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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 16 Dec 2014 08:41:29 +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/Dec/16/t1418719307gufu1j5tdpz2vgg.htm/, Retrieved Thu, 16 May 2024 13:26:33 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269170, Retrieved Thu, 16 May 2024 13:26:33 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Classical Decomposition] [] [2014-11-30 20:55:43] [deebc1e457a5ecb4dd1aad0be1fbee4a]
- R  D  [Classical Decomposition] [] [2014-11-30 21:01:28] [deebc1e457a5ecb4dd1aad0be1fbee4a]
-   PD      [Classical Decomposition] [] [2014-12-16 08:41:29] [f2e79deb6e51141b138dd10990a8e48d] [Current]

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Dataseries X:

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Boxplots

5,06
5,05
5,05
5,04
5,06
5,07
5,09
5,08
5,09
5,09
5,09
5,1
5,12
5,14
5,14
5,14
5,13
5,15
5,16
5,17
5,17
5,18
5,21
5,19
5,22
5,24
5,21
5,24
5,28
5,3
5,32
5,32
5,29
5,3
5,32
5,31
5,35
5,36
5,33
5,35
5,35
5,35
5,37
5,39
5,4
5,39
5,4
5,4
5,4
5,38
5,32
5,36
5,35
5,39
5,4
5,41
5,36
5,38
5,41
5,35
5,4
5,41
5,42
5,41
5,41
5,42
5,4
5,42
5,41
5,34
5,46
5,45
5,47
5,48
5,43
5,5
5,51
5,51
5,52
5,55
5,55
5,48
5,61
5,59
5,68
5,71
5,68
5,7
5,76
5,78
5,77
5,85
5,82
5,84
5,89
5,84

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269170&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269170&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269170&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	5.06	NA	NA	1.00266	NA
2	5.05	NA	NA	1.00319	NA
3	5.05	NA	NA	0.996534	NA
4	5.04	NA	NA	0.999403	NA
5	5.06	NA	NA	1.00002	NA
6	5.07	NA	NA	1.00126	NA
7	5.09	5.08274	5.075	1.00153	1.00143
8	5.08	5.09239	5.08125	1.00219	0.997566
9	5.09	5.08319	5.08875	0.998907	1.00134
10	5.09	5.06942	5.09667	0.994655	1.00406
11	5.09	5.11424	5.10375	1.00206	0.99526
12	5.1	5.09775	5.11	0.997603	1.00044
13	5.12	5.12984	5.11625	1.00266	0.998081
14	5.14	5.13924	5.12292	1.00319	1.00015
15	5.14	5.11222	5.13	0.996534	1.00543
16	5.14	5.13402	5.13708	0.999403	1.00117
17	5.13	5.14593	5.14583	1.00002	0.996904
18	5.15	5.1611	5.15458	1.00126	0.99785
19	5.16	5.17038	5.1625	1.00153	0.997993
20	5.17	5.18217	5.17083	1.00219	0.997651
21	5.17	5.17225	5.17792	0.998907	0.999564
22	5.18	5.15728	5.185	0.994655	1.0044
23	5.21	5.2061	5.19542	1.00206	1.00075
24	5.19	5.19543	5.20792	0.997603	0.998955
25	5.22	5.2347	5.22083	1.00266	0.997191
26	5.24	5.25042	5.23375	1.00319	0.998015
27	5.21	5.22682	5.245	0.996534	0.996782
28	5.24	5.25186	5.255	0.999403	0.997741
29	5.28	5.26468	5.26458	1.00002	1.00291
30	5.3	5.28083	5.27417	1.00126	1.00363
31	5.32	5.29265	5.28458	1.00153	1.00517
32	5.32	5.30661	5.295	1.00219	1.00252
33	5.29	5.2992	5.305	0.998907	0.998264
34	5.3	5.28617	5.31458	0.994655	1.00262
35	5.32	5.33302	5.32208	1.00206	0.997558
36	5.31	5.31431	5.32708	0.997603	0.999189
37	5.35	5.34541	5.33125	1.00266	1.00086
38	5.36	5.35325	5.33625	1.00319	1.00126
39	5.33	5.32523	5.34375	0.996534	1.0009
