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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 19 Dec 2010 19:18:16 +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/2010/Dec/19/t129278617922iqp3bgzap4vj3.htm/, Retrieved Sat, 04 May 2024 21:52:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112684, Retrieved Sat, 04 May 2024 21:52:38 +0000

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Estimated Impact

148

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] [WS8 - Decompositi...] [2010-11-27 10:08:48] [4a7069087cf9e0eda253aeed7d8c30d6]
-    D    [Classical Decomposition] [Paper - Ontleden ...] [2010-11-28 19:03:27] [4a7069087cf9e0eda253aeed7d8c30d6]
- R  D        [Classical Decomposition] [Classical Decompo...] [2010-12-19 19:18:16] [039869833c16fe697975601e6b065e0f] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112684&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112684&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112684&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1038	NA	NA	1.08544698912203	NA
2	934	NA	NA	0.890185350023919	NA
3	988	NA	NA	1.01552386048150	NA
4	870	NA	NA	0.942735333563146	NA
5	854	NA	NA	0.939529631512505	NA
6	834	NA	NA	0.913095660751156	NA
7	872	924.363389136453	961.25	0.9616264126257	0.943351943887164
8	954	883.748477254904	950.791666666667	0.929486982519729	1.07949266624290
9	870	934.137602241508	948.541666666667	0.984814515870688	0.931340305659886
10	1238	1104.06219917146	954	1.15729790269546	1.12131363697539
11	1082	1052.22146490644	961.458333333333	1.09440152362967	1.02830063450207
12	1053	1049.97735058353	966.958333333333	1.0858558372045	1.00287877582767
13	934	1046.91362100819	964.5	1.08544698912203	0.892146191679638
14	787	853.094293772922	958.333333333333	0.890185350023919	0.922524046573315
15	1081	969.78297326565	954.958333333333	1.01552386048150	1.11468238750350
16	908	895.284321773801	949.666666666667	0.942735333563146	1.01420294974116
17	995	883.001265349836	939.833333333333	0.939529631512505	1.12683870232710
18	825	850.20619711692	931.125	0.913095660751156	0.970352842401767
19	822	897.23751074697	933.041666666667	0.9616264126257	0.916145379739715
20	856	878.636298851045	945.291666666667	0.929486982519729	0.974237009237331
21	887	929.952140549058	944.291666666667	0.984814515870688	0.953812525746004
22	1094	1085.30432899861	937.791666666667	1.15729790269546	1.00801219599798
23	990	1021.89742268921	933.75	1.09440152362967	0.968786081674161
24	936	1016.18008765054	935.833333333333	1.0858558372045	0.921096576655104
25	1097	1034.38575367541	952.958333333333	1.08544698912203	1.06053278102691
26	918	863.4797895232	970	0.890185350023919	1.06314011183389
27	926	998.936970760307	983.666666666667	1.01552386048150	0.926985412598361
28	907	938.335902006518	995.333333333333	0.942735333563146	0.966604813969592
29	899	943.83580899027	1004.58333333333	0.939529631512505	0.95249617723422
30	971	927.172552187736	1015.41666666667	0.913095660751156	1.04727000137013
31	1087	990.515272771663	1030.04166666667	0.9616264126257	1.09740862143231
32	1000	971.62372572729	1045.33333333333	0.929486982519729	1.02920500346106
33	1071	1046.24232129812	1062.375	0.984814515870688	1.02366342691162
34	1190	1256.82552232726	1086	1.15729790269546	0.94682991303079
35	1116	1213.78248983228	1109.08333333333	1.09440152362967	0.91943985792233
