][C]8[/C][C]7.55677[/C][C]7.55833[/C][C]-0.0015625[/C][C]0.443229[/C][/ROW]
[ROW][C]16[/C][C]7.7[/C][C]7.42066[/C][C]7.625[/C][C]-0.20434[/C][C]0.27934[/C][/ROW]
[ROW][C]17[/C][C]7.3[/C][C]7.24149[/C][C]7.72083[/C][C]-0.47934[/C][C]0.0585069[/C][/ROW]
[ROW][C]18[/C][C]7.4[/C][C]7.36233[/C][C]7.83333[/C][C]-0.471007[/C][C]0.0376736[/C][/ROW]
[ROW][C]19[/C][C]8.1[/C][C]8.26233[/C][C]7.92917[/C][C]0.33316[/C][C]-0.162326[/C][/ROW]
[ROW][C]20[/C][C]8.3[/C][C]8.45747[/C][C]7.99583[/C][C]0.461632[/C][C]-0.157465[/C][/ROW]
[ROW][C]21[/C][C]8.1[/C][C]8.30052[/C][C]8.04583[/C][C]0.254688[/C][C]-0.200521[/C][/ROW]
[ROW][C]22[/C][C]7.9[/C][C]8.06997[/C][C]8.09167[/C][C]-0.0217014[/C][C]-0.169965[/C][/ROW]
[ROW][C]23[/C][C]7.9[/C][C]7.97969[/C][C]8.14583[/C][C]-0.166146[/C][C]-0.0796875[/C][/ROW]
[ROW][C]24[/C][C]8.3[/C][C]8.14219[/C][C]8.2[/C][C]-0.0578125[/C][C]0.157813[/C][/ROW]
[ROW][C]25[/C][C]8.6[/C][C]8.44497[/C][C]8.25417[/C][C]0.190799[/C][C]0.155035[/C][/ROW]
[ROW][C]26[/C][C]8.7[/C][C]8.46163[/C][C]8.3[/C][C]0.161632[/C][C]0.238368[/C][/ROW]
[ROW][C]27[/C][C]8.5[/C][C]8.33177[/C][C]8.33333[/C][C]-0.0015625[/C][C]0.168229[/C][/ROW]
[ROW][C]28[/C][C]8.3[/C][C]8.15399[/C][C]8.35833[/C][C]-0.20434[/C][C]0.146007[/C][/ROW]
[ROW][C]29[/C][C]8[/C][C]7.88316[/C][C]8.3625[/C][C]-0.47934[/C][C]0.11684[/C][/ROW]
[ROW][C]30[/C][C]8[/C][C]7.86233[/C][C]8.33333[/C][C]-0.471007[/C][C]0.137674[/C][/ROW]
[ROW][C]31[/C][C]8.8[/C][C]8.59566[/C][C]8.2625[/C][C]0.33316[/C][C]0.20434[/C][/ROW]
[ROW][C]32[/C][C]8.7[/C][C]8.6158[/C][C]8.15417[/C][C]0.461632[/C][C]0.0842014[/C][/ROW]
[ROW][C]33[/C][C]8.5[/C][C]8.27969[/C][C]8.025[/C][C]0.254688[/C][C]0.220313[/C][/ROW]
[ROW][C]34[/C][C]8.1[/C][C]7.8658[/C][C]7.8875[/C][C]-0.0217014[/C][C]0.234201[/C][/ROW]
[ROW][C]35[/C][C]7.8[/C][C]7.58802[/C][C]7.75417[/C][C]-0.166146[/C][C]0.211979[/C][/ROW]
[ROW][C]36[/C][C]7.7[/C][C]7.57552[/C][C]7.63333[/C][C]-0.0578125[/C][C]0.124479[/C][/ROW]
[ROW][C]37[/C][C]7.5[/C][C]7.71997[/C][C]7.52917[/C][C]0.190799[/C][C]-0.219965[/C][/ROW]
[ROW][C]38[/C][C]7.2[/C][C]7.6158[/C][C]7.45417[/C][C]0.161632[/C][C]-0.415799[/C][/ROW]
[ROW][C]39[/C][C]6.9[/C][C]7.3901[/C][C]7.39167[/C][C]-0.0015625[/C][C]-0.490104[/C][/ROW]
[ROW][C]40[/C][C]6.6[/C][C]7.12066[/C][C]7.325[/C][C]-0.20434[/C][C]-0.52066[/C][/ROW]
[ROW][C]41[/C][C]6.5[/C][C]6.77899[/C][C]7.25833[/C][C]-0.47934[/C][C]-0.278993[/C][/ROW]
[ROW][C]42[/C][C]6.6[/C][C]6.72483[/C][C]7.19583[/C][C]-0.471007[/C][C]-0.124826[/C][/ROW]
