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rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 11 Dec 2009 06:04:40 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/11/t12605367083qzh1uuyl72ias1.htm/, Retrieved Sun, 28 Apr 2024 19:36:56 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66161, Retrieved Sun, 28 Apr 2024 19:36:56 +0000

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Estimated Impact

113

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [] [2009-11-27 14:58:37] [b98453cac15ba1066b407e146608df68]
- R PD    [Classical Decomposition] [] [2009-12-03 20:05:50] [325e037ef8beb77178124dff9c2e015a]
-   PD        [Classical Decomposition] [] [2009-12-11 13:04:40] [2f6049721194fa571920c3539d7b729e] [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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66161&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66161&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66161&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' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	15859.4	NA	NA	1.11033803352377	NA
2	15258.9	NA	NA	1.00030595448686	NA
3	15498.6	NA	NA	0.99531399743087	NA
4	15106.5	NA	NA	1.06043625305120	NA
5	15023.6	NA	NA	0.956804451872642	NA
6	12083	NA	NA	0.830761475963053	NA
7	15761.3	15900.9893411254	14985.5958333333	1.06108489231745	0.99121505347066
8	16942.6	15717.5466506426	14996.0291666667	1.04811390241756	1.07794176639567
9	15070.3	15681.564751243	14978.1125	1.04696534701839	0.96102016852658
10	13659.6	14728.8550086994	14970.675	0.98384708830426	0.927404064466122
11	14768.9	14004.0085687924	14989.0666666667	0.934281558700059	1.05461946323798
12	14725.1	14553.3898628828	14976.5208333333	0.971747044913876	1.01179863514515
13	15998.1	16635.6164552275	14982.4791666667	1.11033803352377	0.96167761760177
14	15370.6	14999.8253601946	14995.2375	1.00030595448686	1.02471859711042
15	14956.9	14911.8026037926	14982.0083333333	0.99531399743087	1.00302427529425
16	15469.7	15936.0681084467	15027.8416666667	1.06043625305120	0.970735058028551
17	15101.8	14419.2025571294	15070.1666666667	0.956804451872642	1.04733947249622
18	11703.7	12533.3903138072	15086.6291666667	0.830761475963053	0.933801605708135
19	16283.6	16118.127100777	15190.2333333333	1.06108489231745	1.01026626097365
20	16726.5	16048.3794367995	15311.675	1.04811390241756	1.04225476883015
21	14968.9	16095.0157291362	15373.0166666667	1.04696534701839	0.930033263210946
22	14861	15242.1116372162	15492.3583333333	0.98384708830426	0.9749961392301
23	14583.3	14599.2549211996	15626.1833333333	0.934281558700059	0.998907141406485
24	15305.8	15305.105034206	15750.0916666667	0.971747044913876	1.00004540745016
25	17903.9	17659.2139562907	15904.3583333333	1.11033803352377	1.01385599859172
26	16379.4	16021.1377397257	16016.2375	1.00030595448686	1.02236184883337
27	15420.3	16090.4244095586	16166.1791666667	0.99531399743087	0.958352595773636
28	17870.5	17333.0470618569	16345.2041666667	1.06043625305120	1.03100741238543
29	15912.8	15768.7871965514	16480.6791666667	0.956804451872642	1.00913277613894
30	13866.5	13784.4790200400	16592.5833333333	0.830761475963053	1.00595024156087
31	17823.2	17716.5542249381	16696.6416666667	1.06108489231745	1.00601955514079
32	17872	17616.9736017338	16808.2625	1.04811390241756	1.01447617530863