36	1070	1228.10295187829	1131	1.0858558372045	0.871262460825061
37	1314	1252.78673327834	1154.16666666667	1.08544698912203	1.04886168179757
38	1068	1051.30889837825	1181	0.890185350023919	1.01587649609691
39	1185	1234.53850639202	1215.66666666667	1.01552386048150	0.959872854402255
40	1215	1190.32120054017	1262.625	0.942735333563146	1.02073289079337
41	1145	1241.58840804378	1321.5	0.939529631512505	0.922205774942794
42	1251	1271.44766194345	1392.45833333333	0.913095660751156	0.983917810732218
43	1363	1379.57329221314	1434.625	0.9616264126257	0.987986653332092
44	1368	1370.60601297388	1474.58333333333	0.929486982519729	0.99809864180573
45	1535	1498.92872709335	1522.04166666667	0.984814515870688	1.02406470184650
46	1853	1770.32824590243	1529.70833333333	1.15729790269546	1.04669854547535
47	1866	1676.07593343884	1531.5	1.09440152362967	1.11331471490763
48	2023	1673.03238117283	1540.75	1.0858558372045	1.20918161702395
49	1373	NA	1553.25	NA	NA
50	1968	NA	1577.45833333333	NA	NA
51	1424	NA	1609.79166666667	NA	NA
52	1160	NA	1634.54166666667	NA	NA
53	1243	NA	1649.58333333333	NA	NA
54	1375	NA	NA	NA	NA
55	1539	NA	NA	NA	NA
56	1773	NA	NA	NA	NA
57	1906	NA	NA	NA	NA
58	2076	NA	NA	NA	NA
59	2004	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1038 & NA & NA & 1.08544698912203 & NA \tabularnewline
2 & 934 & NA & NA & 0.890185350023919 & NA \tabularnewline
3 & 988 & NA & NA & 1.01552386048150 & NA \tabularnewline
4 & 870 & NA & NA & 0.942735333563146 & NA \tabularnewline
5 & 854 & NA & NA & 0.939529631512505 & NA \tabularnewline
6 & 834 & NA & NA & 0.913095660751156 & NA \tabularnewline
7 & 872 & 924.363389136453 & 961.25 & 0.9616264126257 & 0.943351943887164 \tabularnewline
8 & 954 & 883.748477254904 & 950.791666666667 & 0.929486982519729 & 1.07949266624290 \tabularnewline
9 & 870 & 934.137602241508 & 948.541666666667 & 0.984814515870688 & 0.931340305659886 \tabularnewline
10 & 1238 & 1104.06219917146 & 954 & 1.15729790269546 & 1.12131363697539 \tabularnewline
11 & 1082 & 1052.22146490644 & 961.458333333333 & 1.09440152362967 & 1.02830063450207 \tabularnewline
12 & 1053 & 1049.97735058353 & 966.958333333333 & 1.0858558372045 & 1.00287877582767 \tabularnewline
13 & 934 & 1046.91362100819 & 964.5 & 1.08544698912203 & 0.892146191679638 \tabularnewline
14 & 787 & 853.094293772922 & 958.333333333333 & 0.890185350023919 & 0.922524046573315 \tabularnewline
15 & 1081 & 969.78297326565 & 954.958333333333 & 1.01552386048150 & 1.11468238750350 \tabularnewline
16 & 908 & 895.284321773801 & 949.666666666667 & 0.942735333563146 & 1.01420294974116 \tabularnewline
17 & 995 & 883.001265349836 & 939.833333333333 & 0.939529631512505 & 1.12683870232710 \tabularnewline
18 & 825 & 850.20619711692 & 931.125 & 0.913095660751156 & 0.970352842401767 \tabularnewline
19 & 822 & 897.23751074697 & 933.041666666667 & 0.9616264126257 & 0.916145379739715 \tabularnewline
20 & 856 & 878.636298851045 & 945.291666666667 & 0.929486982519729 & 0.974237009237331 \tabularnewline
21 & 887 & 929.952140549058 & 944.291666666667 & 0.984814515870688 & 0.953812525746004 \tabularnewline
22 & 1094 & 1085.30432899861 & 937.791666666667 & 1.15729790269546 & 1.00801219599798 \tabularnewline
23 & 990 & 1021.89742268921 & 933.75 & 1.09440152362967 & 0.968786081674161 \tabularnewline