[ROW][C]43[/C][C]7.7[/C][C]7.49149[/C][C]7.15833[/C][C]0.33316[/C][C]0.208507[/C][/ROW]
[ROW][C]44[/C][C]8[/C][C]7.6158[/C][C]7.15417[/C][C]0.461632[/C][C]0.384201[/C][/ROW]
[ROW][C]45[/C][C]7.7[/C][C]7.42135[/C][C]7.16667[/C][C]0.254688[/C][C]0.278646[/C][/ROW]
[ROW][C]46[/C][C]7.3[/C][C]7.17413[/C][C]7.19583[/C][C]-0.0217014[/C][C]0.125868[/C][/ROW]
[ROW][C]47[/C][C]7[/C][C]7.07135[/C][C]7.2375[/C][C]-0.166146[/C][C]-0.0713542[/C][/ROW]
[ROW][C]48[/C][C]7[/C][C]7.21719[/C][C]7.275[/C][C]-0.0578125[/C][C]-0.217187[/C][/ROW]
[ROW][C]49[/C][C]7.3[/C][C]7.47413[/C][C]7.28333[/C][C]0.190799[/C][C]-0.174132[/C][/ROW]
[ROW][C]50[/C][C]7.3[/C][C]7.4283[/C][C]7.26667[/C][C]0.161632[/C][C]-0.128299[/C][/ROW]
[ROW][C]51[/C][C]7.1[/C][C]7.2651[/C][C]7.26667[/C][C]-0.0015625[/C][C]-0.165104[/C][/ROW]
[ROW][C]52[/C][C]7.1[/C][C]7.10399[/C][C]7.30833[/C][C]-0.20434[/C][C]-0.00399306[/C][/ROW]
[ROW][C]53[/C][C]7[/C][C]6.91649[/C][C]7.39583[/C][C]-0.47934[/C][C]0.0835069[/C][/ROW]
[ROW][C]54[/C][C]7[/C][C]7.03733[/C][C]7.50833[/C][C]-0.471007[/C][C]-0.0373264[/C][/ROW]
[ROW][C]55[/C][C]7.5[/C][C]7.95399[/C][C]7.62083[/C][C]0.33316[/C][C]-0.453993[/C][/ROW]
[ROW][C]56[/C][C]7.8[/C][C]8.18663[/C][C]7.725[/C][C]0.461632[/C][C]-0.386632[/C][/ROW]
[ROW][C]57[/C][C]7.9[/C][C]8.08385[/C][C]7.82917[/C][C]0.254688[/C][C]-0.183854[/C][/ROW]
[ROW][C]58[/C][C]8.1[/C][C]7.91163[/C][C]7.93333[/C][C]-0.0217014[/C][C]0.188368[/C][/ROW]
[ROW][C]59[/C][C]8.3[/C][C]7.85885[/C][C]8.025[/C][C]-0.166146[/C][C]0.441146[/C][/ROW]
[ROW][C]60[/C][C]8.4[/C][C]8.05052[/C][C]8.10833[/C][C]-0.0578125[/C][C]0.349479[/C][/ROW]
[ROW][C]61[/C][C]8.6[/C][C]8.3908[/C][C]8.2[/C][C]0.190799[/C][C]0.209201[/C][/ROW]
[ROW][C]62[/C][C]8.5[/C][C]8.44913[/C][C]8.2875[/C][C]0.161632[/C][C]0.0508681[/C][/ROW]
[ROW][C]63[/C][C]8.4[/C][C]8.3526[/C][C]8.35417[/C][C]-0.0015625[/C][C]0.0473958[/C][/ROW]
[ROW][C]64[/C][C]8.3[/C][C]8.19566[/C][C]8.4[/C][C]-0.20434[/C][C]0.10434[/C][/ROW]
[ROW][C]65[/C][C]8[/C][C]7.94566[/C][C]8.425[/C][C]-0.47934[/C][C]0.0543403[/C][/ROW]
[ROW][C]66[/C][C]8[/C][C]7.97066[/C][C]8.44167[/C][C]-0.471007[/C][C]0.0293403[/C][/ROW]
[ROW][C]67[/C][C]8.7[/C][C]8.79149[/C][C]8.45833[/C][C]0.33316[/C][C]-0.0914931[/C][/ROW]
[ROW][C]68[/C][C]8.7[/C][C]8.93663[/C][C]8.475[/C][C]0.461632[/C][C]-0.236632[/C][/ROW]
[ROW][C]69[/C][C]8.6[/C][C]8.74635[/C][C]8.49167[/C][C]0.254688[/C][C]-0.146354[/C][/ROW]
