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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 27 Nov 2014 11:58:22 +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/27/t1417089519hy0ffzuo01kjq9q.htm/, Retrieved Sun, 19 May 2024 22:35:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=259815, Retrieved Sun, 19 May 2024 22:35:10 +0000

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-       [Classical Decomposition] [] [2014-11-27 11:58:22] [7686dea5cfa8a11058319f854e13a03d] [Current]

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3,59
3,59
3,59
3,59
3,59
3,59
3,59
3,61
3,71
3,83
3,83
3,83
3,83
3,83
3,83
3,83
3,83
3,83
3,83
3,83
3,92
3,92
3,92
3,92
3,92
3,92
3,92
3,92
3,92
3,92
3,92
3,92
3,98
3,98
3,98
3,98
3,98
3,98
3,98
3,98
3,98
3,98
3,98
3,98
4,09
4,09
4,09
4,09
4,09
4,09
4,09
4,09
4,09
4,09
4,09
4,09
4,21
4,21
4,21
4,21
4,21
4,21
4,21
4,21
4,21
4,21
4,21
4,21
4,23
4,23
4,23
4,23

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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259815&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259815&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259815&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	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	3.59	NA	NA	0.0151806	NA
2	3.59	NA	NA	0.00501389	NA
3	3.59	NA	NA	-0.00431944	NA
4	3.59	NA	NA	-0.0119861	NA
5	3.59	NA	NA	-0.0186528	NA
6	3.59	NA	NA	-0.0253194	NA
7	3.59	3.62485	3.67167	-0.0468194	-0.0348472
8	3.61	3.63851	3.69167	-0.0531528	-0.0285139
9	3.71	3.74418	3.71167	0.0325139	-0.0341806
10	3.83	3.77785	3.73167	0.0461806	0.0521528
11	3.83	3.78751	3.75167	0.0358472	0.0424861
12	3.83	3.79718	3.77167	0.0255139	0.0328194
13	3.83	3.80685	3.79167	0.0151806	0.0231528
14	3.83	3.81585	3.81083	0.00501389	0.0141528
15	3.83	3.82443	3.82875	-0.00431944	0.00556944
16	3.83	3.82926	3.84125	-0.0119861	0.000736111
17	3.83	3.8301	3.84875	-0.0186528	-9.72222e-05
18	3.83	3.83093	3.85625	-0.0253194	-0.000930556
19	3.83	3.81693	3.86375	-0.0468194	0.0130694
20	3.83	3.8181	3.87125	-0.0531528	0.0119028
21	3.92	3.91126	3.87875	0.0325139	0.00873611
22	3.92	3.93243	3.88625	0.0461806	-0.0124306
23	3.92	3.9296	3.89375	0.0358472	-0.00959722
24	3.92	3.92676	3.90125	0.0255139	-0.00676389
25	3.92	3.92393	3.90875	0.0151806	-0.00393056
26	3.92	3.92126	3.91625	0.00501389	-0.00126389
27	3.92	3.91818	3.9225	-0.00431944	0.00181944
28	3.92	3.91551	3.9275	-0.0119861	0.00448611
29	3.92	3.91385	3.9325	-0.0186528	0.00615278
30	3.92	3.91218	3.9375	-0.0253194	0.00781944
31	3.92	3.89568	3.9425	-0.0468194	0.0243194
32	3.92	3.89435	3.9475	-0.0531528	0.0256528
33	3.98	3.98501	3.9525	0.0325139	-0.00501389
34	3.98	4.00368	3.9575	0.0461806	-0.0236806
35	3.98	3.99835	3.9625	0.0358472	-0.0183472
