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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationFri, 05 Dec 2008 02:50:49 -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/05/t1228471209noj1bdh1r2x1t8f.htm/, Retrieved Thu, 16 May 2024 09:09:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29107, Retrieved Thu, 16 May 2024 09:09:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact238

Tree of Dependent Computations

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]
-   PD  [Univariate Data Series] [Werkloosheids Bel...] [2008-12-03 18:39:41] [74be16979710d4c4e7c6647856088456]
-   PD    [Univariate Data Series] [Werkloosheids Bel...] [2008-12-03 18:47:55] [74be16979710d4c4e7c6647856088456]
-   PD      [Univariate Data Series] [Paper: tijdreeks ...] [2008-12-05 09:45:57] [74be16979710d4c4e7c6647856088456]
F RMPD          [Variance Reduction Matrix] [Paper: VRM werklo...] [2008-12-05 09:50:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-                 [Variance Reduction Matrix] [paper var red mat...] [2008-12-16 18:36:11] [74be16979710d4c4e7c6647856088456]
-    D              [Variance Reduction Matrix] [paper var red mat...] [2008-12-18 13:55:11] [5de5fb433ddcb9578e0fa830f795b7e9]
Feedback Forum
2008-12-14 17:28:52 [Gregory Van Overmeiren] [reply] 
Volgens mij heb je de verkeerde (waarschijnlijk je eigen) data gebruikt. Als je de data had gebruikt die in de opgave stond dan vond je ook de laagste waarde bij d=1 en D= 1 maar ik kwam dan uit op
V(Y[t],d=1,D=1) 795.483036989776 Range 221.9 Trim Var. 451.063415764475

De variantie geeft de hoeveelheid spreiding weer en hoe kleiner de variantie, hoe beter! Vandaar d=1 en D=1
(=> stel dat er ergens op een andere regel de trimmed variantie kleiner is dan moeten we die nemen !)
2008-12-15 09:20:51 [Nathalie Koulouris] [reply] 
De student heeft voor deze opdracht alleen gebruik gemaakt van de eigen data niet van de Unemployment data. Hij verder wel de juiste conclusies getrokken.
2008-12-16 06:34:12 [Nilay Erdogdu] [reply] 
de student gebruikte zijn eigen data in plaats van de data in de opgave, maar conclusies zijn goed.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95.20
95.00
94.00
92.20
91.00
91.20
103.40
105.00
104.60
103.80
101.80
102.40
103.80
103.40
102.00
101.80
100.20
101.40
113.80
116.00
115.60
113.00
109.40
111.00
112.40
112.20
111.00
108.80
107.40
108.60
118.80
122.20
122.60
122.20
118.80
119.00
118.20
117.80
116.80
114.60
113.40
113.80
124.20
125.80
125.60
122.40
119.00
119.40
118.60
118.00
116.00
114.80
114.60
114.60
124.00
125.20
124.00
117.60
113.20
111.40
112.20
109.80
106.40
105.20
102.20
99.80
111.00
113.00
108.40
105.40
102.00
102.80

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29107&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29107&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29107&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)79.7883489827856Range34.8Trim Var.54.3768154761905
V(Y[t],d=1,D=0)14.258092555332Range18.8Trim Var.5.84100358422939
V(Y[t],d=2,D=0)21.7870393374741Range24.2Trim Var.9.33851930195664
V(Y[t],d=3,D=0)54.2493776641092Range35.8Trim Var.22.7946229508197
V(Y[t],d=0,D=1)60.6170734463277Range26.6Trim Var.47.8194828791055
V(Y[t],d=1,D=1)2.04596142606663Range6.8Trim Var.1.17037707390648
V(Y[t],d=2,D=1)3.99622504537205Range11.0000000000000Trim Var.2.20609351432881
V(Y[t],d=3,D=1)12.2211278195489Range20.2Trim Var.6.86992941176473
V(Y[t],d=0,D=2)16.8558865248227Range17.4000000000000Trim Var.10.0902206736353
V(Y[t],d=1,D=2)4.98852913968547Range11.6000000000000Trim Var.2.35409756097560
V(Y[t],d=2,D=2)8.6377584541063Range14.4000000000000Trim Var.4.97641025641026
V(Y[t],d=3,D=2)25.786585858586Range26.2000000000001Trim Var.13.7880701754387

