Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 07 Dec 2010 13:33:40 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/07/t12917287659hplrbujagv481p.htm/, Retrieved Fri, 03 May 2024 15:29:06 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106291, Retrieved Fri, 03 May 2024 15:29:06 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

110

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

-     [Classical Decomposition] [HPC Retail Sales] [2008-03-02 16:19:32] [74be16979710d4c4e7c6647856088456]
-  M D    [Classical Decomposition] [Workshop 8] [2010-12-07 13:33:40] [d42b17bf3b3c0d56878eb3f5a4351e6d] [Current]
-    D      [Classical Decomposition] [] [2010-12-27 12:52:22] [1ec36cc0fd92fd0f07d0b885ce2c369b] 

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106291&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106291&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106291&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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	103.48	NA	NA	-0.25884259259259	NA
2	103.93	NA	NA	0.152685185185183	NA
3	103.89	NA	NA	0.0411574074074023	NA
4	104.4	NA	NA	0.189212962962956	NA
5	104.79	NA	NA	0.273240740740743	NA
6	104.77	NA	NA	0.229629629629633	NA
7	105.13	105.067407407407	104.698333333333	0.369074074074079	0.0625925925925799
8	105.26	104.866851851852	104.846666666667	0.020185185185185	0.393148148148157
9	104.96	104.825740740741	105.002083333333	-0.176342592592589	0.134259259259252
10	104.75	104.921018518519	105.158333333333	-0.237314814814813	-0.171018518518508
11	105.01	105.056574074074	105.291666666667	-0.235092592592602	-0.0465740740740586
12	105.15	105.036157407407	105.40375	-0.367592592592586	0.11384259259259
13	105.2	105.261157407407	105.52	-0.25884259259259	-0.061157407407407
14	105.77	105.781851851852	105.629166666667	0.152685185185183	-0.0118518518518584
15	105.78	105.785324074074	105.744166666667	0.0411574074074023	-0.00532407407406765
16	106.26	106.09712962963	105.907916666667	0.189212962962956	0.162870370370385
17	106.13	106.407824074074	106.134583333333	0.273240740740743	-0.277824074074076
18	106.12	106.62837962963	106.39875	0.229629629629633	-0.508379629629616
19	106.57	107.054907407407	106.685833333333	0.369074074074079	-0.48490740740742
20	106.44	107.018101851852	106.997916666667	0.020185185185185	-0.578101851851855
21	106.54	107.175324074074	107.351666666667	-0.176342592592589	-0.635324074074063
22	107.1	107.491435185185	107.72875	-0.237314814814813	-0.391435185185188
23	108.1	107.907824074074	108.142916666667	-0.235092592592602	0.192175925925937
24	108.4	108.262407407407	108.63	-0.367592592592586	0.137592592592597
25	108.84	108.890324074074	109.149166666667	-0.25884259259259	-0.0503240740740694
26	109.62	109.803518518519	109.650833333333	0.152685185185183	-0.183518518518497
27	110.42	110.173657407407	110.1325	0.0411574074074023	0.246342592592597
28	110.67	110.775046296296	110.585833333333	0.189212962962956	-0.105046296296294
29	111.66	111.211157407407	110.937916666667	0.273240740740743	0.448842592592584
30	112.28	111.427546296296	111.197916666667	0.229629629629633	0.852453703703702
31	112.87	111.790740740741	111.421666666667	0.369074074074079	1.07925925925927
32	112.18	111.635185185185	111.615	0.020185185185185	0.544814814814828
33	112.36	111.555324074074	111.731666666667	-0.176342592592589	0.804675925925935
34	112.16	111.550185185185	111.7875	-0.237314814814813	0.609814814814825
35	111.49	111.562824074074	111.797916666667	-0.235092592592602	-0.0728240740740631