24 & 936 & 1016.18008765054 & 935.833333333333 & 1.0858558372045 & 0.921096576655104 \tabularnewline
25 & 1097 & 1034.38575367541 & 952.958333333333 & 1.08544698912203 & 1.06053278102691 \tabularnewline
26 & 918 & 863.4797895232 & 970 & 0.890185350023919 & 1.06314011183389 \tabularnewline
27 & 926 & 998.936970760307 & 983.666666666667 & 1.01552386048150 & 0.926985412598361 \tabularnewline
28 & 907 & 938.335902006518 & 995.333333333333 & 0.942735333563146 & 0.966604813969592 \tabularnewline
29 & 899 & 943.83580899027 & 1004.58333333333 & 0.939529631512505 & 0.95249617723422 \tabularnewline
30 & 971 & 927.172552187736 & 1015.41666666667 & 0.913095660751156 & 1.04727000137013 \tabularnewline
31 & 1087 & 990.515272771663 & 1030.04166666667 & 0.9616264126257 & 1.09740862143231 \tabularnewline
32 & 1000 & 971.62372572729 & 1045.33333333333 & 0.929486982519729 & 1.02920500346106 \tabularnewline
33 & 1071 & 1046.24232129812 & 1062.375 & 0.984814515870688 & 1.02366342691162 \tabularnewline
34 & 1190 & 1256.82552232726 & 1086 & 1.15729790269546 & 0.94682991303079 \tabularnewline
35 & 1116 & 1213.78248983228 & 1109.08333333333 & 1.09440152362967 & 0.91943985792233 \tabularnewline
36 & 1070 & 1228.10295187829 & 1131 & 1.0858558372045 & 0.871262460825061 \tabularnewline
37 & 1314 & 1252.78673327834 & 1154.16666666667 & 1.08544698912203 & 1.04886168179757 \tabularnewline
38 & 1068 & 1051.30889837825 & 1181 & 0.890185350023919 & 1.01587649609691 \tabularnewline
39 & 1185 & 1234.53850639202 & 1215.66666666667 & 1.01552386048150 & 0.959872854402255 \tabularnewline
40 & 1215 & 1190.32120054017 & 1262.625 & 0.942735333563146 & 1.02073289079337 \tabularnewline
41 & 1145 & 1241.58840804378 & 1321.5 & 0.939529631512505 & 0.922205774942794 \tabularnewline
42 & 1251 & 1271.44766194345 & 1392.45833333333 & 0.913095660751156 & 0.983917810732218 \tabularnewline
43 & 1363 & 1379.57329221314 & 1434.625 & 0.9616264126257 & 0.987986653332092 \tabularnewline
44 & 1368 & 1370.60601297388 & 1474.58333333333 & 0.929486982519729 & 0.99809864180573 \tabularnewline
45 & 1535 & 1498.92872709335 & 1522.04166666667 & 0.984814515870688 & 1.02406470184650 \tabularnewline
46 & 1853 & 1770.32824590243 & 1529.70833333333 & 1.15729790269546 & 1.04669854547535 \tabularnewline
47 & 1866 & 1676.07593343884 & 1531.5 & 1.09440152362967 & 1.11331471490763 \tabularnewline
48 & 2023 & 1673.03238117283 & 1540.75 & 1.0858558372045 & 1.20918161702395 \tabularnewline
49 & 1373 & NA & 1553.25 & NA & NA \tabularnewline
50 & 1968 & NA & 1577.45833333333 & NA & NA \tabularnewline
51 & 1424 & NA & 1609.79166666667 & NA & NA \tabularnewline
52 & 1160 & NA & 1634.54166666667 & NA & NA \tabularnewline
53 & 1243 & NA & 1649.58333333333 & NA & NA \tabularnewline
54 & 1375 & NA & NA & NA & NA \tabularnewline
55 & 1539 & NA & NA & NA & NA \tabularnewline
56 & 1773 & NA & NA & NA & NA \tabularnewline
57 & 1906 & NA & NA & NA & NA \tabularnewline
58 & 2076 & NA & NA & NA & NA \tabularnewline