40	5.35	5.34889	5.35208	0.999403	1.00021
41	5.35	5.35927	5.35917	1.00002	0.99827
42	5.35	5.37303	5.36625	1.00126	0.995714
43	5.37	5.38028	5.37208	1.00153	0.998089
44	5.39	5.38679	5.375	1.00219	1.0006
45	5.4	5.36954	5.37542	0.998907	1.00567
46	5.39	5.34668	5.37542	0.994655	1.0081
47	5.4	5.38688	5.37583	1.00206	1.00243
48	5.4	5.36461	5.3775	0.997603	1.0066
49	5.4	5.39471	5.38042	1.00266	1.00098
50	5.38	5.39965	5.3825	1.00319	0.996361
51	5.32	5.36302	5.38167	0.996534	0.991979
52	5.36	5.37637	5.37958	0.999403	0.996955
53	5.35	5.37969	5.37958	1.00002	0.994482
54	5.39	5.38471	5.37792	1.00126	1.00098
55	5.4	5.38404	5.37583	1.00153	1.00297
56	5.41	5.38887	5.37708	1.00219	1.00392
57	5.36	5.37661	5.3825	0.998907	0.99691
58	5.38	5.35994	5.38875	0.994655	1.00374
59	5.41	5.40442	5.39333	1.00206	1.00103
60	5.35	5.38414	5.39708	0.997603	0.993658
61	5.4	5.41268	5.39833	1.00266	0.997658
62	5.41	5.41595	5.39875	1.00319	0.998902
63	5.42	5.38253	5.40125	0.996534	1.00696
64	5.41	5.39844	5.40167	0.999403	1.00214
65	5.41	5.40219	5.40208	1.00002	1.00145
66	5.42	5.41517	5.40833	1.00126	1.00089
67	5.4	5.42368	5.41542	1.00153	0.995634
68	5.42	5.43314	5.42125	1.00219	0.997582
69	5.41	5.41865	5.42458	0.998907	0.998403
70	5.34	5.39973	5.42875	0.994655	0.988938
71	5.46	5.44784	5.43667	1.00206	1.00223
72	5.45	5.43153	5.44458	0.997603	1.0034
73	5.47	5.46782	5.45333	1.00266	1.0004
74	5.48	5.48116	5.46375	1.00319	0.999789
75	5.43	5.45603	5.475	0.996534	0.99523
76	5.5	5.48339	5.48667	0.999403	1.00303
77	5.51	5.49886	5.49875	1.00002	1.00203
78	5.51	5.5178	5.51083	1.00126	0.998587
79	5.52	5.53385	5.52542	1.00153	0.997498
80	5.55	5.55591	5.54375	1.00219	0.998937
81	5.55	5.55767	5.56375	0.998907	0.998621
82	5.48	5.55266	5.5825	0.994655	0.986915
83	5.61	5.61276	5.60125	1.00206	0.999508
84	5.59	5.60944	5.62292	0.997603	0.996535
85	5.68	5.65958	5.64458	1.00266	1.00361
86	5.71	5.68556	5.6675	1.00319	1.0043
87	5.68	5.67153	5.69125	0.996534	1.00149
88	5.7	5.71409	5.7175	0.999403	0.997535
89	5.76	5.74428	5.74417	1.00002	1.00274
90	5.78	5.77354	5.76625	1.00126	1.00112
91	5.77	NA	NA	1.00153	NA
92	5.85	NA	NA	1.00219	NA
93	5.82	NA	NA	0.998907	NA
94	5.84	NA	NA	0.994655	NA
95	5.89	NA	NA	1.00206	NA
96	5.84	NA	NA	0.997603	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 5.06 & NA & NA & 1.00266 & NA \tabularnewline
2 & 5.05 & NA & NA & 1.00319 & NA \tabularnewline
3 & 5.05 & NA & NA & 0.996534 & NA \tabularnewline
4 & 5.04 & NA & NA & 0.999403 & NA \tabularnewline
5 & 5.06 & NA & NA & 1.00002 & NA \tabularnewline
6 & 5.07 & NA & NA & 1.00126 & NA \tabularnewline
7 & 5.09 & 5.08274 & 5.075 & 1.00153 & 1.00143 \tabularnewline
8 & 5.08 & 5.09239 & 5.08125 & 1.00219 & 0.997566 \tabularnewline
9 & 5.09 & 5.08319 & 5.08875 & 0.998907 & 1.00134 \tabularnewline
10 & 5.09 & 5.06942 & 5.09667 & 0.994655 & 1.00406 \tabularnewline
11 & 5.09 & 5.11424 & 5.10375 & 1.00206 & 0.99526 \tabularnewline
12 & 5.1 & 5.09775 & 5.11 & 0.997603 & 1.00044 \tabularnewline
13 & 5.12 & 5.12984 & 5.11625 & 1.00266 & 0.998081 \tabularnewline