36	3.98	3.99301	3.9675	0.0255139	-0.0130139
37	3.98	3.98768	3.9725	0.0151806	-0.00768056
38	3.98	3.98251	3.9775	0.00501389	-0.00251389
39	3.98	3.98026	3.98458	-0.00431944	-0.000263889
40	3.98	3.98176	3.99375	-0.0119861	-0.00176389
41	3.98	3.98426	4.00292	-0.0186528	-0.00426389
42	3.98	3.98676	4.01208	-0.0253194	-0.00676389
43	3.98	3.97443	4.02125	-0.0468194	0.00556944
44	3.98	3.97726	4.03042	-0.0531528	0.00273611
45	4.09	4.0721	4.03958	0.0325139	0.0179028
46	4.09	4.09493	4.04875	0.0461806	-0.00493056
47	4.09	4.09376	4.05792	0.0358472	-0.00376389
48	4.09	4.0926	4.06708	0.0255139	-0.00259722
49	4.09	4.09143	4.07625	0.0151806	-0.00143056
50	4.09	4.09043	4.08542	0.00501389	-0.000430556
51	4.09	4.09068	4.095	-0.00431944	-0.000680556
52	4.09	4.09301	4.105	-0.0119861	-0.00301389
53	4.09	4.09635	4.115	-0.0186528	-0.00634722
54	4.09	4.09968	4.125	-0.0253194	-0.00968056
55	4.09	4.08818	4.135	-0.0468194	0.00181944
56	4.09	4.09185	4.145	-0.0531528	-0.00184722
57	4.21	4.18751	4.155	0.0325139	0.0224861
58	4.21	4.21118	4.165	0.0461806	-0.00118056
59	4.21	4.21085	4.175	0.0358472	-0.000847222
60	4.21	4.21051	4.185	0.0255139	-0.000513889
61	4.21	4.21018	4.195	0.0151806	-0.000180556
62	4.21	4.21001	4.205	0.00501389	-1.38889e-05
63	4.21	4.20651	4.21083	-0.00431944	0.00348611
64	4.21	4.20051	4.2125	-0.0119861	0.00948611
65	4.21	4.19551	4.21417	-0.0186528	0.0144861
66	4.21	4.19051	4.21583	-0.0253194	0.0194861
67	4.21	NA	NA	-0.0468194	NA
68	4.21	NA	NA	-0.0531528	NA
69	4.23	NA	NA	0.0325139	NA
70	4.23	NA	NA	0.0461806	NA
71	4.23	NA	NA	0.0358472	NA
72	4.23	NA	NA	0.0255139	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 3.59 & NA & NA & 0.0151806 & NA \tabularnewline
2 & 3.59 & NA & NA & 0.00501389 & NA \tabularnewline
3 & 3.59 & NA & NA & -0.00431944 & NA \tabularnewline
4 & 3.59 & NA & NA & -0.0119861 & NA \tabularnewline
5 & 3.59 & NA & NA & -0.0186528 & NA \tabularnewline
6 & 3.59 & NA & NA & -0.0253194 & NA \tabularnewline
7 & 3.59 & 3.62485 & 3.67167 & -0.0468194 & -0.0348472 \tabularnewline
8 & 3.61 & 3.63851 & 3.69167 & -0.0531528 & -0.0285139 \tabularnewline
9 & 3.71 & 3.74418 & 3.71167 & 0.0325139 & -0.0341806 \tabularnewline
10 & 3.83 & 3.77785 & 3.73167 & 0.0461806 & 0.0521528 \tabularnewline
11 & 3.83 & 3.78751 & 3.75167 & 0.0358472 & 0.0424861 \tabularnewline
12 & 3.83 & 3.79718 & 3.77167 & 0.0255139 & 0.0328194 \tabularnewline
13 & 3.83 & 3.80685 & 3.79167 & 0.0151806 & 0.0231528 \tabularnewline
14 & 3.83 & 3.81585 & 3.81083 & 0.00501389 & 0.0141528 \tabularnewline
15 & 3.83 & 3.82443 & 3.82875 & -0.00431944 & 0.00556944 \tabularnewline
16 & 3.83 & 3.82926 & 3.84125 & -0.0119861 & 0.000736111 \tabularnewline
17 & 3.83 & 3.8301 & 3.84875 & -0.0186528 & -9.72222e-05 \tabularnewline
18 & 3.83 & 3.83093 & 3.85625 & -0.0253194 & -0.000930556 \tabularnewline