36	111.25	111.361574074074	111.729166666667	-0.367592592592586	-0.11157407407407
37	111.36	111.339490740741	111.598333333333	-0.25884259259259	0.0205092592592564
38	111.74	111.635601851852	111.482916666667	0.152685185185183	0.104398148148164
39	111.1	111.431990740741	111.390833333333	0.0411574074074023	-0.331990740740721
40	111.33	111.478796296296	111.289583333333	0.189212962962956	-0.148796296296297
41	111.25	111.511990740741	111.23875	0.273240740740743	-0.261990740740728
42	111.04	111.475046296296	111.245416666667	0.229629629629633	-0.435046296296278
43	110.97	111.655324074074	111.28625	0.369074074074079	-0.68532407407406
44	111.31	111.367685185185	111.3475	0.020185185185185	-0.0576851851851785
45	111.02	111.280324074074	111.456666666667	-0.176342592592589	-0.260324074074077
46	111.07	111.379351851852	111.616666666667	-0.237314814814813	-0.309351851851858
47	111.36	111.570324074074	111.805416666667	-0.235092592592602	-0.210324074074066
48	111.54	111.656990740741	112.024583333333	-0.367592592592586	-0.116990740740732
49	112.05	NA	112.257083333333	NA	NA
50	112.52	NA	112.483333333333	NA	NA
51	112.94	NA	112.725416666667	NA	NA
52	113.33	NA	112.999166666667	NA	NA
53	113.78	NA	NA	NA	NA
54	113.77	NA	NA	NA	NA
55	113.82	NA	NA	NA	NA
56	113.89	NA	NA	NA	NA
57	114.25	NA	NA	NA	NA
58	114.41	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 103.48 & NA & NA & -0.25884259259259 & NA \tabularnewline
2 & 103.93 & NA & NA & 0.152685185185183 & NA \tabularnewline
3 & 103.89 & NA & NA & 0.0411574074074023 & NA \tabularnewline
4 & 104.4 & NA & NA & 0.189212962962956 & NA \tabularnewline
5 & 104.79 & NA & NA & 0.273240740740743 & NA \tabularnewline
6 & 104.77 & NA & NA & 0.229629629629633 & NA \tabularnewline
7 & 105.13 & 105.067407407407 & 104.698333333333 & 0.369074074074079 & 0.0625925925925799 \tabularnewline
8 & 105.26 & 104.866851851852 & 104.846666666667 & 0.020185185185185 & 0.393148148148157 \tabularnewline
9 & 104.96 & 104.825740740741 & 105.002083333333 & -0.176342592592589 & 0.134259259259252 \tabularnewline
10 & 104.75 & 104.921018518519 & 105.158333333333 & -0.237314814814813 & -0.171018518518508 \tabularnewline
11 & 105.01 & 105.056574074074 & 105.291666666667 & -0.235092592592602 & -0.0465740740740586 \tabularnewline
12 & 105.15 & 105.036157407407 & 105.40375 & -0.367592592592586 & 0.11384259259259 \tabularnewline
13 & 105.2 & 105.261157407407 & 105.52 & -0.25884259259259 & -0.061157407407407 \tabularnewline
14 & 105.77 & 105.781851851852 & 105.629166666667 & 0.152685185185183 & -0.0118518518518584 \tabularnewline
15 & 105.78 & 105.785324074074 & 105.744166666667 & 0.0411574074074023 & -0.00532407407406765 \tabularnewline
16 & 106.26 & 106.09712962963 & 105.907916666667 & 0.189212962962956 & 0.162870370370385 \tabularnewline
17 & 106.13 & 106.407824074074 & 106.134583333333 & 0.273240740740743 & -0.277824074074076 \tabularnewline
18 & 106.12 & 106.62837962963 & 106.39875 & 0.229629629629633 & -0.508379629629616 \tabularnewline
19 & 106.57 & 107.054907407407 & 106.685833333333 & 0.369074074074079 & -0.48490740740742 \tabularnewline
20 & 106.44 & 107.018101851852 & 106.997916666667 & 0.020185185185185 & -0.578101851851855 \tabularnewline
21 & 106.54 & 107.175324074074 & 107.351666666667 & -0.176342592592589 & -0.635324074074063 \tabularnewline
22 & 107.1 & 107.491435185185 & 107.72875 & -0.237314814814813 & -0.391435185185188 \tabularnewline
23 & 108.1 & 107.907824074074 & 108.142916666667 & -0.235092592592602 & 0.192175925925937 \tabularnewline