14 & 5.14 & 5.13924 & 5.12292 & 1.00319 & 1.00015 \tabularnewline
15 & 5.14 & 5.11222 & 5.13 & 0.996534 & 1.00543 \tabularnewline
16 & 5.14 & 5.13402 & 5.13708 & 0.999403 & 1.00117 \tabularnewline
17 & 5.13 & 5.14593 & 5.14583 & 1.00002 & 0.996904 \tabularnewline
18 & 5.15 & 5.1611 & 5.15458 & 1.00126 & 0.99785 \tabularnewline
19 & 5.16 & 5.17038 & 5.1625 & 1.00153 & 0.997993 \tabularnewline
20 & 5.17 & 5.18217 & 5.17083 & 1.00219 & 0.997651 \tabularnewline
21 & 5.17 & 5.17225 & 5.17792 & 0.998907 & 0.999564 \tabularnewline
22 & 5.18 & 5.15728 & 5.185 & 0.994655 & 1.0044 \tabularnewline
23 & 5.21 & 5.2061 & 5.19542 & 1.00206 & 1.00075 \tabularnewline
24 & 5.19 & 5.19543 & 5.20792 & 0.997603 & 0.998955 \tabularnewline
25 & 5.22 & 5.2347 & 5.22083 & 1.00266 & 0.997191 \tabularnewline
26 & 5.24 & 5.25042 & 5.23375 & 1.00319 & 0.998015 \tabularnewline
27 & 5.21 & 5.22682 & 5.245 & 0.996534 & 0.996782 \tabularnewline
28 & 5.24 & 5.25186 & 5.255 & 0.999403 & 0.997741 \tabularnewline
29 & 5.28 & 5.26468 & 5.26458 & 1.00002 & 1.00291 \tabularnewline
30 & 5.3 & 5.28083 & 5.27417 & 1.00126 & 1.00363 \tabularnewline
31 & 5.32 & 5.29265 & 5.28458 & 1.00153 & 1.00517 \tabularnewline
32 & 5.32 & 5.30661 & 5.295 & 1.00219 & 1.00252 \tabularnewline
33 & 5.29 & 5.2992 & 5.305 & 0.998907 & 0.998264 \tabularnewline
34 & 5.3 & 5.28617 & 5.31458 & 0.994655 & 1.00262 \tabularnewline
35 & 5.32 & 5.33302 & 5.32208 & 1.00206 & 0.997558 \tabularnewline
36 & 5.31 & 5.31431 & 5.32708 & 0.997603 & 0.999189 \tabularnewline
37 & 5.35 & 5.34541 & 5.33125 & 1.00266 & 1.00086 \tabularnewline
38 & 5.36 & 5.35325 & 5.33625 & 1.00319 & 1.00126 \tabularnewline
39 & 5.33 & 5.32523 & 5.34375 & 0.996534 & 1.0009 \tabularnewline
40 & 5.35 & 5.34889 & 5.35208 & 0.999403 & 1.00021 \tabularnewline
41 & 5.35 & 5.35927 & 5.35917 & 1.00002 & 0.99827 \tabularnewline
42 & 5.35 & 5.37303 & 5.36625 & 1.00126 & 0.995714 \tabularnewline
43 & 5.37 & 5.38028 & 5.37208 & 1.00153 & 0.998089 \tabularnewline
44 & 5.39 & 5.38679 & 5.375 & 1.00219 & 1.0006 \tabularnewline
45 & 5.4 & 5.36954 & 5.37542 & 0.998907 & 1.00567 \tabularnewline
46 & 5.39 & 5.34668 & 5.37542 & 0.994655 & 1.0081 \tabularnewline
47 & 5.4 & 5.38688 & 5.37583 & 1.00206 & 1.00243 \tabularnewline
48 & 5.4 & 5.36461 & 5.3775 & 0.997603 & 1.0066 \tabularnewline
49 & 5.4 & 5.39471 & 5.38042 & 1.00266 & 1.00098 \tabularnewline
50 & 5.38 & 5.39965 & 5.3825 & 1.00319 & 0.996361 \tabularnewline
51 & 5.32 & 5.36302 & 5.38167 & 0.996534 & 0.991979 \tabularnewline
52 & 5.36 & 5.37637 & 5.37958 & 0.999403 & 0.996955 \tabularnewline
53 & 5.35 & 5.37969 & 5.37958 & 1.00002 & 0.994482 \tabularnewline
54 & 5.39 & 5.38471 & 5.37792 & 1.00126 & 1.00098 \tabularnewline
55 & 5.4 & 5.38404 & 5.37583 & 1.00153 & 1.00297 \tabularnewline
56 & 5.41 & 5.38887 & 5.37708 & 1.00219 & 1.00392 \tabularnewline
57 & 5.36 & 5.37661 & 5.3825 & 0.998907 & 0.99691 \tabularnewline
58 & 5.38 & 5.35994 & 5.38875 & 0.994655 & 1.00374 \tabularnewline