19 & 3.83 & 3.81693 & 3.86375 & -0.0468194 & 0.0130694 \tabularnewline
20 & 3.83 & 3.8181 & 3.87125 & -0.0531528 & 0.0119028 \tabularnewline
21 & 3.92 & 3.91126 & 3.87875 & 0.0325139 & 0.00873611 \tabularnewline
22 & 3.92 & 3.93243 & 3.88625 & 0.0461806 & -0.0124306 \tabularnewline
23 & 3.92 & 3.9296 & 3.89375 & 0.0358472 & -0.00959722 \tabularnewline
24 & 3.92 & 3.92676 & 3.90125 & 0.0255139 & -0.00676389 \tabularnewline
25 & 3.92 & 3.92393 & 3.90875 & 0.0151806 & -0.00393056 \tabularnewline
26 & 3.92 & 3.92126 & 3.91625 & 0.00501389 & -0.00126389 \tabularnewline
27 & 3.92 & 3.91818 & 3.9225 & -0.00431944 & 0.00181944 \tabularnewline
28 & 3.92 & 3.91551 & 3.9275 & -0.0119861 & 0.00448611 \tabularnewline
29 & 3.92 & 3.91385 & 3.9325 & -0.0186528 & 0.00615278 \tabularnewline
30 & 3.92 & 3.91218 & 3.9375 & -0.0253194 & 0.00781944 \tabularnewline
31 & 3.92 & 3.89568 & 3.9425 & -0.0468194 & 0.0243194 \tabularnewline
32 & 3.92 & 3.89435 & 3.9475 & -0.0531528 & 0.0256528 \tabularnewline
33 & 3.98 & 3.98501 & 3.9525 & 0.0325139 & -0.00501389 \tabularnewline
34 & 3.98 & 4.00368 & 3.9575 & 0.0461806 & -0.0236806 \tabularnewline
35 & 3.98 & 3.99835 & 3.9625 & 0.0358472 & -0.0183472 \tabularnewline
36 & 3.98 & 3.99301 & 3.9675 & 0.0255139 & -0.0130139 \tabularnewline
37 & 3.98 & 3.98768 & 3.9725 & 0.0151806 & -0.00768056 \tabularnewline
38 & 3.98 & 3.98251 & 3.9775 & 0.00501389 & -0.00251389 \tabularnewline
39 & 3.98 & 3.98026 & 3.98458 & -0.00431944 & -0.000263889 \tabularnewline
40 & 3.98 & 3.98176 & 3.99375 & -0.0119861 & -0.00176389 \tabularnewline
41 & 3.98 & 3.98426 & 4.00292 & -0.0186528 & -0.00426389 \tabularnewline
42 & 3.98 & 3.98676 & 4.01208 & -0.0253194 & -0.00676389 \tabularnewline
43 & 3.98 & 3.97443 & 4.02125 & -0.0468194 & 0.00556944 \tabularnewline
44 & 3.98 & 3.97726 & 4.03042 & -0.0531528 & 0.00273611 \tabularnewline
45 & 4.09 & 4.0721 & 4.03958 & 0.0325139 & 0.0179028 \tabularnewline
46 & 4.09 & 4.09493 & 4.04875 & 0.0461806 & -0.00493056 \tabularnewline
47 & 4.09 & 4.09376 & 4.05792 & 0.0358472 & -0.00376389 \tabularnewline
48 & 4.09 & 4.0926 & 4.06708 & 0.0255139 & -0.00259722 \tabularnewline
49 & 4.09 & 4.09143 & 4.07625 & 0.0151806 & -0.00143056 \tabularnewline
50 & 4.09 & 4.09043 & 4.08542 & 0.00501389 & -0.000430556 \tabularnewline
51 & 4.09 & 4.09068 & 4.095 & -0.00431944 & -0.000680556 \tabularnewline
52 & 4.09 & 4.09301 & 4.105 & -0.0119861 & -0.00301389 \tabularnewline
53 & 4.09 & 4.09635 & 4.115 & -0.0186528 & -0.00634722 \tabularnewline
54 & 4.09 & 4.09968 & 4.125 & -0.0253194 & -0.00968056 \tabularnewline
55 & 4.09 & 4.08818 & 4.135 & -0.0468194 & 0.00181944 \tabularnewline
56 & 4.09 & 4.09185 & 4.145 & -0.0531528 & -0.00184722 \tabularnewline