59 & 2004 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112684&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]1038[/C][C]NA[/C][C]NA[/C][C]1.08544698912203[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]934[/C][C]NA[/C][C]NA[/C][C]0.890185350023919[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]988[/C][C]NA[/C][C]NA[/C][C]1.01552386048150[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]870[/C][C]NA[/C][C]NA[/C][C]0.942735333563146[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]854[/C][C]NA[/C][C]NA[/C][C]0.939529631512505[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]834[/C][C]NA[/C][C]NA[/C][C]0.913095660751156[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]872[/C][C]924.363389136453[/C][C]961.25[/C][C]0.9616264126257[/C][C]0.943351943887164[/C][/ROW]
[ROW][C]8[/C][C]954[/C][C]883.748477254904[/C][C]950.791666666667[/C][C]0.929486982519729[/C][C]1.07949266624290[/C][/ROW]
[ROW][C]9[/C][C]870[/C][C]934.137602241508[/C][C]948.541666666667[/C][C]0.984814515870688[/C][C]0.931340305659886[/C][/ROW]
[ROW][C]10[/C][C]1238[/C][C]1104.06219917146[/C][C]954[/C][C]1.15729790269546[/C][C]1.12131363697539[/C][/ROW]
[ROW][C]11[/C][C]1082[/C][C]1052.22146490644[/C][C]961.458333333333[/C][C]1.09440152362967[/C][C]1.02830063450207[/C][/ROW]
[ROW][C]12[/C][C]1053[/C][C]1049.97735058353[/C][C]966.958333333333[/C][C]1.0858558372045[/C][C]1.00287877582767[/C][/ROW]
[ROW][C]13[/C][C]934[/C][C]1046.91362100819[/C][C]964.5[/C][C]1.08544698912203[/C][C]0.892146191679638[/C][/ROW]
[ROW][C]14[/C][C]787[/C][C]853.094293772922[/C][C]958.333333333333[/C][C]0.890185350023919[/C][C]0.922524046573315[/C][/ROW]
[ROW][C]15[/C][C]1081[/C][C]969.78297326565[/C][C]954.958333333333[/C][C]1.01552386048150[/C][C]1.11468238750350[/C][/ROW]
[ROW][C]16[/C][C]908[/C][C]895.284321773801[/C][C]949.666666666667[/C][C]0.942735333563146[/C][C]1.01420294974116[/C][/ROW]
[ROW][C]17[/C][C]995[/C][C]883.001265349836[/C][C]939.833333333333[/C][C]0.939529631512505[/C][C]1.12683870232710[/C][/ROW]
[ROW][C]18[/C][C]825[/C][C]850.20619711692[/C][C]931.125[/C][C]0.913095660751156[/C][C]0.970352842401767[/C][/ROW]
[ROW][C]19[/C][C]822[/C][C]897.23751074697[/C][C]933.041666666667[/C][C]0.9616264126257[/C][C]0.916145379739715[/C][/ROW]
[ROW][C]20[/C][C]856[/C][C]878.636298851045[/C][C]945.291666666667[/C][C]0.929486982519729[/C][C]0.974237009237331[/C][/ROW]
[ROW][C]21[/C][C]887[/C][C]929.952140549058[/C][C]944.291666666667[/C][C]0.984814515870688[/C][C]0.953812525746004[/C][/ROW]
[ROW][C]22[/C][C]1094[/C][C]1085.30432899861[/C][C]937.791666666667[/C][C]1.15729790269546[/C][C]1.00801219599798[/C][/ROW]
[ROW][C]23[/C][C]990[/C][C]1021.89742268921[/C][C]933.75[/C][C]1.09440152362967[/C][C]0.968786081674161[/C][/ROW]
[ROW][C]24[/C][C]936[/C][C]1016.18008765054[/C][C]935.833333333333[/C][C]1.0858558372045[/C][C]0.921096576655104[/C][/ROW]
[ROW][C]25[/C][C]1097[/C][C]1034.38575367541[/C][C]952.958333333333[/C][C]1.08544698912203[/C][C]1.06053278102691[/C][/ROW]
[ROW][C]26[/C][C]918[/C][C]863.4797895232[/C][C]970[/C][C]0.890185350023919[/C][C]1.06314011183389[/C][/ROW]
[ROW][C]27[/C][C]926[/C][C]998.936970760307[/C][C]983.666666666667[/C][C]1.01552386048150[/C][C]0.926985412598361[/C][/ROW]
[ROW][C]28[/C][C]907[/C][C]938.335902006518[/C][C]995.333333333333[/C][C]0.942735333563146[/C][C]0.966604813969592[/C][/ROW]
[ROW][C]29[/C][C]899[/C][C]943.83580899027[/C][C]1004.58333333333[/C][C]0.939529631512505[/C][C]0.95249617723422[/C][/ROW]
[ROW][C]30[/C][C]971[/C][C]927.172552187736[/C][C]1015.41666666667[/C][C]0.913095660751156[/C][C]1.04727000137013[/C][/ROW]
[ROW][C]31[/C][C]1087[/C][C]990.515272771663[/C][C]1030.04166666667[/C][C]0.9616264126257[/C][C]1.09740862143231[/C][/ROW]