59 & 5.41 & 5.40442 & 5.39333 & 1.00206 & 1.00103 \tabularnewline
60 & 5.35 & 5.38414 & 5.39708 & 0.997603 & 0.993658 \tabularnewline
61 & 5.4 & 5.41268 & 5.39833 & 1.00266 & 0.997658 \tabularnewline
62 & 5.41 & 5.41595 & 5.39875 & 1.00319 & 0.998902 \tabularnewline
63 & 5.42 & 5.38253 & 5.40125 & 0.996534 & 1.00696 \tabularnewline
64 & 5.41 & 5.39844 & 5.40167 & 0.999403 & 1.00214 \tabularnewline
65 & 5.41 & 5.40219 & 5.40208 & 1.00002 & 1.00145 \tabularnewline
66 & 5.42 & 5.41517 & 5.40833 & 1.00126 & 1.00089 \tabularnewline
67 & 5.4 & 5.42368 & 5.41542 & 1.00153 & 0.995634 \tabularnewline
68 & 5.42 & 5.43314 & 5.42125 & 1.00219 & 0.997582 \tabularnewline
69 & 5.41 & 5.41865 & 5.42458 & 0.998907 & 0.998403 \tabularnewline
70 & 5.34 & 5.39973 & 5.42875 & 0.994655 & 0.988938 \tabularnewline
71 & 5.46 & 5.44784 & 5.43667 & 1.00206 & 1.00223 \tabularnewline
72 & 5.45 & 5.43153 & 5.44458 & 0.997603 & 1.0034 \tabularnewline
73 & 5.47 & 5.46782 & 5.45333 & 1.00266 & 1.0004 \tabularnewline
74 & 5.48 & 5.48116 & 5.46375 & 1.00319 & 0.999789 \tabularnewline
75 & 5.43 & 5.45603 & 5.475 & 0.996534 & 0.99523 \tabularnewline
76 & 5.5 & 5.48339 & 5.48667 & 0.999403 & 1.00303 \tabularnewline
77 & 5.51 & 5.49886 & 5.49875 & 1.00002 & 1.00203 \tabularnewline
78 & 5.51 & 5.5178 & 5.51083 & 1.00126 & 0.998587 \tabularnewline
79 & 5.52 & 5.53385 & 5.52542 & 1.00153 & 0.997498 \tabularnewline
80 & 5.55 & 5.55591 & 5.54375 & 1.00219 & 0.998937 \tabularnewline
81 & 5.55 & 5.55767 & 5.56375 & 0.998907 & 0.998621 \tabularnewline
82 & 5.48 & 5.55266 & 5.5825 & 0.994655 & 0.986915 \tabularnewline
83 & 5.61 & 5.61276 & 5.60125 & 1.00206 & 0.999508 \tabularnewline
84 & 5.59 & 5.60944 & 5.62292 & 0.997603 & 0.996535 \tabularnewline
85 & 5.68 & 5.65958 & 5.64458 & 1.00266 & 1.00361 \tabularnewline
86 & 5.71 & 5.68556 & 5.6675 & 1.00319 & 1.0043 \tabularnewline
87 & 5.68 & 5.67153 & 5.69125 & 0.996534 & 1.00149 \tabularnewline
88 & 5.7 & 5.71409 & 5.7175 & 0.999403 & 0.997535 \tabularnewline
89 & 5.76 & 5.74428 & 5.74417 & 1.00002 & 1.00274 \tabularnewline
90 & 5.78 & 5.77354 & 5.76625 & 1.00126 & 1.00112 \tabularnewline
91 & 5.77 & NA & NA & 1.00153 & NA \tabularnewline
92 & 5.85 & NA & NA & 1.00219 & NA \tabularnewline
93 & 5.82 & NA & NA & 0.998907 & NA \tabularnewline
94 & 5.84 & NA & NA & 0.994655 & NA \tabularnewline
95 & 5.89 & NA & NA & 1.00206 & NA \tabularnewline
96 & 5.84 & NA & NA & 0.997603 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269170&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]5.06[/C][C]NA[/C][C]NA[/C][C]1.00266[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]5.05[/C][C]NA[/C][C]NA[/C][C]1.00319[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]5.05[/C][C]NA[/C][C]NA[/C][C]0.996534[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.04[/C][C]NA[/C][C]NA[/C][C]0.999403[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]5.06[/C][C]NA[/C][C]NA[/C][C]1.00002[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5.07[/C][C]NA[/C][C]NA[/C][C]1.00126[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.09[/C][C]5.08274[/C][C]5.075[/C][C]1.00153[/C][C]1.00143[/C][/ROW]
