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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationMon, 15 Dec 2008 15:31:00 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/15/t1229380320yc0awp3zsh19vi1.htm/, Retrieved Tue, 14 May 2024 10:27:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33839, Retrieved Tue, 14 May 2024 10:27:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact231
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [SMP prof bach] [2008-12-15 22:25:20] [bc937651ef42bf891200cf0e0edc7238]
- RM      [Variance Reduction Matrix] [VRM prof bach] [2008-12-15 22:31:00] [21d7d81e7693ad6dde5aadefb1046611] [Current]
- RMP       [(Partial) Autocorrelation Function] [ARIMA Prof bach A...] [2008-12-15 22:38:57] [bc937651ef42bf891200cf0e0edc7238]
-   P         [(Partial) Autocorrelation Function] [ARIMA ACF prof ba...] [2008-12-15 22:41:53] [bc937651ef42bf891200cf0e0edc7238]
-   P           [(Partial) Autocorrelation Function] [ARIMA ACF prof ba...] [2008-12-15 22:44:07] [bc937651ef42bf891200cf0e0edc7238]
-   P             [(Partial) Autocorrelation Function] [ARIMA ACF prof ba...] [2008-12-15 22:46:08] [bc937651ef42bf891200cf0e0edc7238]
-   P           [(Partial) Autocorrelation Function] [acf prof bach L =...] [2008-12-19 15:35:04] [bc937651ef42bf891200cf0e0edc7238]
-   P             [(Partial) Autocorrelation Function] [acf prof bach lam...] [2008-12-19 15:40:07] [bc937651ef42bf891200cf0e0edc7238]
-   P             [(Partial) Autocorrelation Function] [acf prof bach lam...] [2008-12-19 15:40:07] [bc937651ef42bf891200cf0e0edc7238]
-   P               [(Partial) Autocorrelation Function] [acf lambda = 1,1,1] [2008-12-19 15:45:45] [bc937651ef42bf891200cf0e0edc7238]
-  MPD                [(Partial) Autocorrelation Function] [ACF bij d=0 en D=0] [2010-12-17 13:29:13] [616fb52b46273b7e6805de1e68b3a688]
-   P                   [(Partial) Autocorrelation Function] [ACF bij d=0 en D=1] [2010-12-17 13:34:11] [616fb52b46273b7e6805de1e68b3a688]
-   P                     [(Partial) Autocorrelation Function] [ACF bij d=1 en D=1] [2010-12-17 13:51:58] [616fb52b46273b7e6805de1e68b3a688]
-  MPD            [(Partial) Autocorrelation Function] [] [2010-12-24 12:03:15] [4dfa50539945b119a90a7606969443b9]
-  MPD            [(Partial) Autocorrelation Function] [] [2010-12-24 12:12:12] [4dfa50539945b119a90a7606969443b9]
- RMP         [ARIMA Backward Selection] [Arima backward se...] [2008-12-19 17:26:16] [bc937651ef42bf891200cf0e0edc7238]
- RMP           [ARIMA Forecasting] [ARIMA forecast pr...] [2008-12-20 11:34:44] [bc937651ef42bf891200cf0e0edc7238]
-  MPD            [ARIMA Forecasting] [] [2010-12-21 19:37:30] [94f4aa1c01e87d8321fffb341ed4df07]
-    D              [ARIMA Forecasting] [] [2010-12-22 16:40:18] [94f4aa1c01e87d8321fffb341ed4df07]
-  MPD            [ARIMA Forecasting] [ARIMA Forecasting] [2010-12-22 13:25:50] [616fb52b46273b7e6805de1e68b3a688]
-    D              [ARIMA Forecasting] [ARIMA Forecasting] [2010-12-24 15:04:34] [616fb52b46273b7e6805de1e68b3a688]
- RMPD            [ARIMA Forecasting] [] [2010-12-24 13:59:54] [4dfa50539945b119a90a7606969443b9]