33	17422	17739.3751408076	16943.6125	1.04696534701839	0.982109001118222
34	16704.5	16772.6169626853	17047.9916666667	0.98384708830426	0.99593879936346
35	15991.2	15968.9389361326	17092.2125	0.934281558700059	1.00139402273103
36	16583.6	16674.9161092308	17159.7291666667	0.971747044913876	0.994523744009708
37	19123.5	19175.8848195910	17270.3125	1.11033803352377	0.997268192832622
38	17838.7	17327.8374080719	17322.5375	1.00030595448686	1.02948218983692
39	17209.4	17305.3378519560	17386.8125	0.99531399743087	0.994456169953066
40	18586.5	18570.3331525263	17511.975	1.06043625305120	1.00087057390629
41	16258.1	16869.5588249491	17631.1458333333	0.956804451872642	0.963753715713964
42	15141.6	14740.4777885044	17743.3333333333	0.830761475963053	1.02721229374318
43	19202.1	18964.9957609295	17873.2125	1.06108489231745	1.01250220364188
44	17746.5	18789.0706445249	17926.5541666667	1.04811390241756	0.944511856693206
45	19090.1	18836.5948244829	17991.6125	1.04696534701839	1.01345812116676
46	18040.3	17841.9726610518	18134.9041666667	0.98384708830426	1.01111577417564
47	17515.5	17041.4279872432	18240.1416666667	0.934281558700059	1.02781879623654
48	17751.8	17819.5733939490	18337.6666666667	0.971747044913876	0.996196688189402
49	21072.4	20420.5182382694	18391.2625	1.11033803352377	1.0319228804149
50	17170	18498.92476458	18493.2666666667	1.00030595448686	0.928162053660302
51	19439.5	18533.3728505528	18620.6291666667	0.99531399743087	1.04889164842006
52	19795.4	19753.6872227593	18627.8875	1.06043625305120	1.00211164512074
53	17574.9	17851.6229143512	18657.5458333333	0.956804451872642	0.984498725091895
54	16165.4	15577.1965165514	18750.5041666667	0.830761475963053	1.03776054842883
55	19464.6	19944.5318580853	18796.3583333333	1.06108489231745	0.975936669684693
56	19932.1	NA	NA	1.04811390241756	NA
57	19961.2	NA	NA	1.04696534701839	NA
58	17343.4	NA	NA	0.98384708830426	NA
59	18924.2	NA	NA	0.934281558700059	NA
60	18574.1	NA	NA	0.971747044913876	NA
61	21350.6	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 15859.4 & NA & NA & 1.11033803352377 & NA \tabularnewline
2 & 15258.9 & NA & NA & 1.00030595448686 & NA \tabularnewline
3 & 15498.6 & NA & NA & 0.99531399743087 & NA \tabularnewline
4 & 15106.5 & NA & NA & 1.06043625305120 & NA \tabularnewline
5 & 15023.6 & NA & NA & 0.956804451872642 & NA \tabularnewline
6 & 12083 & NA & NA & 0.830761475963053 & NA \tabularnewline
7 & 15761.3 & 15900.9893411254 & 14985.5958333333 & 1.06108489231745 & 0.99121505347066 \tabularnewline
8 & 16942.6 & 15717.5466506426 & 14996.0291666667 & 1.04811390241756 & 1.07794176639567 \tabularnewline
9 & 15070.3 & 15681.564751243 & 14978.1125 & 1.04696534701839 & 0.96102016852658 \tabularnewline
10 & 13659.6 & 14728.8550086994 & 14970.675 & 0.98384708830426 & 0.927404064466122 \tabularnewline
11 & 14768.9 & 14004.0085687924 & 14989.0666666667 & 0.934281558700059 & 1.05461946323798 \tabularnewline
12 & 14725.1 & 14553.3898628828 & 14976.5208333333 & 0.971747044913876 & 1.01179863514515 \tabularnewline
13 & 15998.1 & 16635.6164552275 & 14982.4791666667 & 1.11033803352377 & 0.96167761760177 \tabularnewline
14 & 15370.6 & 14999.8253601946 & 14995.2375 & 1.00030595448686 & 1.02471859711042 \tabularnewline