[ROW][C]8[/C][C]5.08[/C][C]5.09239[/C][C]5.08125[/C][C]1.00219[/C][C]0.997566[/C][/ROW]
[ROW][C]9[/C][C]5.09[/C][C]5.08319[/C][C]5.08875[/C][C]0.998907[/C][C]1.00134[/C][/ROW]
[ROW][C]10[/C][C]5.09[/C][C]5.06942[/C][C]5.09667[/C][C]0.994655[/C][C]1.00406[/C][/ROW]
[ROW][C]11[/C][C]5.09[/C][C]5.11424[/C][C]5.10375[/C][C]1.00206[/C][C]0.99526[/C][/ROW]
[ROW][C]12[/C][C]5.1[/C][C]5.09775[/C][C]5.11[/C][C]0.997603[/C][C]1.00044[/C][/ROW]
[ROW][C]13[/C][C]5.12[/C][C]5.12984[/C][C]5.11625[/C][C]1.00266[/C][C]0.998081[/C][/ROW]
[ROW][C]14[/C][C]5.14[/C][C]5.13924[/C][C]5.12292[/C][C]1.00319[/C][C]1.00015[/C][/ROW]
[ROW][C]15[/C][C]5.14[/C][C]5.11222[/C][C]5.13[/C][C]0.996534[/C][C]1.00543[/C][/ROW]
[ROW][C]16[/C][C]5.14[/C][C]5.13402[/C][C]5.13708[/C][C]0.999403[/C][C]1.00117[/C][/ROW]
[ROW][C]17[/C][C]5.13[/C][C]5.14593[/C][C]5.14583[/C][C]1.00002[/C][C]0.996904[/C][/ROW]
[ROW][C]18[/C][C]5.15[/C][C]5.1611[/C][C]5.15458[/C][C]1.00126[/C][C]0.99785[/C][/ROW]
[ROW][C]19[/C][C]5.16[/C][C]5.17038[/C][C]5.1625[/C][C]1.00153[/C][C]0.997993[/C][/ROW]
[ROW][C]20[/C][C]5.17[/C][C]5.18217[/C][C]5.17083[/C][C]1.00219[/C][C]0.997651[/C][/ROW]
[ROW][C]21[/C][C]5.17[/C][C]5.17225[/C][C]5.17792[/C][C]0.998907[/C][C]0.999564[/C][/ROW]
[ROW][C]22[/C][C]5.18[/C][C]5.15728[/C][C]5.185[/C][C]0.994655[/C][C]1.0044[/C][/ROW]
[ROW][C]23[/C][C]5.21[/C][C]5.2061[/C][C]5.19542[/C][C]1.00206[/C][C]1.00075[/C][/ROW]
[ROW][C]24[/C][C]5.19[/C][C]5.19543[/C][C]5.20792[/C][C]0.997603[/C][C]0.998955[/C][/ROW]
[ROW][C]25[/C][C]5.22[/C][C]5.2347[/C][C]5.22083[/C][C]1.00266[/C][C]0.997191[/C][/ROW]
[ROW][C]26[/C][C]5.24[/C][C]5.25042[/C][C]5.23375[/C][C]1.00319[/C][C]0.998015[/C][/ROW]
[ROW][C]27[/C][C]5.21[/C][C]5.22682[/C][C]5.245[/C][C]0.996534[/C][C]0.996782[/C][/ROW]
[ROW][C]28[/C][C]5.24[/C][C]5.25186[/C][C]5.255[/C][C]0.999403[/C][C]0.997741[/C][/ROW]
[ROW][C]29[/C][C]5.28[/C][C]5.26468[/C][C]5.26458[/C][C]1.00002[/C][C]1.00291[/C][/ROW]
[ROW][C]30[/C][C]5.3[/C][C]5.28083[/C][C]5.27417[/C][C]1.00126[/C][C]1.00363[/C][/ROW]
[ROW][C]31[/C][C]5.32[/C][C]5.29265[/C][C]5.28458[/C][C]1.00153[/C][C]1.00517[/C][/ROW]
[ROW][C]32[/C][C]5.32[/C][C]5.30661[/C][C]5.295[/C][C]1.00219[/C][C]1.00252[/C][/ROW]
[ROW][C]33[/C][C]5.29[/C][C]5.2992[/C][C]5.305[/C][C]0.998907[/C][C]0.998264[/C][/ROW]
[ROW][C]34[/C][C]5.3[/C][C]5.28617[/C][C]5.31458[/C][C]0.994655[/C][C]1.00262[/C][/ROW]
[ROW][C]35[/C][C]5.32[/C][C]5.33302[/C][C]5.32208[/C][C]1.00206[/C][C]0.997558[/C][/ROW]
[ROW][C]36[/C][C]5.31[/C][C]5.31431[/C][C]5.32708[/C][C]0.997603[/C][C]0.999189[/C][/ROW]
[ROW][C]37[/C][C]5.35[/C][C]5.34541[/C][C]5.33125[/C][C]1.00266[/C][C]1.00086[/C][/ROW]
[ROW][C]38[/C][C]5.36[/C][C]5.35325[/C][C]5.33625[/C][C]1.00319[/C][C]1.00126[/C][/ROW]
[ROW][C]39[/C][C]5.33[/C][C]5.32523[/C][C]5.34375[/C][C]0.996534[/C][C]1.0009[/C][/ROW]