-   PD              [ARIMA Forecasting] [] [2010-12-26 10:14:56] [4dfa50539945b119a90a7606969443b9]
- RMP           [ARIMA Forecasting] [ARIMA forecast pr...] [2008-12-20 11:40:03] [bc937651ef42bf891200cf0e0edc7238]
-   P             [ARIMA Forecasting] [ARIMA forecast pr...] [2008-12-20 13:00:09] [bc937651ef42bf891200cf0e0edc7238]
-   P               [ARIMA Forecasting] [ARIMA voorspellin...] [2008-12-20 13:17:10] [bc937651ef42bf891200cf0e0edc7238]
-  M D          [ARIMA Backward Selection] [] [2010-12-21 17:53:23] [94f4aa1c01e87d8321fffb341ed4df07]
-  MPD          [ARIMA Backward Selection] [] [2010-12-21 19:17:29] [94f4aa1c01e87d8321fffb341ed4df07]
-  MPD          [ARIMA Backward Selection] [] [2010-12-24 13:46:46] [4dfa50539945b119a90a7606969443b9]
-  MPD          [ARIMA Backward Selection] [Paper Statistiek] [2010-12-28 15:46:48] [82c18f3ebe9df70882495121eb816e07]
-  MP           [ARIMA Backward Selection] [Paper Statistiek] [2010-12-28 16:09:56] [82c18f3ebe9df70882495121eb816e07]
- RMPD          [ARIMA Backward Selection] [ARIMA Backward Se...] [2010-12-28 18:28:51] [74be16979710d4c4e7c6647856088456]
-  MPD        [(Partial) Autocorrelation Function] [] [2010-12-20 16:16:49] [94f4aa1c01e87d8321fffb341ed4df07]
-  MPD        [(Partial) Autocorrelation Function] [b-r0245787] [2010-12-22 14:53:44] [ebb35fb07def4d07c0eb7ec8d2fd3b0e]
-               [(Partial) Autocorrelation Function] [b-r0245095] [2010-12-22 14:58:29] [ec8d68d52c1e9c5e97bb689b42436a8c]
-   PD            [(Partial) Autocorrelation Function] [b-r0245095] [2010-12-22 15:32:51] [ec8d68d52c1e9c5e97bb689b42436a8c]
-   PD          [(Partial) Autocorrelation Function] [b-r0245787] [2010-12-22 15:30:39] [ebb35fb07def4d07c0eb7ec8d2fd3b0e]
-  MPD        [(Partial) Autocorrelation Function] [] [2010-12-24 12:53:41] [4dfa50539945b119a90a7606969443b9]
-  MPD        [(Partial) Autocorrelation Function] [] [2010-12-28 12:28:43] [c6813a60da787bb62b5d86150b8926dd]
- R P           [(Partial) Autocorrelation Function] [Deel 4: ARIMA bac...] [2012-12-13 15:17:46] [b4e5b8b5af0253f45dc68b47bb41cf13]
- RMPD        [(Partial) Autocorrelation Function] [Autocorrelation] [2010-12-28 16:20:44] [74be16979710d4c4e7c6647856088456]
- RMPD        [ARIMA Backward Selection] [arima-model] [2010-12-29 22:10:14] [5a05da414fd67612c3b80d44effe0727]
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Dataseries X:
13363
12530
11420
10948
10173
10602
16094
19631
17140
14345
12632
12894
11808
10673
9939
9890
9283
10131
15864
19283
16203
13919
11937
11795
11268
10522
9929
9725
9372
10068
16230
19115
18351
16265
14103
14115
13327
12618
12129
11775
11493
12470
20792
22337
21325
18581
16475
16581
15745
14453
13712
13766
13336
15346
24446
26178
24628
21282
18850
18822
18060
17536
16417
15842
15188
16905
25430
27962
26607
23364
20827
20506
19181
18016
17354
16256
15770
17538
26899
28915
25247
22856
19980
19856
16994
16839
15618
15883
15513
17106
25272
26731
22891
19583
16939
16757
15435
14786
13680
13208
12707
14277
22436
23229
18241
16145
13994
14780
13100
12329
12463
11532
10784
13106
19491
20418
16094
14491
13067