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 79.7883489827856 & Range & 34.8 & Trim Var. & 54.3768154761905 \tabularnewline
V(Y[t],d=1,D=0) & 14.258092555332 & Range & 18.8 & Trim Var. & 5.84100358422939 \tabularnewline
V(Y[t],d=2,D=0) & 21.7870393374741 & Range & 24.2 & Trim Var. & 9.33851930195664 \tabularnewline
V(Y[t],d=3,D=0) & 54.2493776641092 & Range & 35.8 & Trim Var. & 22.7946229508197 \tabularnewline
V(Y[t],d=0,D=1) & 60.6170734463277 & Range & 26.6 & Trim Var. & 47.8194828791055 \tabularnewline
V(Y[t],d=1,D=1) & 2.04596142606663 & Range & 6.8 & Trim Var. & 1.17037707390648 \tabularnewline
V(Y[t],d=2,D=1) & 3.99622504537205 & Range & 11.0000000000000 & Trim Var. & 2.20609351432881 \tabularnewline
V(Y[t],d=3,D=1) & 12.2211278195489 & Range & 20.2 & Trim Var. & 6.86992941176473 \tabularnewline
V(Y[t],d=0,D=2) & 16.8558865248227 & Range & 17.4000000000000 & Trim Var. & 10.0902206736353 \tabularnewline
V(Y[t],d=1,D=2) & 4.98852913968547 & Range & 11.6000000000000 & Trim Var. & 2.35409756097560 \tabularnewline
V(Y[t],d=2,D=2) & 8.6377584541063 & Range & 14.4000000000000 & Trim Var. & 4.97641025641026 \tabularnewline
V(Y[t],d=3,D=2) & 25.786585858586 & Range & 26.2000000000001 & Trim Var. & 13.7880701754387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29107&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]79.7883489827856[/C][C]Range[/C][C]34.8[/C][C]Trim Var.[/C][C]54.3768154761905[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]14.258092555332[/C][C]Range[/C][C]18.8[/C][C]Trim Var.[/C][C]5.84100358422939[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]21.7870393374741[/C][C]Range[/C][C]24.2[/C][C]Trim Var.[/C][C]9.33851930195664[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]54.2493776641092[/C][C]Range[/C][C]35.8[/C][C]Trim Var.[/C][C]22.7946229508197[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]60.6170734463277[/C][C]Range[/C][C]26.6[/C][C]Trim Var.[/C][C]47.8194828791055[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]2.04596142606663[/C][C]Range[/C][C]6.8[/C][C]Trim Var.[/C][C]1.17037707390648[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3.99622504537205[/C][C]Range[/C][C]11.0000000000000[/C][C]Trim Var.[/C][C]2.20609351432881[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]12.2211278195489[/C][C]Range[/C][C]20.2[/C][C]Trim Var.[/C][C]6.86992941176473[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]16.8558865248227[/C][C]Range[/C][C]17.4000000000000[/C][C]Trim Var.[/C][C]10.0902206736353[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]4.98852913968547[/C][C]Range[/C][C]11.6000000000000[/C][C]Trim Var.[/C][C]2.35409756097560[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]8.6377584541063[/C][C]Range[/C][C]14.4000000000000[/C][C]Trim Var.[/C][C]4.97641025641026[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]25.786585858586[/C][C]Range[/C][C]26.2000000000001[/C][C]Trim Var.[/C][C]13.7880701754387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29107&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29107&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Variance Reduction Matrix
V(Y[t],d=0,D=0)79.7883489827856Range34.8Trim Var.54.3768154761905
V(Y[t],d=1,D=0)14.258092555332Range18.8Trim Var.5.84100358422939
V(Y[t],d=2,D=0)21.7870393374741Range24.2Trim Var.9.33851930195664
V(Y[t],d=3,D=0)54.2493776641092Range35.8Trim Var.22.7946229508197
V(Y[t],d=0,D=1)60.6170734463277Range26.6Trim Var.47.8194828791055
V(Y[t],d=1,D=1)2.04596142606663Range6.8Trim Var.1.17037707390648
V(Y[t],d=2,D=1)3.99622504537205Range11.0000000000000Trim Var.2.20609351432881
V(Y[t],d=3,D=1)12.2211278195489Range20.2Trim Var.6.86992941176473
V(Y[t],d=0,D=2)16.8558865248227Range17.4000000000000Trim Var.10.0902206736353
V(Y[t],d=1,D=2)4.98852913968547Range11.6000000000000Trim Var.2.35409756097560
V(Y[t],d=2,D=2)8.6377584541063Range14.4000000000000Trim Var.4.97641025641026
V(Y[t],d=3,D=2)25.786585858586Range26.2000000000001Trim Var.13.7880701754387


Figures (Output of Computation)

Input Parameters & R Code

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')