15 & 14956.9 & 14911.8026037926 & 14982.0083333333 & 0.99531399743087 & 1.00302427529425 \tabularnewline
16 & 15469.7 & 15936.0681084467 & 15027.8416666667 & 1.06043625305120 & 0.970735058028551 \tabularnewline
17 & 15101.8 & 14419.2025571294 & 15070.1666666667 & 0.956804451872642 & 1.04733947249622 \tabularnewline
18 & 11703.7 & 12533.3903138072 & 15086.6291666667 & 0.830761475963053 & 0.933801605708135 \tabularnewline
19 & 16283.6 & 16118.127100777 & 15190.2333333333 & 1.06108489231745 & 1.01026626097365 \tabularnewline
20 & 16726.5 & 16048.3794367995 & 15311.675 & 1.04811390241756 & 1.04225476883015 \tabularnewline
21 & 14968.9 & 16095.0157291362 & 15373.0166666667 & 1.04696534701839 & 0.930033263210946 \tabularnewline
22 & 14861 & 15242.1116372162 & 15492.3583333333 & 0.98384708830426 & 0.9749961392301 \tabularnewline
23 & 14583.3 & 14599.2549211996 & 15626.1833333333 & 0.934281558700059 & 0.998907141406485 \tabularnewline
24 & 15305.8 & 15305.105034206 & 15750.0916666667 & 0.971747044913876 & 1.00004540745016 \tabularnewline
25 & 17903.9 & 17659.2139562907 & 15904.3583333333 & 1.11033803352377 & 1.01385599859172 \tabularnewline
26 & 16379.4 & 16021.1377397257 & 16016.2375 & 1.00030595448686 & 1.02236184883337 \tabularnewline
27 & 15420.3 & 16090.4244095586 & 16166.1791666667 & 0.99531399743087 & 0.958352595773636 \tabularnewline
28 & 17870.5 & 17333.0470618569 & 16345.2041666667 & 1.06043625305120 & 1.03100741238543 \tabularnewline
29 & 15912.8 & 15768.7871965514 & 16480.6791666667 & 0.956804451872642 & 1.00913277613894 \tabularnewline
30 & 13866.5 & 13784.4790200400 & 16592.5833333333 & 0.830761475963053 & 1.00595024156087 \tabularnewline
31 & 17823.2 & 17716.5542249381 & 16696.6416666667 & 1.06108489231745 & 1.00601955514079 \tabularnewline
32 & 17872 & 17616.9736017338 & 16808.2625 & 1.04811390241756 & 1.01447617530863 \tabularnewline
33 & 17422 & 17739.3751408076 & 16943.6125 & 1.04696534701839 & 0.982109001118222 \tabularnewline
34 & 16704.5 & 16772.6169626853 & 17047.9916666667 & 0.98384708830426 & 0.99593879936346 \tabularnewline
35 & 15991.2 & 15968.9389361326 & 17092.2125 & 0.934281558700059 & 1.00139402273103 \tabularnewline
36 & 16583.6 & 16674.9161092308 & 17159.7291666667 & 0.971747044913876 & 0.994523744009708 \tabularnewline
37 & 19123.5 & 19175.8848195910 & 17270.3125 & 1.11033803352377 & 0.997268192832622 \tabularnewline
38 & 17838.7 & 17327.8374080719 & 17322.5375 & 1.00030595448686 & 1.02948218983692 \tabularnewline
39 & 17209.4 & 17305.3378519560 & 17386.8125 & 0.99531399743087 & 0.994456169953066 \tabularnewline
40 & 18586.5 & 18570.3331525263 & 17511.975 & 1.06043625305120 & 1.00087057390629 \tabularnewline
41 & 16258.1 & 16869.5588249491 & 17631.1458333333 & 0.956804451872642 & 0.963753715713964 \tabularnewline
42 & 15141.6 & 14740.4777885044 & 17743.3333333333 & 0.830761475963053 & 1.02721229374318 \tabularnewline
43 & 19202.1 & 18964.9957609295 & 17873.2125 & 1.06108489231745 & 1.01250220364188 \tabularnewline
44 & 17746.5 & 18789.0706445249 & 17926.5541666667 & 1.04811390241756 & 0.944511856693206 \tabularnewline
45 & 19090.1 & 18836.5948244829 & 17991.6125 & 1.04696534701839 & 1.01345812116676 \tabularnewline
46 & 18040.3 & 17841.9726610518 & 18134.9041666667 & 0.98384708830426 & 1.01111577417564 \tabularnewline