[ROW][C]70[/C][C]8.5[/C][C]8.48247[/C][C]8.50417[/C][C]-0.0217014[/C][C]0.0175347[/C][/ROW]
[ROW][C]71[/C][C]8.5[/C][C]8.34635[/C][C]8.5125[/C][C]-0.166146[/C][C]0.153646[/C][/ROW]
[ROW][C]72[/C][C]8.6[/C][C]8.46302[/C][C]8.52083[/C][C]-0.0578125[/C][C]0.136979[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]8.7158[/C][C]8.525[/C][C]0.190799[/C][C]0.0842014[/C][/ROW]
[ROW][C]74[/C][C]8.7[/C][C]8.68663[/C][C]8.525[/C][C]0.161632[/C][C]0.0133681[/C][/ROW]
[ROW][C]75[/C][C]8.6[/C][C]8.52344[/C][C]8.525[/C][C]-0.0015625[/C][C]0.0765625[/C][/ROW]
[ROW][C]76[/C][C]8.4[/C][C]8.32483[/C][C]8.52917[/C][C]-0.20434[/C][C]0.0751736[/C][/ROW]
[ROW][C]77[/C][C]8.1[/C][C]8.05399[/C][C]8.53333[/C][C]-0.47934[/C][C]0.0460069[/C][/ROW]
[ROW][C]78[/C][C]8.1[/C][C]8.06233[/C][C]8.53333[/C][C]-0.471007[/C][C]0.0376736[/C][/ROW]
[ROW][C]79[/C][C]8.7[/C][C]NA[/C][C]NA[/C][C]0.33316[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]8.7[/C][C]NA[/C][C]NA[/C][C]0.461632[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]8.6[/C][C]NA[/C][C]NA[/C][C]0.254688[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]8.6[/C][C]NA[/C][C]NA[/C][C]-0.0217014[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]8.5[/C][C]NA[/C][C]NA[/C][C]-0.166146[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]8.6[/C][C]NA[/C][C]NA[/C][C]-0.0578125[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295741&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295741&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	7.3	NA	NA	0.190799	NA
2	7.1	NA	NA	0.161632	NA
3	6.8	NA	NA	-0.0015625	NA
4	6.4	NA	NA	-0.20434	NA
5	6.1	NA	NA	-0.47934	NA
6	6.5	NA	NA	-0.471007	NA
7	7.7	7.32483	6.99167	0.33316	0.375174
8	7.9	7.50747	7.04583	0.461632	0.392535
9	7.5	7.38802	7.13333	0.254688	0.111979
10	6.9	7.2158	7.2375	-0.0217014	-0.315799
11	6.6	7.17552	7.34167	-0.166146	-0.575521
12	6.9	7.37135	7.42917	-0.0578125	-0.471354
13	7.7	7.67413	7.48333	0.190799	0.0258681
14	8	7.6783	7.51667	0.161632	0.321701
15	8	7.55677	7.55833	-0.0015625	0.443229
16	7.7	7.42066	7.625	-0.20434	0.27934
17	7.3	7.24149	7.72083	-0.47934	0.0585069
18	7.4	7.36233	7.83333	-0.471007	0.0376736
19	8.1	8.26233	7.92917	0.33316	-0.162326
20	8.3	8.45747	7.99583	0.461632	-0.157465
21	8.1	8.30052	8.04583	0.254688	-0.200521
22	7.9	8.06997	8.09167	-0.0217014	-0.169965
23	7.9	7.97969	8.14583	-0.166146	-0.0796875
24	8.3	8.14219	8.2	-0.0578125	0.157813
25	8.6	8.44497	8.25417	0.190799	0.155035
