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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationTue, 11 Nov 2008 05:21:24 -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/Nov/11/t1226406112hb5f3zqqulgz06c.htm/, Retrieved Sun, 19 May 2024 10:48:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23374, Retrieved Sun, 19 May 2024 10:48:48 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [Various EDA Topic...] [2008-11-11 12:21:24] [620b6ad5c4696049e39cb73ce029682c] [Current]
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Dataseries X:
1045.9
1401.9
1027.6
1703.8
1481.3
1422.7
1304.7
1246.1
1417.8
1459.1
1156.4
1304.5
1336.9
1372.3
975.5
1180.8
1361.3
1428.1
1355.9
1781.2
1697
1852
1844.1
1967.2
1747.1
1863.9
1559.3
1675
2237.5
1965.2
1871.5
1752.2
1360.7
1444.3
1621.6
1368
1553.9
1695.3
1397.1
1848.4
1809.2
1551.1
1546.6
1467.9
1662.4
1972.3
1673.5
1762
2019.8
1754.3
1400.4
1453.6
1740.9
1694.6
1541.2
1482.3
1632.1
1837.3
1797
2066.2
1983.8
1601.7
1660.3
1954
1991.9
1881.4
2345.5
1773.1
1719.2
2240.9
1816.4
2171.3
1823.3
2022.5
1991
1920
2168.4
2013.5
1790.8
1855.7
2074
2535.8
1837.2
1805.1
1785.7
2250
1959.7
1890.8
2405.7
2090.3
1666.5
1803.5
1793.8
1488.8
1545
1369.9
1451.6
Dataseries Y:
4,5
4,7
4,75
4,75
4,75
4,75
4,75
4,75
4,58
4,5
4,5
4,49
4,03
3,75
3,39
3,25
3,25
3,25
3,25
3,25
3,25
3,25
3,25
3,25
3,25
3,25
3,25
2,85
2,75
2,75
2,55
2,5
2,5
2,1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2,21
2,25
2,25
2,45
2,5
2,5
2,64
2,75
2,93
3
3,17
3,25
3,39
3,5
3,5
3,65
3,75
3,75
3,9
4
4
4
4
4
4
4
4
4
4
4
4
4,18
4,25
4,25




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=23374&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=23374&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23374&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







Bandwidth
x axis111.537179366116
y axis0.222883429865528
Correlation
correlation used in KDE-0.194769834639652
correlation(x,y)-0.194769834639652

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 111.537179366116 \tabularnewline
y axis & 0.222883429865528 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.194769834639652 \tabularnewline
correlation(x,y) & -0.194769834639652 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23374&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]111.537179366116[/C][/ROW]
[ROW][C]y axis[/C][C]0.222883429865528[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.194769834639652[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.194769834639652[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23374&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23374&T=1

As an alternative you can also use a QR Code:  

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

Bandwidth
x axis111.537179366116
y axis0.222883429865528
Correlation
correlation used in KDE-0.194769834639652
correlation(x,y)-0.194769834639652



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
par4 <- as(par4,'numeric')
par5 <- as(par5,'numeric')
library('GenKern')
if (par3==0) par3 <- dpik(x)
if (par4==0) par4 <- dpik(y)
if (par5==0) par5 <- cor(x,y)
if (par1 > 500) par1 <- 500
if (par2 > 500) par2 <- 500
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par7=='Y') points(x,y)
(r<-lm(y ~ x))
abline(r)
box()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Bandwidth',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'x axis',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'y axis',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation used in KDE',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation(x,y)',header=TRUE)
a<-table.element(a,cor(x,y))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')