47 & 17515.5 & 17041.4279872432 & 18240.1416666667 & 0.934281558700059 & 1.02781879623654 \tabularnewline
48 & 17751.8 & 17819.5733939490 & 18337.6666666667 & 0.971747044913876 & 0.996196688189402 \tabularnewline
49 & 21072.4 & 20420.5182382694 & 18391.2625 & 1.11033803352377 & 1.0319228804149 \tabularnewline
50 & 17170 & 18498.92476458 & 18493.2666666667 & 1.00030595448686 & 0.928162053660302 \tabularnewline
51 & 19439.5 & 18533.3728505528 & 18620.6291666667 & 0.99531399743087 & 1.04889164842006 \tabularnewline
52 & 19795.4 & 19753.6872227593 & 18627.8875 & 1.06043625305120 & 1.00211164512074 \tabularnewline
53 & 17574.9 & 17851.6229143512 & 18657.5458333333 & 0.956804451872642 & 0.984498725091895 \tabularnewline
54 & 16165.4 & 15577.1965165514 & 18750.5041666667 & 0.830761475963053 & 1.03776054842883 \tabularnewline
55 & 19464.6 & 19944.5318580853 & 18796.3583333333 & 1.06108489231745 & 0.975936669684693 \tabularnewline
56 & 19932.1 & NA & NA & 1.04811390241756 & NA \tabularnewline
57 & 19961.2 & NA & NA & 1.04696534701839 & NA \tabularnewline
58 & 17343.4 & NA & NA & 0.98384708830426 & NA \tabularnewline
59 & 18924.2 & NA & NA & 0.934281558700059 & NA \tabularnewline
60 & 18574.1 & NA & NA & 0.971747044913876 & NA \tabularnewline
61 & 21350.6 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66161&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]15859.4[/C][C]NA[/C][C]NA[/C][C]1.11033803352377[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]15258.9[/C][C]NA[/C][C]NA[/C][C]1.00030595448686[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]15498.6[/C][C]NA[/C][C]NA[/C][C]0.99531399743087[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]15106.5[/C][C]NA[/C][C]NA[/C][C]1.06043625305120[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]15023.6[/C][C]NA[/C][C]NA[/C][C]0.956804451872642[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]12083[/C][C]NA[/C][C]NA[/C][C]0.830761475963053[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]15761.3[/C][C]15900.9893411254[/C][C]14985.5958333333[/C][C]1.06108489231745[/C][C]0.99121505347066[/C][/ROW]
[ROW][C]8[/C][C]16942.6[/C][C]15717.5466506426[/C][C]14996.0291666667[/C][C]1.04811390241756[/C][C]1.07794176639567[/C][/ROW]
[ROW][C]9[/C][C]15070.3[/C][C]15681.564751243[/C][C]14978.1125[/C][C]1.04696534701839[/C][C]0.96102016852658[/C][/ROW]
[ROW][C]10[/C][C]13659.6[/C][C]14728.8550086994[/C][C]14970.675[/C][C]0.98384708830426[/C][C]0.927404064466122[/C][/ROW]
[ROW][C]11[/C][C]14768.9[/C][C]14004.0085687924[/C][C]14989.0666666667[/C][C]0.934281558700059[/C][C]1.05461946323798[/C][/ROW]
[ROW][C]12[/C][C]14725.1[/C][C]14553.3898628828[/C][C]14976.5208333333[/C][C]0.971747044913876[/C][C]1.01179863514515[/C][/ROW]
[ROW][C]13[/C][C]15998.1[/C][C]16635.6164552275[/C][C]14982.4791666667[/C][C]1.11033803352377[/C][C]0.96167761760177[/C][/ROW]
[ROW][C]14[/C][C]15370.6[/C][C]14999.8253601946[/C][C]14995.2375[/C][C]1.00030595448686[/C][C]1.02471859711042[/C][/ROW]
[ROW][C]15[/C][C]14956.9[/C][C]14911.8026037926[/C][C]14982.0083333333[/C][C]0.99531399743087[/C][C]1.00302427529425[/C][/ROW]
[ROW][C]16[/C][C]15469.7[/C][C]15936.0681084467[/C][C]15027.8416666667[/C][C]1.06043625305120[/C][C]0.970735058028551[/C][/ROW]
[ROW][C]17[/C][C]15101.8[/C][C]14419.2025571294[/C][C]15070.1666666667[/C][C]0.956804451872642[/C][C]1.04733947249622[/C][/ROW]