[ROW][C]32[/C][C]1000[/C][C]971.62372572729[/C][C]1045.33333333333[/C][C]0.929486982519729[/C][C]1.02920500346106[/C][/ROW]
[ROW][C]33[/C][C]1071[/C][C]1046.24232129812[/C][C]1062.375[/C][C]0.984814515870688[/C][C]1.02366342691162[/C][/ROW]
[ROW][C]34[/C][C]1190[/C][C]1256.82552232726[/C][C]1086[/C][C]1.15729790269546[/C][C]0.94682991303079[/C][/ROW]
[ROW][C]35[/C][C]1116[/C][C]1213.78248983228[/C][C]1109.08333333333[/C][C]1.09440152362967[/C][C]0.91943985792233[/C][/ROW]
[ROW][C]36[/C][C]1070[/C][C]1228.10295187829[/C][C]1131[/C][C]1.0858558372045[/C][C]0.871262460825061[/C][/ROW]
[ROW][C]37[/C][C]1314[/C][C]1252.78673327834[/C][C]1154.16666666667[/C][C]1.08544698912203[/C][C]1.04886168179757[/C][/ROW]
[ROW][C]38[/C][C]1068[/C][C]1051.30889837825[/C][C]1181[/C][C]0.890185350023919[/C][C]1.01587649609691[/C][/ROW]
[ROW][C]39[/C][C]1185[/C][C]1234.53850639202[/C][C]1215.66666666667[/C][C]1.01552386048150[/C][C]0.959872854402255[/C][/ROW]
[ROW][C]40[/C][C]1215[/C][C]1190.32120054017[/C][C]1262.625[/C][C]0.942735333563146[/C][C]1.02073289079337[/C][/ROW]
[ROW][C]41[/C][C]1145[/C][C]1241.58840804378[/C][C]1321.5[/C][C]0.939529631512505[/C][C]0.922205774942794[/C][/ROW]
[ROW][C]42[/C][C]1251[/C][C]1271.44766194345[/C][C]1392.45833333333[/C][C]0.913095660751156[/C][C]0.983917810732218[/C][/ROW]
[ROW][C]43[/C][C]1363[/C][C]1379.57329221314[/C][C]1434.625[/C][C]0.9616264126257[/C][C]0.987986653332092[/C][/ROW]
[ROW][C]44[/C][C]1368[/C][C]1370.60601297388[/C][C]1474.58333333333[/C][C]0.929486982519729[/C][C]0.99809864180573[/C][/ROW]
[ROW][C]45[/C][C]1535[/C][C]1498.92872709335[/C][C]1522.04166666667[/C][C]0.984814515870688[/C][C]1.02406470184650[/C][/ROW]
[ROW][C]46[/C][C]1853[/C][C]1770.32824590243[/C][C]1529.70833333333[/C][C]1.15729790269546[/C][C]1.04669854547535[/C][/ROW]
[ROW][C]47[/C][C]1866[/C][C]1676.07593343884[/C][C]1531.5[/C][C]1.09440152362967[/C][C]1.11331471490763[/C][/ROW]
[ROW][C]48[/C][C]2023[/C][C]1673.03238117283[/C][C]1540.75[/C][C]1.0858558372045[/C][C]1.20918161702395[/C][/ROW]
[ROW][C]49[/C][C]1373[/C][C]NA[/C][C]1553.25[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]1968[/C][C]NA[/C][C]1577.45833333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]1424[/C][C]NA[/C][C]1609.79166666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]1160[/C][C]NA[/C][C]1634.54166666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]1243[/C][C]NA[/C][C]1649.58333333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]1375[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]1539[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]1773[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]1906[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]2076[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]2004[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112684&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112684&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	1038	NA	NA	1.08544698912203	NA
2	934	NA	NA	0.890185350023919	NA
3	988	NA	NA	1.01552386048150	NA
4	870	NA	NA	0.942735333563146	NA
5	854	NA	NA	0.939529631512505	NA
6	834	NA	NA	0.913095660751156	NA
7	872	924.363389136453	961.25	0.9616264126257	0.943351943887164
8	954	883.748477254904	950.791666666667	0.929486982519729	1.07949266624290