[ROW][C]40[/C][C]5.35[/C][C]5.34889[/C][C]5.35208[/C][C]0.999403[/C][C]1.00021[/C][/ROW]
[ROW][C]41[/C][C]5.35[/C][C]5.35927[/C][C]5.35917[/C][C]1.00002[/C][C]0.99827[/C][/ROW]
[ROW][C]42[/C][C]5.35[/C][C]5.37303[/C][C]5.36625[/C][C]1.00126[/C][C]0.995714[/C][/ROW]
[ROW][C]43[/C][C]5.37[/C][C]5.38028[/C][C]5.37208[/C][C]1.00153[/C][C]0.998089[/C][/ROW]
[ROW][C]44[/C][C]5.39[/C][C]5.38679[/C][C]5.375[/C][C]1.00219[/C][C]1.0006[/C][/ROW]
[ROW][C]45[/C][C]5.4[/C][C]5.36954[/C][C]5.37542[/C][C]0.998907[/C][C]1.00567[/C][/ROW]
[ROW][C]46[/C][C]5.39[/C][C]5.34668[/C][C]5.37542[/C][C]0.994655[/C][C]1.0081[/C][/ROW]
[ROW][C]47[/C][C]5.4[/C][C]5.38688[/C][C]5.37583[/C][C]1.00206[/C][C]1.00243[/C][/ROW]
[ROW][C]48[/C][C]5.4[/C][C]5.36461[/C][C]5.3775[/C][C]0.997603[/C][C]1.0066[/C][/ROW]
[ROW][C]49[/C][C]5.4[/C][C]5.39471[/C][C]5.38042[/C][C]1.00266[/C][C]1.00098[/C][/ROW]
[ROW][C]50[/C][C]5.38[/C][C]5.39965[/C][C]5.3825[/C][C]1.00319[/C][C]0.996361[/C][/ROW]
[ROW][C]51[/C][C]5.32[/C][C]5.36302[/C][C]5.38167[/C][C]0.996534[/C][C]0.991979[/C][/ROW]
[ROW][C]52[/C][C]5.36[/C][C]5.37637[/C][C]5.37958[/C][C]0.999403[/C][C]0.996955[/C][/ROW]
[ROW][C]53[/C][C]5.35[/C][C]5.37969[/C][C]5.37958[/C][C]1.00002[/C][C]0.994482[/C][/ROW]
[ROW][C]54[/C][C]5.39[/C][C]5.38471[/C][C]5.37792[/C][C]1.00126[/C][C]1.00098[/C][/ROW]
[ROW][C]55[/C][C]5.4[/C][C]5.38404[/C][C]5.37583[/C][C]1.00153[/C][C]1.00297[/C][/ROW]
[ROW][C]56[/C][C]5.41[/C][C]5.38887[/C][C]5.37708[/C][C]1.00219[/C][C]1.00392[/C][/ROW]
[ROW][C]57[/C][C]5.36[/C][C]5.37661[/C][C]5.3825[/C][C]0.998907[/C][C]0.99691[/C][/ROW]
[ROW][C]58[/C][C]5.38[/C][C]5.35994[/C][C]5.38875[/C][C]0.994655[/C][C]1.00374[/C][/ROW]
[ROW][C]59[/C][C]5.41[/C][C]5.40442[/C][C]5.39333[/C][C]1.00206[/C][C]1.00103[/C][/ROW]
[ROW][C]60[/C][C]5.35[/C][C]5.38414[/C][C]5.39708[/C][C]0.997603[/C][C]0.993658[/C][/ROW]
[ROW][C]61[/C][C]5.4[/C][C]5.41268[/C][C]5.39833[/C][C]1.00266[/C][C]0.997658[/C][/ROW]
[ROW][C]62[/C][C]5.41[/C][C]5.41595[/C][C]5.39875[/C][C]1.00319[/C][C]0.998902[/C][/ROW]
[ROW][C]63[/C][C]5.42[/C][C]5.38253[/C][C]5.40125[/C][C]0.996534[/C][C]1.00696[/C][/ROW]
[ROW][C]64[/C][C]5.41[/C][C]5.39844[/C][C]5.40167[/C][C]0.999403[/C][C]1.00214[/C][/ROW]
[ROW][C]65[/C][C]5.41[/C][C]5.40219[/C][C]5.40208[/C][C]1.00002[/C][C]1.00145[/C][/ROW]
[ROW][C]66[/C][C]5.42[/C][C]5.41517[/C][C]5.40833[/C][C]1.00126[/C][C]1.00089[/C][/ROW]
[ROW][C]67[/C][C]5.4[/C][C]5.42368[/C][C]5.41542[/C][C]1.00153[/C][C]0.995634[/C][/ROW]
[ROW][C]68[/C][C]5.42[/C][C]5.43314[/C][C]5.42125[/C][C]1.00219[/C][C]0.997582[/C][/ROW]
[ROW][C]69[/C][C]5.41[/C][C]5.41865[/C][C]5.42458[/C][C]0.998907[/C][C]0.998403[/C][/ROW]
[ROW][C]70[/C][C]5.34[/C][C]5.39973[/C][C]5.42875[/C][C]0.994655[/C][C]0.988938[/C][/ROW]
[ROW][C]71[/C][C]5.46[/C][C]5.44784[/C][C]5.43667[/C][C]1.00206[/C][C]1.00223[/C][/ROW]
[ROW][C]72[/C][C]5.45[/C][C]5.43153[/C][C]5.44458[/C][C]0.997603[/C][C]1.0034[/C][/ROW]
[ROW][C]73[/C][C]5.47[/C][C]5.46782[/C][C]5.45333[/C][C]1.00266[/C][C]1.0004[/C][/ROW]