[ROW][C]18[/C][C]11703.7[/C][C]12533.3903138072[/C][C]15086.6291666667[/C][C]0.830761475963053[/C][C]0.933801605708135[/C][/ROW]
[ROW][C]19[/C][C]16283.6[/C][C]16118.127100777[/C][C]15190.2333333333[/C][C]1.06108489231745[/C][C]1.01026626097365[/C][/ROW]
[ROW][C]20[/C][C]16726.5[/C][C]16048.3794367995[/C][C]15311.675[/C][C]1.04811390241756[/C][C]1.04225476883015[/C][/ROW]
[ROW][C]21[/C][C]14968.9[/C][C]16095.0157291362[/C][C]15373.0166666667[/C][C]1.04696534701839[/C][C]0.930033263210946[/C][/ROW]
[ROW][C]22[/C][C]14861[/C][C]15242.1116372162[/C][C]15492.3583333333[/C][C]0.98384708830426[/C][C]0.9749961392301[/C][/ROW]
[ROW][C]23[/C][C]14583.3[/C][C]14599.2549211996[/C][C]15626.1833333333[/C][C]0.934281558700059[/C][C]0.998907141406485[/C][/ROW]
[ROW][C]24[/C][C]15305.8[/C][C]15305.105034206[/C][C]15750.0916666667[/C][C]0.971747044913876[/C][C]1.00004540745016[/C][/ROW]
[ROW][C]25[/C][C]17903.9[/C][C]17659.2139562907[/C][C]15904.3583333333[/C][C]1.11033803352377[/C][C]1.01385599859172[/C][/ROW]
[ROW][C]26[/C][C]16379.4[/C][C]16021.1377397257[/C][C]16016.2375[/C][C]1.00030595448686[/C][C]1.02236184883337[/C][/ROW]
[ROW][C]27[/C][C]15420.3[/C][C]16090.4244095586[/C][C]16166.1791666667[/C][C]0.99531399743087[/C][C]0.958352595773636[/C][/ROW]
[ROW][C]28[/C][C]17870.5[/C][C]17333.0470618569[/C][C]16345.2041666667[/C][C]1.06043625305120[/C][C]1.03100741238543[/C][/ROW]
[ROW][C]29[/C][C]15912.8[/C][C]15768.7871965514[/C][C]16480.6791666667[/C][C]0.956804451872642[/C][C]1.00913277613894[/C][/ROW]
[ROW][C]30[/C][C]13866.5[/C][C]13784.4790200400[/C][C]16592.5833333333[/C][C]0.830761475963053[/C][C]1.00595024156087[/C][/ROW]
[ROW][C]31[/C][C]17823.2[/C][C]17716.5542249381[/C][C]16696.6416666667[/C][C]1.06108489231745[/C][C]1.00601955514079[/C][/ROW]
[ROW][C]32[/C][C]17872[/C][C]17616.9736017338[/C][C]16808.2625[/C][C]1.04811390241756[/C][C]1.01447617530863[/C][/ROW]
[ROW][C]33[/C][C]17422[/C][C]17739.3751408076[/C][C]16943.6125[/C][C]1.04696534701839[/C][C]0.982109001118222[/C][/ROW]
[ROW][C]34[/C][C]16704.5[/C][C]16772.6169626853[/C][C]17047.9916666667[/C][C]0.98384708830426[/C][C]0.99593879936346[/C][/ROW]
[ROW][C]35[/C][C]15991.2[/C][C]15968.9389361326[/C][C]17092.2125[/C][C]0.934281558700059[/C][C]1.00139402273103[/C][/ROW]
[ROW][C]36[/C][C]16583.6[/C][C]16674.9161092308[/C][C]17159.7291666667[/C][C]0.971747044913876[/C][C]0.994523744009708[/C][/ROW]
[ROW][C]37[/C][C]19123.5[/C][C]19175.8848195910[/C][C]17270.3125[/C][C]1.11033803352377[/C][C]0.997268192832622[/C][/ROW]
[ROW][C]38[/C][C]17838.7[/C][C]17327.8374080719[/C][C]17322.5375[/C][C]1.00030595448686[/C][C]1.02948218983692[/C][/ROW]
[ROW][C]39[/C][C]17209.4[/C][C]17305.3378519560[/C][C]17386.8125[/C][C]0.99531399743087[/C][C]0.994456169953066[/C][/ROW]
[ROW][C]40[/C][C]18586.5[/C][C]18570.3331525263[/C][C]17511.975[/C][C]1.06043625305120[/C][C]1.00087057390629[/C][/ROW]
[ROW][C]41[/C][C]16258.1[/C][C]16869.5588249491[/C][C]17631.1458333333[/C][C]0.956804451872642[/C][C]0.963753715713964[/C][/ROW]
[ROW][C]42[/C][C]15141.6[/C][C]14740.4777885044[/C][C]17743.3333333333[/C][C]0.830761475963053[/C][C]1.02721229374318[/C][/ROW]
[ROW][C]43[/C][C]19202.1[/C][C]18964.9957609295[/C][C]17873.2125[/C][C]1.06108489231745[/C][C]1.01250220364188[/C][/ROW]