57 & 4.21 & 4.18751 & 4.155 & 0.0325139 & 0.0224861 \tabularnewline
58 & 4.21 & 4.21118 & 4.165 & 0.0461806 & -0.00118056 \tabularnewline
59 & 4.21 & 4.21085 & 4.175 & 0.0358472 & -0.000847222 \tabularnewline
60 & 4.21 & 4.21051 & 4.185 & 0.0255139 & -0.000513889 \tabularnewline
61 & 4.21 & 4.21018 & 4.195 & 0.0151806 & -0.000180556 \tabularnewline
62 & 4.21 & 4.21001 & 4.205 & 0.00501389 & -1.38889e-05 \tabularnewline
63 & 4.21 & 4.20651 & 4.21083 & -0.00431944 & 0.00348611 \tabularnewline
64 & 4.21 & 4.20051 & 4.2125 & -0.0119861 & 0.00948611 \tabularnewline
65 & 4.21 & 4.19551 & 4.21417 & -0.0186528 & 0.0144861 \tabularnewline
66 & 4.21 & 4.19051 & 4.21583 & -0.0253194 & 0.0194861 \tabularnewline
67 & 4.21 & NA & NA & -0.0468194 & NA \tabularnewline
68 & 4.21 & NA & NA & -0.0531528 & NA \tabularnewline
69 & 4.23 & NA & NA & 0.0325139 & NA \tabularnewline
70 & 4.23 & NA & NA & 0.0461806 & NA \tabularnewline
71 & 4.23 & NA & NA & 0.0358472 & NA \tabularnewline
72 & 4.23 & NA & NA & 0.0255139 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259815&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]3.59[/C][C]NA[/C][C]NA[/C][C]0.0151806[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3.59[/C][C]NA[/C][C]NA[/C][C]0.00501389[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3.59[/C][C]NA[/C][C]NA[/C][C]-0.00431944[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3.59[/C][C]NA[/C][C]NA[/C][C]-0.0119861[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]3.59[/C][C]NA[/C][C]NA[/C][C]-0.0186528[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3.59[/C][C]NA[/C][C]NA[/C][C]-0.0253194[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]3.59[/C][C]3.62485[/C][C]3.67167[/C][C]-0.0468194[/C][C]-0.0348472[/C][/ROW]
[ROW][C]8[/C][C]3.61[/C][C]3.63851[/C][C]3.69167[/C][C]-0.0531528[/C][C]-0.0285139[/C][/ROW]
[ROW][C]9[/C][C]3.71[/C][C]3.74418[/C][C]3.71167[/C][C]0.0325139[/C][C]-0.0341806[/C][/ROW]
[ROW][C]10[/C][C]3.83[/C][C]3.77785[/C][C]3.73167[/C][C]0.0461806[/C][C]0.0521528[/C][/ROW]
[ROW][C]11[/C][C]3.83[/C][C]3.78751[/C][C]3.75167[/C][C]0.0358472[/C][C]0.0424861[/C][/ROW]
[ROW][C]12[/C][C]3.83[/C][C]3.79718[/C][C]3.77167[/C][C]0.0255139[/C][C]0.0328194[/C][/ROW]
[ROW][C]13[/C][C]3.83[/C][C]3.80685[/C][C]3.79167[/C][C]0.0151806[/C][C]0.0231528[/C][/ROW]
[ROW][C]14[/C][C]3.83[/C][C]3.81585[/C][C]3.81083[/C][C]0.00501389[/C][C]0.0141528[/C][/ROW]
[ROW][C]15[/C][C]3.83[/C][C]3.82443[/C][C]3.82875[/C][C]-0.00431944[/C][C]0.00556944[/C][/ROW]
[ROW][C]16[/C][C]3.83[/C][C]3.82926[/C][C]3.84125[/C][C]-0.0119861[/C][C]0.000736111[/C][/ROW]
[ROW][C]17[/C][C]3.83[/C][C]3.8301[/C][C]3.84875[/C][C]-0.0186528[/C][C]-9.72222e-05[/C][/ROW]
[ROW][C]18[/C][C]3.83[/C][C]3.83093[/C][C]3.85625[/C][C]-0.0253194[/C][C]-0.000930556[/C][/ROW]