9	870	934.137602241508	948.541666666667	0.984814515870688	0.931340305659886
10	1238	1104.06219917146	954	1.15729790269546	1.12131363697539
11	1082	1052.22146490644	961.458333333333	1.09440152362967	1.02830063450207
12	1053	1049.97735058353	966.958333333333	1.0858558372045	1.00287877582767
13	934	1046.91362100819	964.5	1.08544698912203	0.892146191679638
14	787	853.094293772922	958.333333333333	0.890185350023919	0.922524046573315
15	1081	969.78297326565	954.958333333333	1.01552386048150	1.11468238750350
16	908	895.284321773801	949.666666666667	0.942735333563146	1.01420294974116
17	995	883.001265349836	939.833333333333	0.939529631512505	1.12683870232710
18	825	850.20619711692	931.125	0.913095660751156	0.970352842401767
19	822	897.23751074697	933.041666666667	0.9616264126257	0.916145379739715
20	856	878.636298851045	945.291666666667	0.929486982519729	0.974237009237331
21	887	929.952140549058	944.291666666667	0.984814515870688	0.953812525746004
22	1094	1085.30432899861	937.791666666667	1.15729790269546	1.00801219599798
23	990	1021.89742268921	933.75	1.09440152362967	0.968786081674161
24	936	1016.18008765054	935.833333333333	1.0858558372045	0.921096576655104
25	1097	1034.38575367541	952.958333333333	1.08544698912203	1.06053278102691
26	918	863.4797895232	970	0.890185350023919	1.06314011183389
27	926	998.936970760307	983.666666666667	1.01552386048150	0.926985412598361
28	907	938.335902006518	995.333333333333	0.942735333563146	0.966604813969592
29	899	943.83580899027	1004.58333333333	0.939529631512505	0.95249617723422
30	971	927.172552187736	1015.41666666667	0.913095660751156	1.04727000137013
31	1087	990.515272771663	1030.04166666667	0.9616264126257	1.09740862143231
32	1000	971.62372572729	1045.33333333333	0.929486982519729	1.02920500346106
33	1071	1046.24232129812	1062.375	0.984814515870688	1.02366342691162
34	1190	1256.82552232726	1086	1.15729790269546	0.94682991303079
35	1116	1213.78248983228	1109.08333333333	1.09440152362967	0.91943985792233
36	1070	1228.10295187829	1131	1.0858558372045	0.871262460825061
37	1314	1252.78673327834	1154.16666666667	1.08544698912203	1.04886168179757
38	1068	1051.30889837825	1181	0.890185350023919	1.01587649609691
39	1185	1234.53850639202	1215.66666666667	1.01552386048150	0.959872854402255
40	1215	1190.32120054017	1262.625	0.942735333563146	1.02073289079337
41	1145	1241.58840804378	1321.5	0.939529631512505	0.922205774942794
42	1251	1271.44766194345	1392.45833333333	0.913095660751156	0.983917810732218
43	1363	1379.57329221314	1434.625	0.9616264126257	0.987986653332092
44	1368	1370.60601297388	1474.58333333333	0.929486982519729	0.99809864180573
45	1535	1498.92872709335	1522.04166666667	0.984814515870688	1.02406470184650
46	1853	1770.32824590243	1529.70833333333	1.15729790269546	1.04669854547535
47	1866	1676.07593343884	1531.5	1.09440152362967	1.11331471490763
48	2023	1673.03238117283	1540.75	1.0858558372045	1.20918161702395
49	1373	NA	1553.25	NA	NA
50	1968	NA	1577.45833333333	NA	NA
51	1424	NA	1609.79166666667	NA	NA
52	1160	NA	1634.54166666667	NA	NA
53	1243	NA	1649.58333333333	NA	NA
54	1375	NA	NA	NA	NA
55	1539	NA	NA	NA	NA
56	1773	NA	NA	NA	NA
57	1906	NA	NA	NA	NA
58	2076	NA	NA	NA	NA
59	2004	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 = 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$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