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33839&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33839&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33839&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Variance Reduction Matrix
V(Y[t],d=0,D=0)21813863.9884632Range19632Trim Var.15001746.6688415
V(Y[t],d=1,D=0)7825315.67086774Range14349Trim Var.3508439.31581312
V(Y[t],d=2,D=0)9819617.04907162Range14961Trim Var.5274942.7496337
V(Y[t],d=3,D=0)20672629.2995502Range23611Trim Var.8572604.1493652
V(Y[t],d=0,D=1)4347872.10174572Range9212Trim Var.3254351.91086226
V(Y[t],d=1,D=1)493932.889487871Range4629Trim Var.206454.268130863
V(Y[t],d=2,D=1)1140888.77692308Range6665Trim Var.517844.694483403
V(Y[t],d=3,D=1)3630174.48991785Range10341Trim Var.1630117.23877210
V(Y[t],d=0,D=2)3039947.54826428Range7535Trim Var.2109661.17647059
V(Y[t],d=1,D=2)1173276.35243651Range5641Trim Var.645101.111302352
V(Y[t],d=2,D=2)2900827.70991117Range7913Trim Var.1867671.40434910
V(Y[t],d=3,D=2)9248736.51063067Range14672Trim Var.5894249.95137007

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 21813863.9884632 & Range & 19632 & Trim Var. & 15001746.6688415 \tabularnewline
V(Y[t],d=1,D=0) & 7825315.67086774 & Range & 14349 & Trim Var. & 3508439.31581312 \tabularnewline
V(Y[t],d=2,D=0) & 9819617.04907162 & Range & 14961 & Trim Var. & 5274942.7496337 \tabularnewline
V(Y[t],d=3,D=0) & 20672629.2995502 & Range & 23611 & Trim Var. & 8572604.1493652 \tabularnewline
V(Y[t],d=0,D=1) & 4347872.10174572 & Range & 9212 & Trim Var. & 3254351.91086226 \tabularnewline
V(Y[t],d=1,D=1) & 493932.889487871 & Range & 4629 & Trim Var. & 206454.268130863 \tabularnewline
V(Y[t],d=2,D=1) & 1140888.77692308 & Range & 6665 & Trim Var. & 517844.694483403 \tabularnewline
V(Y[t],d=3,D=1) & 3630174.48991785 & Range & 10341 & Trim Var. & 1630117.23877210 \tabularnewline
V(Y[t],d=0,D=2) & 3039947.54826428 & Range & 7535 & Trim Var. & 2109661.17647059 \tabularnewline
V(Y[t],d=1,D=2) & 1173276.35243651 & Range & 5641 & Trim Var. & 645101.111302352 \tabularnewline
V(Y[t],d=2,D=2) & 2900827.70991117 & Range & 7913 & Trim Var. & 1867671.40434910 \tabularnewline
V(Y[t],d=3,D=2) & 9248736.51063067 & Range & 14672 & Trim Var. & 5894249.95137007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33839&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]21813863.9884632[/C][C]Range[/C][C]19632[/C][C]Trim Var.[/C][C]15001746.6688415[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]7825315.67086774[/C][C]Range[/C][C]14349[/C][C]Trim Var.[/C][C]3508439.31581312[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]9819617.04907162[/C][C]Range[/C][C]14961[/C][C]Trim Var.[/C][C]5274942.7496337[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]20672629.2995502[/C][C]Range[/C][C]23611[/C][C]Trim Var.[/C][C]8572604.1493652[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]4347872.10174572[/C][C]Range[/C][C]9212[/C][C]Trim Var.[/C][C]3254351.91086226[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]493932.889487871[/C][C]Range[/C][C]4629[/C][C]Trim Var.[/C][C]206454.268130863[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1140888.77692308[/C][C]Range[/C][C]6665[/C][C]Trim Var.[/C][C]517844.694483403[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]3630174.48991785[/C][C]Range[/C][C]10341[/C][C]Trim Var.[/C][C]1630117.23877210[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]3039947.54826428[/C][C]Range[/C][C]7535[/C][C]Trim Var.[/C][C]2109661.17647059[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1173276.35243651[/C][C]Range[/C][C]5641[/C][C]Trim Var.[/C][C]645101.111302352[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]2900827.70991117[/C][C]Range[/C][C]7913[/C][C]Trim Var.[/C][C]1867671.40434910[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]9248736.51063067[/C][C]Range[/C][C]14672[/C][C]Trim Var.[/C][C]5894249.95137007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33839&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33839&T=1

As an alternative you can also use a QR Code:  

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

Variance Reduction Matrix
V(Y[t],d=0,D=0)21813863.9884632Range19632Trim Var.15001746.6688415
V(Y[t],d=1,D=0)7825315.67086774Range14349Trim Var.3508439.31581312
V(Y[t],d=2,D=0)9819617.04907162Range14961Trim Var.5274942.7496337
V(Y[t],d=3,D=0)20672629.2995502Range23611Trim Var.8572604.1493652
V(Y[t],d=0,D=1)4347872.10174572Range9212Trim Var.3254351.91086226
V(Y[t],d=1,D=1)493932.889487871Range4629Trim Var.206454.268130863
V(Y[t],d=2,D=1)1140888.77692308Range6665Trim Var.517844.694483403
V(Y[t],d=3,D=1)3630174.48991785Range10341Trim Var.1630117.23877210
V(Y[t],d=0,D=2)3039947.54826428Range7535Trim Var.2109661.17647059
V(Y[t],d=1,D=2)1173276.35243651Range5641Trim Var.645101.111302352
V(Y[t],d=2,D=2)2900827.70991117Range7913Trim Var.1867671.40434910
V(Y[t],d=3,D=2)9248736.51063067Range14672Trim Var.5894249.95137007



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
n <- length(x)
sx <- sort(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Reduction Matrix',6,TRUE)
a<-table.row.end(a)
for (bigd in 0:2) {
for (smalld in 0:3) {
mylabel <- 'V(Y[t],d='
mylabel <- paste(mylabel,as.character(smalld),sep='')
mylabel <- paste(mylabel,',D=',sep='')
mylabel <- paste(mylabel,as.character(bigd),sep='')
mylabel <- paste(mylabel,')',sep='')
a<-table.row.start(a)
a<-table.element(a,mylabel,header=TRUE)
myx <- x
if (smalld > 0) myx <- diff(x,lag=1,differences=smalld)
if (bigd > 0) myx <- diff(myx,lag=par1,differences=bigd)
a<-table.element(a,var(myx))
a<-table.element(a,'Range',header=TRUE)
a<-table.element(a,max(myx)-min(myx))
a<-table.element(a,'Trim Var.',header=TRUE)
smyx <- sort(myx)
sn <- length(smyx)
a<-table.element(a,var(smyx[smyx>quantile(smyx,0.05) & smyxa<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')