[ROW][C]74[/C][C]5.48[/C][C]5.48116[/C][C]5.46375[/C][C]1.00319[/C][C]0.999789[/C][/ROW]
[ROW][C]75[/C][C]5.43[/C][C]5.45603[/C][C]5.475[/C][C]0.996534[/C][C]0.99523[/C][/ROW]
[ROW][C]76[/C][C]5.5[/C][C]5.48339[/C][C]5.48667[/C][C]0.999403[/C][C]1.00303[/C][/ROW]
[ROW][C]77[/C][C]5.51[/C][C]5.49886[/C][C]5.49875[/C][C]1.00002[/C][C]1.00203[/C][/ROW]
[ROW][C]78[/C][C]5.51[/C][C]5.5178[/C][C]5.51083[/C][C]1.00126[/C][C]0.998587[/C][/ROW]
[ROW][C]79[/C][C]5.52[/C][C]5.53385[/C][C]5.52542[/C][C]1.00153[/C][C]0.997498[/C][/ROW]
[ROW][C]80[/C][C]5.55[/C][C]5.55591[/C][C]5.54375[/C][C]1.00219[/C][C]0.998937[/C][/ROW]
[ROW][C]81[/C][C]5.55[/C][C]5.55767[/C][C]5.56375[/C][C]0.998907[/C][C]0.998621[/C][/ROW]
[ROW][C]82[/C][C]5.48[/C][C]5.55266[/C][C]5.5825[/C][C]0.994655[/C][C]0.986915[/C][/ROW]
[ROW][C]83[/C][C]5.61[/C][C]5.61276[/C][C]5.60125[/C][C]1.00206[/C][C]0.999508[/C][/ROW]
[ROW][C]84[/C][C]5.59[/C][C]5.60944[/C][C]5.62292[/C][C]0.997603[/C][C]0.996535[/C][/ROW]
[ROW][C]85[/C][C]5.68[/C][C]5.65958[/C][C]5.64458[/C][C]1.00266[/C][C]1.00361[/C][/ROW]
[ROW][C]86[/C][C]5.71[/C][C]5.68556[/C][C]5.6675[/C][C]1.00319[/C][C]1.0043[/C][/ROW]
[ROW][C]87[/C][C]5.68[/C][C]5.67153[/C][C]5.69125[/C][C]0.996534[/C][C]1.00149[/C][/ROW]
[ROW][C]88[/C][C]5.7[/C][C]5.71409[/C][C]5.7175[/C][C]0.999403[/C][C]0.997535[/C][/ROW]
[ROW][C]89[/C][C]5.76[/C][C]5.74428[/C][C]5.74417[/C][C]1.00002[/C][C]1.00274[/C][/ROW]
[ROW][C]90[/C][C]5.78[/C][C]5.77354[/C][C]5.76625[/C][C]1.00126[/C][C]1.00112[/C][/ROW]
[ROW][C]91[/C][C]5.77[/C][C]NA[/C][C]NA[/C][C]1.00153[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]5.85[/C][C]NA[/C][C]NA[/C][C]1.00219[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]5.82[/C][C]NA[/C][C]NA[/C][C]0.998907[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]5.84[/C][C]NA[/C][C]NA[/C][C]0.994655[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]5.89[/C][C]NA[/C][C]NA[/C][C]1.00206[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]5.84[/C][C]NA[/C][C]NA[/C][C]0.997603[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269170&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269170&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	5.06	NA	NA	1.00266	NA
2	5.05	NA	NA	1.00319	NA
3	5.05	NA	NA	0.996534	NA
4	5.04	NA	NA	0.999403	NA
5	5.06	NA	NA	1.00002	NA
6	5.07	NA	NA	1.00126	NA
7	5.09	5.08274	5.075	1.00153	1.00143
8	5.08	5.09239	5.08125	1.00219	0.997566
9	5.09	5.08319	5.08875	0.998907	1.00134
10	5.09	5.06942	5.09667	0.994655	1.00406
11	5.09	5.11424	5.10375	1.00206	0.99526
12	5.1	5.09775	5.11	0.997603	1.00044
13	5.12	5.12984	5.11625	1.00266	0.998081
14	5.14	5.13924	5.12292	1.00319	1.00015
15	5.14	5.11222	5.13	0.996534	1.00543
16	5.14	5.13402	5.13708	0.999403	1.00117
17	5.13	5.14593	5.14583	1.00002	0.996904
18	5.15	5.1611	5.15458	1.00126	0.99785
19	5.16	5.17038	5.1625	1.00153	0.997993
20	5.17	5.18217	5.17083	1.00219	0.997651
21	5.17	5.17225	5.17792	0.998907	0.999564
22	5.18	5.15728	5.185	0.994655	1.0044