[ROW][C]19[/C][C]3.83[/C][C]3.81693[/C][C]3.86375[/C][C]-0.0468194[/C][C]0.0130694[/C][/ROW]
[ROW][C]20[/C][C]3.83[/C][C]3.8181[/C][C]3.87125[/C][C]-0.0531528[/C][C]0.0119028[/C][/ROW]
[ROW][C]21[/C][C]3.92[/C][C]3.91126[/C][C]3.87875[/C][C]0.0325139[/C][C]0.00873611[/C][/ROW]
[ROW][C]22[/C][C]3.92[/C][C]3.93243[/C][C]3.88625[/C][C]0.0461806[/C][C]-0.0124306[/C][/ROW]
[ROW][C]23[/C][C]3.92[/C][C]3.9296[/C][C]3.89375[/C][C]0.0358472[/C][C]-0.00959722[/C][/ROW]
[ROW][C]24[/C][C]3.92[/C][C]3.92676[/C][C]3.90125[/C][C]0.0255139[/C][C]-0.00676389[/C][/ROW]
[ROW][C]25[/C][C]3.92[/C][C]3.92393[/C][C]3.90875[/C][C]0.0151806[/C][C]-0.00393056[/C][/ROW]
[ROW][C]26[/C][C]3.92[/C][C]3.92126[/C][C]3.91625[/C][C]0.00501389[/C][C]-0.00126389[/C][/ROW]
[ROW][C]27[/C][C]3.92[/C][C]3.91818[/C][C]3.9225[/C][C]-0.00431944[/C][C]0.00181944[/C][/ROW]
[ROW][C]28[/C][C]3.92[/C][C]3.91551[/C][C]3.9275[/C][C]-0.0119861[/C][C]0.00448611[/C][/ROW]
[ROW][C]29[/C][C]3.92[/C][C]3.91385[/C][C]3.9325[/C][C]-0.0186528[/C][C]0.00615278[/C][/ROW]
[ROW][C]30[/C][C]3.92[/C][C]3.91218[/C][C]3.9375[/C][C]-0.0253194[/C][C]0.00781944[/C][/ROW]
[ROW][C]31[/C][C]3.92[/C][C]3.89568[/C][C]3.9425[/C][C]-0.0468194[/C][C]0.0243194[/C][/ROW]
[ROW][C]32[/C][C]3.92[/C][C]3.89435[/C][C]3.9475[/C][C]-0.0531528[/C][C]0.0256528[/C][/ROW]
[ROW][C]33[/C][C]3.98[/C][C]3.98501[/C][C]3.9525[/C][C]0.0325139[/C][C]-0.00501389[/C][/ROW]
[ROW][C]34[/C][C]3.98[/C][C]4.00368[/C][C]3.9575[/C][C]0.0461806[/C][C]-0.0236806[/C][/ROW]
[ROW][C]35[/C][C]3.98[/C][C]3.99835[/C][C]3.9625[/C][C]0.0358472[/C][C]-0.0183472[/C][/ROW]
[ROW][C]36[/C][C]3.98[/C][C]3.99301[/C][C]3.9675[/C][C]0.0255139[/C][C]-0.0130139[/C][/ROW]
[ROW][C]37[/C][C]3.98[/C][C]3.98768[/C][C]3.9725[/C][C]0.0151806[/C][C]-0.00768056[/C][/ROW]
[ROW][C]38[/C][C]3.98[/C][C]3.98251[/C][C]3.9775[/C][C]0.00501389[/C][C]-0.00251389[/C][/ROW]
[ROW][C]39[/C][C]3.98[/C][C]3.98026[/C][C]3.98458[/C][C]-0.00431944[/C][C]-0.000263889[/C][/ROW]
[ROW][C]40[/C][C]3.98[/C][C]3.98176[/C][C]3.99375[/C][C]-0.0119861[/C][C]-0.00176389[/C][/ROW]
[ROW][C]41[/C][C]3.98[/C][C]3.98426[/C][C]4.00292[/C][C]-0.0186528[/C][C]-0.00426389[/C][/ROW]
[ROW][C]42[/C][C]3.98[/C][C]3.98676[/C][C]4.01208[/C][C]-0.0253194[/C][C]-0.00676389[/C][/ROW]
[ROW][C]43[/C][C]3.98[/C][C]3.97443[/C][C]4.02125[/C][C]-0.0468194[/C][C]0.00556944[/C][/ROW]
[ROW][C]44[/C][C]3.98[/C][C]3.97726[/C][C]4.03042[/C][C]-0.0531528[/C][C]0.00273611[/C][/ROW]
[ROW][C]45[/C][C]4.09[/C][C]4.0721[/C][C]4.03958[/C][C]0.0325139[/C][C]0.0179028[/C][/ROW]
[ROW][C]46[/C][C]4.09[/C][C]4.09493[/C][C]4.04875[/C][C]0.0461806[/C][C]-0.00493056[/C][/ROW]
[ROW][C]47[/C][C]4.09[/C][C]4.09376[/C][C]4.05792[/C][C]0.0358472[/C][C]-0.00376389[/C][/ROW]