24 & 108.4 & 108.262407407407 & 108.63 & -0.367592592592586 & 0.137592592592597 \tabularnewline
25 & 108.84 & 108.890324074074 & 109.149166666667 & -0.25884259259259 & -0.0503240740740694 \tabularnewline
26 & 109.62 & 109.803518518519 & 109.650833333333 & 0.152685185185183 & -0.183518518518497 \tabularnewline
27 & 110.42 & 110.173657407407 & 110.1325 & 0.0411574074074023 & 0.246342592592597 \tabularnewline
28 & 110.67 & 110.775046296296 & 110.585833333333 & 0.189212962962956 & -0.105046296296294 \tabularnewline
29 & 111.66 & 111.211157407407 & 110.937916666667 & 0.273240740740743 & 0.448842592592584 \tabularnewline
30 & 112.28 & 111.427546296296 & 111.197916666667 & 0.229629629629633 & 0.852453703703702 \tabularnewline
31 & 112.87 & 111.790740740741 & 111.421666666667 & 0.369074074074079 & 1.07925925925927 \tabularnewline
32 & 112.18 & 111.635185185185 & 111.615 & 0.020185185185185 & 0.544814814814828 \tabularnewline
33 & 112.36 & 111.555324074074 & 111.731666666667 & -0.176342592592589 & 0.804675925925935 \tabularnewline
34 & 112.16 & 111.550185185185 & 111.7875 & -0.237314814814813 & 0.609814814814825 \tabularnewline
35 & 111.49 & 111.562824074074 & 111.797916666667 & -0.235092592592602 & -0.0728240740740631 \tabularnewline
36 & 111.25 & 111.361574074074 & 111.729166666667 & -0.367592592592586 & -0.11157407407407 \tabularnewline
37 & 111.36 & 111.339490740741 & 111.598333333333 & -0.25884259259259 & 0.0205092592592564 \tabularnewline
38 & 111.74 & 111.635601851852 & 111.482916666667 & 0.152685185185183 & 0.104398148148164 \tabularnewline
39 & 111.1 & 111.431990740741 & 111.390833333333 & 0.0411574074074023 & -0.331990740740721 \tabularnewline
40 & 111.33 & 111.478796296296 & 111.289583333333 & 0.189212962962956 & -0.148796296296297 \tabularnewline
41 & 111.25 & 111.511990740741 & 111.23875 & 0.273240740740743 & -0.261990740740728 \tabularnewline
42 & 111.04 & 111.475046296296 & 111.245416666667 & 0.229629629629633 & -0.435046296296278 \tabularnewline
43 & 110.97 & 111.655324074074 & 111.28625 & 0.369074074074079 & -0.68532407407406 \tabularnewline
44 & 111.31 & 111.367685185185 & 111.3475 & 0.020185185185185 & -0.0576851851851785 \tabularnewline
45 & 111.02 & 111.280324074074 & 111.456666666667 & -0.176342592592589 & -0.260324074074077 \tabularnewline
46 & 111.07 & 111.379351851852 & 111.616666666667 & -0.237314814814813 & -0.309351851851858 \tabularnewline
47 & 111.36 & 111.570324074074 & 111.805416666667 & -0.235092592592602 & -0.210324074074066 \tabularnewline
48 & 111.54 & 111.656990740741 & 112.024583333333 & -0.367592592592586 & -0.116990740740732 \tabularnewline
49 & 112.05 & NA & 112.257083333333 & NA & NA \tabularnewline
50 & 112.52 & NA & 112.483333333333 & NA & NA \tabularnewline
51 & 112.94 & NA & 112.725416666667 & NA & NA \tabularnewline
52 & 113.33 & NA & 112.999166666667 & NA & NA \tabularnewline
53 & 113.78 & NA & NA & NA & NA \tabularnewline
54 & 113.77 & NA & NA & NA & NA \tabularnewline
55 & 113.82 & NA & NA & NA & NA \tabularnewline
56 & 113.89 & NA & NA & NA & NA \tabularnewline
57 & 114.25 & NA & NA & NA & NA \tabularnewline