[ROW][C]44[/C][C]17746.5[/C][C]18789.0706445249[/C][C]17926.5541666667[/C][C]1.04811390241756[/C][C]0.944511856693206[/C][/ROW]
[ROW][C]45[/C][C]19090.1[/C][C]18836.5948244829[/C][C]17991.6125[/C][C]1.04696534701839[/C][C]1.01345812116676[/C][/ROW]
[ROW][C]46[/C][C]18040.3[/C][C]17841.9726610518[/C][C]18134.9041666667[/C][C]0.98384708830426[/C][C]1.01111577417564[/C][/ROW]
[ROW][C]47[/C][C]17515.5[/C][C]17041.4279872432[/C][C]18240.1416666667[/C][C]0.934281558700059[/C][C]1.02781879623654[/C][/ROW]
[ROW][C]48[/C][C]17751.8[/C][C]17819.5733939490[/C][C]18337.6666666667[/C][C]0.971747044913876[/C][C]0.996196688189402[/C][/ROW]
[ROW][C]49[/C][C]21072.4[/C][C]20420.5182382694[/C][C]18391.2625[/C][C]1.11033803352377[/C][C]1.0319228804149[/C][/ROW]
[ROW][C]50[/C][C]17170[/C][C]18498.92476458[/C][C]18493.2666666667[/C][C]1.00030595448686[/C][C]0.928162053660302[/C][/ROW]
[ROW][C]51[/C][C]19439.5[/C][C]18533.3728505528[/C][C]18620.6291666667[/C][C]0.99531399743087[/C][C]1.04889164842006[/C][/ROW]
[ROW][C]52[/C][C]19795.4[/C][C]19753.6872227593[/C][C]18627.8875[/C][C]1.06043625305120[/C][C]1.00211164512074[/C][/ROW]
[ROW][C]53[/C][C]17574.9[/C][C]17851.6229143512[/C][C]18657.5458333333[/C][C]0.956804451872642[/C][C]0.984498725091895[/C][/ROW]
[ROW][C]54[/C][C]16165.4[/C][C]15577.1965165514[/C][C]18750.5041666667[/C][C]0.830761475963053[/C][C]1.03776054842883[/C][/ROW]
[ROW][C]55[/C][C]19464.6[/C][C]19944.5318580853[/C][C]18796.3583333333[/C][C]1.06108489231745[/C][C]0.975936669684693[/C][/ROW]
[ROW][C]56[/C][C]19932.1[/C][C]NA[/C][C]NA[/C][C]1.04811390241756[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]19961.2[/C][C]NA[/C][C]NA[/C][C]1.04696534701839[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]17343.4[/C][C]NA[/C][C]NA[/C][C]0.98384708830426[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]18924.2[/C][C]NA[/C][C]NA[/C][C]0.934281558700059[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]18574.1[/C][C]NA[/C][C]NA[/C][C]0.971747044913876[/C][C]NA[/C][/ROW]
[ROW][C]61[/C][C]21350.6[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66161&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66161&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	15859.4	NA	NA	1.11033803352377	NA
2	15258.9	NA	NA	1.00030595448686	NA
3	15498.6	NA	NA	0.99531399743087	NA
4	15106.5	NA	NA	1.06043625305120	NA
5	15023.6	NA	NA	0.956804451872642	NA
6	12083	NA	NA	0.830761475963053	NA
7	15761.3	15900.9893411254	14985.5958333333	1.06108489231745	0.99121505347066
8	16942.6	15717.5466506426	14996.0291666667	1.04811390241756	1.07794176639567
9	15070.3	15681.564751243	14978.1125	1.04696534701839	0.96102016852658
10	13659.6	14728.8550086994	14970.675	0.98384708830426	0.927404064466122
11	14768.9	14004.0085687924	14989.0666666667	0.934281558700059	1.05461946323798
12	14725.1	14553.3898628828	14976.5208333333	0.971747044913876	1.01179863514515
13	15998.1	16635.6164552275	14982.4791666667	1.11033803352377	0.96167761760177
14	15370.6	14999.8253601946	14995.2375	1.00030595448686	1.02471859711042
15	14956.9	14911.8026037926	14982.0083333333	0.99531399743087	1.00302427529425
16	15469.7	15936.0681084467	15027.8416666667	1.06043625305120	0.970735058028551
17	15101.8	14419.2025571294	15070.1666666667	0.956804451872642	1.04733947249622