[ROW][C]48[/C][C]4.09[/C][C]4.0926[/C][C]4.06708[/C][C]0.0255139[/C][C]-0.00259722[/C][/ROW]
[ROW][C]49[/C][C]4.09[/C][C]4.09143[/C][C]4.07625[/C][C]0.0151806[/C][C]-0.00143056[/C][/ROW]
[ROW][C]50[/C][C]4.09[/C][C]4.09043[/C][C]4.08542[/C][C]0.00501389[/C][C]-0.000430556[/C][/ROW]
[ROW][C]51[/C][C]4.09[/C][C]4.09068[/C][C]4.095[/C][C]-0.00431944[/C][C]-0.000680556[/C][/ROW]
[ROW][C]52[/C][C]4.09[/C][C]4.09301[/C][C]4.105[/C][C]-0.0119861[/C][C]-0.00301389[/C][/ROW]
[ROW][C]53[/C][C]4.09[/C][C]4.09635[/C][C]4.115[/C][C]-0.0186528[/C][C]-0.00634722[/C][/ROW]
[ROW][C]54[/C][C]4.09[/C][C]4.09968[/C][C]4.125[/C][C]-0.0253194[/C][C]-0.00968056[/C][/ROW]
[ROW][C]55[/C][C]4.09[/C][C]4.08818[/C][C]4.135[/C][C]-0.0468194[/C][C]0.00181944[/C][/ROW]
[ROW][C]56[/C][C]4.09[/C][C]4.09185[/C][C]4.145[/C][C]-0.0531528[/C][C]-0.00184722[/C][/ROW]
[ROW][C]57[/C][C]4.21[/C][C]4.18751[/C][C]4.155[/C][C]0.0325139[/C][C]0.0224861[/C][/ROW]
[ROW][C]58[/C][C]4.21[/C][C]4.21118[/C][C]4.165[/C][C]0.0461806[/C][C]-0.00118056[/C][/ROW]
[ROW][C]59[/C][C]4.21[/C][C]4.21085[/C][C]4.175[/C][C]0.0358472[/C][C]-0.000847222[/C][/ROW]
[ROW][C]60[/C][C]4.21[/C][C]4.21051[/C][C]4.185[/C][C]0.0255139[/C][C]-0.000513889[/C][/ROW]
[ROW][C]61[/C][C]4.21[/C][C]4.21018[/C][C]4.195[/C][C]0.0151806[/C][C]-0.000180556[/C][/ROW]
[ROW][C]62[/C][C]4.21[/C][C]4.21001[/C][C]4.205[/C][C]0.00501389[/C][C]-1.38889e-05[/C][/ROW]
[ROW][C]63[/C][C]4.21[/C][C]4.20651[/C][C]4.21083[/C][C]-0.00431944[/C][C]0.00348611[/C][/ROW]
[ROW][C]64[/C][C]4.21[/C][C]4.20051[/C][C]4.2125[/C][C]-0.0119861[/C][C]0.00948611[/C][/ROW]
[ROW][C]65[/C][C]4.21[/C][C]4.19551[/C][C]4.21417[/C][C]-0.0186528[/C][C]0.0144861[/C][/ROW]
[ROW][C]66[/C][C]4.21[/C][C]4.19051[/C][C]4.21583[/C][C]-0.0253194[/C][C]0.0194861[/C][/ROW]
[ROW][C]67[/C][C]4.21[/C][C]NA[/C][C]NA[/C][C]-0.0468194[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]4.21[/C][C]NA[/C][C]NA[/C][C]-0.0531528[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]4.23[/C][C]NA[/C][C]NA[/C][C]0.0325139[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]4.23[/C][C]NA[/C][C]NA[/C][C]0.0461806[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]4.23[/C][C]NA[/C][C]NA[/C][C]0.0358472[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]4.23[/C][C]NA[/C][C]NA[/C][C]0.0255139[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259815&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259815&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	3.59	NA	NA	0.0151806	NA
2	3.59	NA	NA	0.00501389	NA
3	3.59	NA	NA	-0.00431944	NA
4	3.59	NA	NA	-0.0119861	NA
5	3.59	NA	NA	-0.0186528	NA
6	3.59	NA	NA	-0.0253194	NA
7	3.59	3.62485	3.67167	-0.0468194	-0.0348472
8	3.61	3.63851	3.69167	-0.0531528	-0.0285139
9	3.71	3.74418	3.71167	0.0325139	-0.0341806
10	3.83	3.77785	3.73167	0.0461806	0.0521528