23	5.21	5.2061	5.19542	1.00206	1.00075
24	5.19	5.19543	5.20792	0.997603	0.998955
25	5.22	5.2347	5.22083	1.00266	0.997191
26	5.24	5.25042	5.23375	1.00319	0.998015
27	5.21	5.22682	5.245	0.996534	0.996782
28	5.24	5.25186	5.255	0.999403	0.997741
29	5.28	5.26468	5.26458	1.00002	1.00291
30	5.3	5.28083	5.27417	1.00126	1.00363
31	5.32	5.29265	5.28458	1.00153	1.00517
32	5.32	5.30661	5.295	1.00219	1.00252
33	5.29	5.2992	5.305	0.998907	0.998264
34	5.3	5.28617	5.31458	0.994655	1.00262
35	5.32	5.33302	5.32208	1.00206	0.997558
36	5.31	5.31431	5.32708	0.997603	0.999189
37	5.35	5.34541	5.33125	1.00266	1.00086
38	5.36	5.35325	5.33625	1.00319	1.00126
39	5.33	5.32523	5.34375	0.996534	1.0009
40	5.35	5.34889	5.35208	0.999403	1.00021
41	5.35	5.35927	5.35917	1.00002	0.99827
42	5.35	5.37303	5.36625	1.00126	0.995714
43	5.37	5.38028	5.37208	1.00153	0.998089
44	5.39	5.38679	5.375	1.00219	1.0006
45	5.4	5.36954	5.37542	0.998907	1.00567
46	5.39	5.34668	5.37542	0.994655	1.0081
47	5.4	5.38688	5.37583	1.00206	1.00243
48	5.4	5.36461	5.3775	0.997603	1.0066
49	5.4	5.39471	5.38042	1.00266	1.00098
50	5.38	5.39965	5.3825	1.00319	0.996361
51	5.32	5.36302	5.38167	0.996534	0.991979
52	5.36	5.37637	5.37958	0.999403	0.996955
53	5.35	5.37969	5.37958	1.00002	0.994482
54	5.39	5.38471	5.37792	1.00126	1.00098
55	5.4	5.38404	5.37583	1.00153	1.00297
56	5.41	5.38887	5.37708	1.00219	1.00392
57	5.36	5.37661	5.3825	0.998907	0.99691
58	5.38	5.35994	5.38875	0.994655	1.00374
59	5.41	5.40442	5.39333	1.00206	1.00103
60	5.35	5.38414	5.39708	0.997603	0.993658
61	5.4	5.41268	5.39833	1.00266	0.997658
62	5.41	5.41595	5.39875	1.00319	0.998902
63	5.42	5.38253	5.40125	0.996534	1.00696
64	5.41	5.39844	5.40167	0.999403	1.00214
65	5.41	5.40219	5.40208	1.00002	1.00145
66	5.42	5.41517	5.40833	1.00126	1.00089
67	5.4	5.42368	5.41542	1.00153	0.995634
68	5.42	5.43314	5.42125	1.00219	0.997582
69	5.41	5.41865	5.42458	0.998907	0.998403
70	5.34	5.39973	5.42875	0.994655	0.988938
71	5.46	5.44784	5.43667	1.00206	1.00223
72	5.45	5.43153	5.44458	0.997603	1.0034
73	5.47	5.46782	5.45333	1.00266	1.0004
74	5.48	5.48116	5.46375	1.00319	0.999789
75	5.43	5.45603	5.475	0.996534	0.99523
76	5.5	5.48339	5.48667	0.999403	1.00303
77	5.51	5.49886	5.49875	1.00002	1.00203
78	5.51	5.5178	5.51083	1.00126	0.998587
79	5.52	5.53385	5.52542	1.00153	0.997498
80	5.55	5.55591	5.54375	1.00219	0.998937
81	5.55	5.55767	5.56375	0.998907	0.998621
82	5.48	5.55266	5.5825	0.994655	0.986915
83	5.61	5.61276	5.60125	1.00206	0.999508
84	5.59	5.60944	5.62292	0.997603	0.996535
85	5.68	5.65958	5.64458	1.00266	1.00361
86	5.71	5.68556	5.6675	1.00319	1.0043
87	5.68	5.67153	5.69125	0.996534	1.00149
88	5.7	5.71409	5.7175	0.999403	0.997535
89	5.76	5.74428	5.74417	1.00002	1.00274
90	5.78	5.77354	5.76625	1.00126	1.00112
91	5.77	NA	NA	1.00153	NA
92	5.85	NA	NA	1.00219	NA
93	5.82	NA	NA	0.998907	NA
94	5.84	NA	NA	0.994655	NA
95	5.89	NA	NA	1.00206	NA
96	5.84	NA	NA	0.997603	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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