18	11703.7	12533.3903138072	15086.6291666667	0.830761475963053	0.933801605708135
19	16283.6	16118.127100777	15190.2333333333	1.06108489231745	1.01026626097365
20	16726.5	16048.3794367995	15311.675	1.04811390241756	1.04225476883015
21	14968.9	16095.0157291362	15373.0166666667	1.04696534701839	0.930033263210946
22	14861	15242.1116372162	15492.3583333333	0.98384708830426	0.9749961392301
23	14583.3	14599.2549211996	15626.1833333333	0.934281558700059	0.998907141406485
24	15305.8	15305.105034206	15750.0916666667	0.971747044913876	1.00004540745016
25	17903.9	17659.2139562907	15904.3583333333	1.11033803352377	1.01385599859172
26	16379.4	16021.1377397257	16016.2375	1.00030595448686	1.02236184883337
27	15420.3	16090.4244095586	16166.1791666667	0.99531399743087	0.958352595773636
28	17870.5	17333.0470618569	16345.2041666667	1.06043625305120	1.03100741238543
29	15912.8	15768.7871965514	16480.6791666667	0.956804451872642	1.00913277613894
30	13866.5	13784.4790200400	16592.5833333333	0.830761475963053	1.00595024156087
31	17823.2	17716.5542249381	16696.6416666667	1.06108489231745	1.00601955514079
32	17872	17616.9736017338	16808.2625	1.04811390241756	1.01447617530863
33	17422	17739.3751408076	16943.6125	1.04696534701839	0.982109001118222
34	16704.5	16772.6169626853	17047.9916666667	0.98384708830426	0.99593879936346
35	15991.2	15968.9389361326	17092.2125	0.934281558700059	1.00139402273103
36	16583.6	16674.9161092308	17159.7291666667	0.971747044913876	0.994523744009708
37	19123.5	19175.8848195910	17270.3125	1.11033803352377	0.997268192832622
38	17838.7	17327.8374080719	17322.5375	1.00030595448686	1.02948218983692
39	17209.4	17305.3378519560	17386.8125	0.99531399743087	0.994456169953066
40	18586.5	18570.3331525263	17511.975	1.06043625305120	1.00087057390629
41	16258.1	16869.5588249491	17631.1458333333	0.956804451872642	0.963753715713964
42	15141.6	14740.4777885044	17743.3333333333	0.830761475963053	1.02721229374318
43	19202.1	18964.9957609295	17873.2125	1.06108489231745	1.01250220364188
44	17746.5	18789.0706445249	17926.5541666667	1.04811390241756	0.944511856693206
45	19090.1	18836.5948244829	17991.6125	1.04696534701839	1.01345812116676
46	18040.3	17841.9726610518	18134.9041666667	0.98384708830426	1.01111577417564
47	17515.5	17041.4279872432	18240.1416666667	0.934281558700059	1.02781879623654
48	17751.8	17819.5733939490	18337.6666666667	0.971747044913876	0.996196688189402
49	21072.4	20420.5182382694	18391.2625	1.11033803352377	1.0319228804149
50	17170	18498.92476458	18493.2666666667	1.00030595448686	0.928162053660302
51	19439.5	18533.3728505528	18620.6291666667	0.99531399743087	1.04889164842006
52	19795.4	19753.6872227593	18627.8875	1.06043625305120	1.00211164512074
53	17574.9	17851.6229143512	18657.5458333333	0.956804451872642	0.984498725091895
54	16165.4	15577.1965165514	18750.5041666667	0.830761475963053	1.03776054842883
55	19464.6	19944.5318580853	18796.3583333333	1.06108489231745	0.975936669684693
56	19932.1	NA	NA	1.04811390241756	NA
57	19961.2	NA	NA	1.04696534701839	NA
58	17343.4	NA	NA	0.98384708830426	NA
59	18924.2	NA	NA	0.934281558700059	NA
60	18574.1	NA	NA	0.971747044913876	NA
61	21350.6	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 = 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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