26	8.7	8.46163	8.3	0.161632	0.238368
27	8.5	8.33177	8.33333	-0.0015625	0.168229
28	8.3	8.15399	8.35833	-0.20434	0.146007
29	8	7.88316	8.3625	-0.47934	0.11684
30	8	7.86233	8.33333	-0.471007	0.137674
31	8.8	8.59566	8.2625	0.33316	0.20434
32	8.7	8.6158	8.15417	0.461632	0.0842014
33	8.5	8.27969	8.025	0.254688	0.220313
34	8.1	7.8658	7.8875	-0.0217014	0.234201
35	7.8	7.58802	7.75417	-0.166146	0.211979
36	7.7	7.57552	7.63333	-0.0578125	0.124479
37	7.5	7.71997	7.52917	0.190799	-0.219965
38	7.2	7.6158	7.45417	0.161632	-0.415799
39	6.9	7.3901	7.39167	-0.0015625	-0.490104
40	6.6	7.12066	7.325	-0.20434	-0.52066
41	6.5	6.77899	7.25833	-0.47934	-0.278993
42	6.6	6.72483	7.19583	-0.471007	-0.124826
43	7.7	7.49149	7.15833	0.33316	0.208507
44	8	7.6158	7.15417	0.461632	0.384201
45	7.7	7.42135	7.16667	0.254688	0.278646
46	7.3	7.17413	7.19583	-0.0217014	0.125868
47	7	7.07135	7.2375	-0.166146	-0.0713542
48	7	7.21719	7.275	-0.0578125	-0.217187
49	7.3	7.47413	7.28333	0.190799	-0.174132
50	7.3	7.4283	7.26667	0.161632	-0.128299
51	7.1	7.2651	7.26667	-0.0015625	-0.165104
52	7.1	7.10399	7.30833	-0.20434	-0.00399306
53	7	6.91649	7.39583	-0.47934	0.0835069
54	7	7.03733	7.50833	-0.471007	-0.0373264
55	7.5	7.95399	7.62083	0.33316	-0.453993
56	7.8	8.18663	7.725	0.461632	-0.386632
57	7.9	8.08385	7.82917	0.254688	-0.183854
58	8.1	7.91163	7.93333	-0.0217014	0.188368
59	8.3	7.85885	8.025	-0.166146	0.441146
60	8.4	8.05052	8.10833	-0.0578125	0.349479
61	8.6	8.3908	8.2	0.190799	0.209201
62	8.5	8.44913	8.2875	0.161632	0.0508681
63	8.4	8.3526	8.35417	-0.0015625	0.0473958
64	8.3	8.19566	8.4	-0.20434	0.10434
65	8	7.94566	8.425	-0.47934	0.0543403
66	8	7.97066	8.44167	-0.471007	0.0293403
67	8.7	8.79149	8.45833	0.33316	-0.0914931
68	8.7	8.93663	8.475	0.461632	-0.236632
69	8.6	8.74635	8.49167	0.254688	-0.146354
70	8.5	8.48247	8.50417	-0.0217014	0.0175347
71	8.5	8.34635	8.5125	-0.166146	0.153646
72	8.6	8.46302	8.52083	-0.0578125	0.136979
73	8.8	8.7158	8.525	0.190799	0.0842014
74	8.7	8.68663	8.525	0.161632	0.0133681
75	8.6	8.52344	8.525	-0.0015625	0.0765625
76	8.4	8.32483	8.52917	-0.20434	0.0751736
77	8.1	8.05399	8.53333	-0.47934	0.0460069
78	8.1	8.06233	8.53333	-0.471007	0.0376736
79	8.7	NA	NA	0.33316	NA
80	8.7	NA	NA	0.461632	NA
81	8.6	NA	NA	0.254688	NA
82	8.6	NA	NA	-0.0217014	NA
83	8.5	NA	NA	-0.166146	NA
84	8.6	NA	NA	-0.0578125	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 = 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