58 & 114.41 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106291&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]103.48[/C][C]NA[/C][C]NA[/C][C]-0.25884259259259[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]103.93[/C][C]NA[/C][C]NA[/C][C]0.152685185185183[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]103.89[/C][C]NA[/C][C]NA[/C][C]0.0411574074074023[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]104.4[/C][C]NA[/C][C]NA[/C][C]0.189212962962956[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]104.79[/C][C]NA[/C][C]NA[/C][C]0.273240740740743[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]104.77[/C][C]NA[/C][C]NA[/C][C]0.229629629629633[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]105.13[/C][C]105.067407407407[/C][C]104.698333333333[/C][C]0.369074074074079[/C][C]0.0625925925925799[/C][/ROW]
[ROW][C]8[/C][C]105.26[/C][C]104.866851851852[/C][C]104.846666666667[/C][C]0.020185185185185[/C][C]0.393148148148157[/C][/ROW]
[ROW][C]9[/C][C]104.96[/C][C]104.825740740741[/C][C]105.002083333333[/C][C]-0.176342592592589[/C][C]0.134259259259252[/C][/ROW]
[ROW][C]10[/C][C]104.75[/C][C]104.921018518519[/C][C]105.158333333333[/C][C]-0.237314814814813[/C][C]-0.171018518518508[/C][/ROW]
[ROW][C]11[/C][C]105.01[/C][C]105.056574074074[/C][C]105.291666666667[/C][C]-0.235092592592602[/C][C]-0.0465740740740586[/C][/ROW]
[ROW][C]12[/C][C]105.15[/C][C]105.036157407407[/C][C]105.40375[/C][C]-0.367592592592586[/C][C]0.11384259259259[/C][/ROW]
[ROW][C]13[/C][C]105.2[/C][C]105.261157407407[/C][C]105.52[/C][C]-0.25884259259259[/C][C]-0.061157407407407[/C][/ROW]
[ROW][C]14[/C][C]105.77[/C][C]105.781851851852[/C][C]105.629166666667[/C][C]0.152685185185183[/C][C]-0.0118518518518584[/C][/ROW]
[ROW][C]15[/C][C]105.78[/C][C]105.785324074074[/C][C]105.744166666667[/C][C]0.0411574074074023[/C][C]-0.00532407407406765[/C][/ROW]
[ROW][C]16[/C][C]106.26[/C][C]106.09712962963[/C][C]105.907916666667[/C][C]0.189212962962956[/C][C]0.162870370370385[/C][/ROW]
[ROW][C]17[/C][C]106.13[/C][C]106.407824074074[/C][C]106.134583333333[/C][C]0.273240740740743[/C][C]-0.277824074074076[/C][/ROW]
[ROW][C]18[/C][C]106.12[/C][C]106.62837962963[/C][C]106.39875[/C][C]0.229629629629633[/C][C]-0.508379629629616[/C][/ROW]
[ROW][C]19[/C][C]106.57[/C][C]107.054907407407[/C][C]106.685833333333[/C][C]0.369074074074079[/C][C]-0.48490740740742[/C][/ROW]
[ROW][C]20[/C][C]106.44[/C][C]107.018101851852[/C][C]106.997916666667[/C][C]0.020185185185185[/C][C]-0.578101851851855[/C][/ROW]
[ROW][C]21[/C][C]106.54[/C][C]107.175324074074[/C][C]107.351666666667[/C][C]-0.176342592592589[/C][C]-0.635324074074063[/C][/ROW]
[ROW][C]22[/C][C]107.1[/C][C]107.491435185185[/C][C]107.72875[/C][C]-0.237314814814813[/C][C]-0.391435185185188[/C][/ROW]
[ROW][C]23[/C][C]108.1[/C][C]107.907824074074[/C][C]108.142916666667[/C][C]-0.235092592592602[/C][C]0.192175925925937[/C][/ROW]
[ROW][C]24[/C][C]108.4[/C][C]108.262407407407[/C][C]108.63[/C][C]-0.367592592592586[/C][C]0.137592592592597[/C][/ROW]
[ROW][C]25[/C][C]108.84[/C][C]108.890324074074[/C][C]109.149166666667[/C][C]-0.25884259259259[/C][C]-0.0503240740740694[/C][/ROW]
[ROW][C]26[/C][C]109.62[/C][C]109.803518518519[/C][C]109.650833333333[/C][C]0.152685185185183[/C][C]-0.183518518518497[/C][/ROW]
[ROW][C]27[/C][C]110.42[/C][C]110.173657407407[/C][C]110.1325[/C][C]0.0411574074074023[/C][C]0.246342592592597[/C][/ROW]
[ROW][C]28[/C][C]110.67[/C][C]110.775046296296[/C][C]110.585833333333[/C][C]0.189212962962956[/C][C]-0.105046296296294[/C][/ROW]
[ROW][C]29[/C][C]111.66[/C][C]111.211157407407[/C][C]110.937916666667[/C][C]0.273240740740743[/C][C]0.448842592592584[/C][/ROW]
[ROW][C]30[/C][C]112.28[/C][C]111.427546296296[/C][C]111.197916666667[/C][C]0.229629629629633[/C][C]0.852453703703702[/C][/ROW]
[ROW][C]31[/C][C]112.87[/C][C]111.790740740741[/C][C]111.421666666667[/C][C]0.369074074074079[/C][C]1.07925925925927[/C][/ROW]