11	3.83	3.78751	3.75167	0.0358472	0.0424861
12	3.83	3.79718	3.77167	0.0255139	0.0328194
13	3.83	3.80685	3.79167	0.0151806	0.0231528
14	3.83	3.81585	3.81083	0.00501389	0.0141528
15	3.83	3.82443	3.82875	-0.00431944	0.00556944
16	3.83	3.82926	3.84125	-0.0119861	0.000736111
17	3.83	3.8301	3.84875	-0.0186528	-9.72222e-05
18	3.83	3.83093	3.85625	-0.0253194	-0.000930556
19	3.83	3.81693	3.86375	-0.0468194	0.0130694
20	3.83	3.8181	3.87125	-0.0531528	0.0119028
21	3.92	3.91126	3.87875	0.0325139	0.00873611
22	3.92	3.93243	3.88625	0.0461806	-0.0124306
23	3.92	3.9296	3.89375	0.0358472	-0.00959722
24	3.92	3.92676	3.90125	0.0255139	-0.00676389
25	3.92	3.92393	3.90875	0.0151806	-0.00393056
26	3.92	3.92126	3.91625	0.00501389	-0.00126389
27	3.92	3.91818	3.9225	-0.00431944	0.00181944
28	3.92	3.91551	3.9275	-0.0119861	0.00448611
29	3.92	3.91385	3.9325	-0.0186528	0.00615278
30	3.92	3.91218	3.9375	-0.0253194	0.00781944
31	3.92	3.89568	3.9425	-0.0468194	0.0243194
32	3.92	3.89435	3.9475	-0.0531528	0.0256528
33	3.98	3.98501	3.9525	0.0325139	-0.00501389
34	3.98	4.00368	3.9575	0.0461806	-0.0236806
35	3.98	3.99835	3.9625	0.0358472	-0.0183472
36	3.98	3.99301	3.9675	0.0255139	-0.0130139
37	3.98	3.98768	3.9725	0.0151806	-0.00768056
38	3.98	3.98251	3.9775	0.00501389	-0.00251389
39	3.98	3.98026	3.98458	-0.00431944	-0.000263889
40	3.98	3.98176	3.99375	-0.0119861	-0.00176389
41	3.98	3.98426	4.00292	-0.0186528	-0.00426389
42	3.98	3.98676	4.01208	-0.0253194	-0.00676389
43	3.98	3.97443	4.02125	-0.0468194	0.00556944
44	3.98	3.97726	4.03042	-0.0531528	0.00273611
45	4.09	4.0721	4.03958	0.0325139	0.0179028
46	4.09	4.09493	4.04875	0.0461806	-0.00493056
47	4.09	4.09376	4.05792	0.0358472	-0.00376389
48	4.09	4.0926	4.06708	0.0255139	-0.00259722
49	4.09	4.09143	4.07625	0.0151806	-0.00143056
50	4.09	4.09043	4.08542	0.00501389	-0.000430556
51	4.09	4.09068	4.095	-0.00431944	-0.000680556
52	4.09	4.09301	4.105	-0.0119861	-0.00301389
53	4.09	4.09635	4.115	-0.0186528	-0.00634722
54	4.09	4.09968	4.125	-0.0253194	-0.00968056
55	4.09	4.08818	4.135	-0.0468194	0.00181944
56	4.09	4.09185	4.145	-0.0531528	-0.00184722
57	4.21	4.18751	4.155	0.0325139	0.0224861
58	4.21	4.21118	4.165	0.0461806	-0.00118056
59	4.21	4.21085	4.175	0.0358472	-0.000847222
60	4.21	4.21051	4.185	0.0255139	-0.000513889
61	4.21	4.21018	4.195	0.0151806	-0.000180556
62	4.21	4.21001	4.205	0.00501389	-1.38889e-05
63	4.21	4.20651	4.21083	-0.00431944	0.00348611
64	4.21	4.20051	4.2125	-0.0119861	0.00948611
65	4.21	4.19551	4.21417	-0.0186528	0.0144861
66	4.21	4.19051	4.21583	-0.0253194	0.0194861
67	4.21	NA	NA	-0.0468194	NA
68	4.21	NA	NA	-0.0531528	NA
69	4.23	NA	NA	0.0325139	NA
70	4.23	NA	NA	0.0461806	NA
71	4.23	NA	NA	0.0358472	NA
72	4.23	NA	NA	0.0255139	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