[ROW][C]32[/C][C]112.18[/C][C]111.635185185185[/C][C]111.615[/C][C]0.020185185185185[/C][C]0.544814814814828[/C][/ROW]
[ROW][C]33[/C][C]112.36[/C][C]111.555324074074[/C][C]111.731666666667[/C][C]-0.176342592592589[/C][C]0.804675925925935[/C][/ROW]
[ROW][C]34[/C][C]112.16[/C][C]111.550185185185[/C][C]111.7875[/C][C]-0.237314814814813[/C][C]0.609814814814825[/C][/ROW]
[ROW][C]35[/C][C]111.49[/C][C]111.562824074074[/C][C]111.797916666667[/C][C]-0.235092592592602[/C][C]-0.0728240740740631[/C][/ROW]
[ROW][C]36[/C][C]111.25[/C][C]111.361574074074[/C][C]111.729166666667[/C][C]-0.367592592592586[/C][C]-0.11157407407407[/C][/ROW]
[ROW][C]37[/C][C]111.36[/C][C]111.339490740741[/C][C]111.598333333333[/C][C]-0.25884259259259[/C][C]0.0205092592592564[/C][/ROW]
[ROW][C]38[/C][C]111.74[/C][C]111.635601851852[/C][C]111.482916666667[/C][C]0.152685185185183[/C][C]0.104398148148164[/C][/ROW]
[ROW][C]39[/C][C]111.1[/C][C]111.431990740741[/C][C]111.390833333333[/C][C]0.0411574074074023[/C][C]-0.331990740740721[/C][/ROW]
[ROW][C]40[/C][C]111.33[/C][C]111.478796296296[/C][C]111.289583333333[/C][C]0.189212962962956[/C][C]-0.148796296296297[/C][/ROW]
[ROW][C]41[/C][C]111.25[/C][C]111.511990740741[/C][C]111.23875[/C][C]0.273240740740743[/C][C]-0.261990740740728[/C][/ROW]
[ROW][C]42[/C][C]111.04[/C][C]111.475046296296[/C][C]111.245416666667[/C][C]0.229629629629633[/C][C]-0.435046296296278[/C][/ROW]
[ROW][C]43[/C][C]110.97[/C][C]111.655324074074[/C][C]111.28625[/C][C]0.369074074074079[/C][C]-0.68532407407406[/C][/ROW]
[ROW][C]44[/C][C]111.31[/C][C]111.367685185185[/C][C]111.3475[/C][C]0.020185185185185[/C][C]-0.0576851851851785[/C][/ROW]
[ROW][C]45[/C][C]111.02[/C][C]111.280324074074[/C][C]111.456666666667[/C][C]-0.176342592592589[/C][C]-0.260324074074077[/C][/ROW]
[ROW][C]46[/C][C]111.07[/C][C]111.379351851852[/C][C]111.616666666667[/C][C]-0.237314814814813[/C][C]-0.309351851851858[/C][/ROW]
[ROW][C]47[/C][C]111.36[/C][C]111.570324074074[/C][C]111.805416666667[/C][C]-0.235092592592602[/C][C]-0.210324074074066[/C][/ROW]
[ROW][C]48[/C][C]111.54[/C][C]111.656990740741[/C][C]112.024583333333[/C][C]-0.367592592592586[/C][C]-0.116990740740732[/C][/ROW]
[ROW][C]49[/C][C]112.05[/C][C]NA[/C][C]112.257083333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]112.52[/C][C]NA[/C][C]112.483333333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]112.94[/C][C]NA[/C][C]112.725416666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]113.33[/C][C]NA[/C][C]112.999166666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]113.78[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]113.77[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]113.82[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]113.89[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]114.25[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]114.41[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106291&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106291&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	103.48	NA	NA	-0.25884259259259	NA
2	103.93	NA	NA	0.152685185185183	NA
3	103.89	NA	NA	0.0411574074074023	NA
4	104.4	NA	NA	0.189212962962956	NA
5	104.79	NA	NA	0.273240740740743	NA
6	104.77	NA	NA	0.229629629629633	NA
7	105.13	105.067407407407	104.698333333333	0.369074074074079	0.0625925925925799
8	105.26	104.866851851852	104.846666666667	0.020185185185185	0.393148148148157
9	104.96	104.825740740741	105.002083333333	-0.176342592592589	0.134259259259252
10	104.75	104.921018518519	105.158333333333	-0.237314814814813	-0.171018518518508
11	105.01	105.056574074074	105.291666666667	-0.235092592592602	-0.0465740740740586
12	105.15	105.036157407407	105.40375	-0.367592592592586	0.11384259259259
13	105.2	105.261157407407	105.52	-0.25884259259259	-0.061157407407407
14	105.77	105.781851851852	105.629166666667	0.152685185185183	-0.0118518518518584
15	105.78	105.785324074074	105.744166666667	0.0411574074074023	-0.00532407407406765
16	106.26	106.09712962963	105.907916666667	0.189212962962956	0.162870370370385
17	106.13	106.407824074074	106.134583333333	0.273240740740743	-0.277824074074076
18	106.12	106.62837962963	106.39875	0.229629629629633	-0.508379629629616
19	106.57	107.054907407407	106.685833333333	0.369074074074079	-0.48490740740742
20	106.44	107.018101851852	106.997916666667	0.020185185185185	-0.578101851851855
21	106.54	107.175324074074	107.351666666667	-0.176342592592589	-0.635324074074063
22	107.1	107.491435185185	107.72875	-0.237314814814813	-0.391435185185188
23	108.1	107.907824074074	108.142916666667	-0.235092592592602	0.192175925925937
24	108.4	108.262407407407	108.63	-0.367592592592586	0.137592592592597
25	108.84	108.890324074074	109.149166666667	-0.25884259259259	-0.0503240740740694
26	109.62	109.803518518519	109.650833333333	0.152685185185183	-0.183518518518497
27	110.42	110.173657407407	110.1325	0.0411574074074023	0.246342592592597
28	110.67	110.775046296296	110.585833333333	0.189212962962956	-0.105046296296294
29	111.66	111.211157407407	110.937916666667	0.273240740740743	0.448842592592584
30	112.28	111.427546296296	111.197916666667	0.229629629629633	0.852453703703702
31	112.87	111.790740740741	111.421666666667	0.369074074074079	1.07925925925927
32	112.18	111.635185185185	111.615	0.020185185185185	0.544814814814828
33	112.36	111.555324074074	111.731666666667	-0.176342592592589	0.804675925925935
34	112.16	111.550185185185	111.7875	-0.237314814814813	0.609814814814825
35	111.49	111.562824074074	111.797916666667	-0.235092592592602	-0.0728240740740631
36	111.25	111.361574074074	111.729166666667	-0.367592592592586	-0.11157407407407
37	111.36	111.339490740741	111.598333333333	-0.25884259259259	0.0205092592592564
38	111.74	111.635601851852	111.482916666667	0.152685185185183	0.104398148148164
39	111.1	111.431990740741	111.390833333333	0.0411574074074023	-0.331990740740721
40	111.33	111.478796296296	111.289583333333	0.189212962962956	-0.148796296296297
41	111.25	111.511990740741	111.23875	0.273240740740743	-0.261990740740728
42	111.04	111.475046296296	111.245416666667	0.229629629629633	-0.435046296296278
43	110.97	111.655324074074	111.28625	0.369074074074079	-0.68532407407406
44	111.31	111.367685185185	111.3475	0.020185185185185	-0.0576851851851785
45	111.02	111.280324074074	111.456666666667	-0.176342592592589	-0.260324074074077
46	111.07	111.379351851852	111.616666666667	-0.237314814814813	-0.309351851851858
47	111.36	111.570324074074	111.805416666667	-0.235092592592602	-0.210324074074066
48	111.54	111.656990740741	112.024583333333	-0.367592592592586	-0.116990740740732
49	112.05	NA	112.257083333333	NA	NA
50	112.52	NA	112.483333333333	NA	NA
51	112.94	NA	112.725416666667	NA	NA
52	113.33	NA	112.999166666667	NA	NA
53	113.78	NA	NA	NA	NA
54	113.77	NA	NA	NA	NA
55	113.82	NA	NA	NA	NA
56	113.89	NA	NA	NA	NA
57	114.25	NA	NA	NA	NA
58	114.41	NA	NA	NA	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,m$trend[i]+m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
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