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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 computationWed, 15 Dec 2010 15:52:22 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/15/t129242821787eq7sgpq1esbg2.htm/, Retrieved Fri, 03 May 2024 05:41:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110497, Retrieved Fri, 03 May 2024 05:41:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [appelen] [2009-12-17 16:03:06] [7773f496f69461f4a67891f0ef752622]
-    D    [Bivariate Kernel Density Estimation] [Bivariate Kernell...] [2010-12-15 15:52:22] [c1f1b5e209adb4577289f490325e36f2] [Current]
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Dataseries X:
 1.3031
 1.3241
 1.2961
 1.2865
 1.2305
 1.2101
 1.2125
 1.2350
 1.2014
 1.1992
 1.1791
 1.1832
 1.2159
 1.1922
 1.2114
 1.2614
 1.2812
 1.2786
 1.2772
 1.2815
 1.2679
 1.2765
 1.3247
 1.3191
 1.3029
 1.3234
 1.3354
 1.3651
 1.3453
 1.3534
 1.3706
 1.3638
 1.4268
 1.4485
 1.4635
 1.4587
 1.4876
 1.5189
 1.5783
 1.5633
 1.5554
 1.5757
 1.5593
 1.4660
 1.4065
 1.2759
 1.2705
 1.3954
 1.2793
 1.2694
 1.3282
 1.3230
 1.4135
 1.4042
 1.4253
 1.4322
 1.4632
 1.4713
 1.5016
 1.4318
Dataseries Y:
 0.6923
 0.6886
 0.6855
 0.6745
 0.6769
 0.6758
 0.6896
 0.6843
 0.6818
 0.6774
 0.6821
 0.6885
 0.6829
 0.6796
 0.6976
 0.6924
 0.6849
 0.6921
 0.6839
 0.6727
 0.6776
 0.6692
 0.6738
 0.6740
 0.6635
 0.6737
 0.6788
 0.6828
 0.6795
 0.6740
 0.6744
 0.6764
 0.6987
 0.6967
 0.7116
 0.7357
 0.7455
 0.7639
 0.7958
 0.7864
 0.7853
 0.7903
 0.7866
 0.8039
 0.7916
 0.7903
 0.8242
 0.9567
 0.8850
 0.8865
 0.9258
 0.8948
 0.8762
 0.8527
 0.8536
 0.8805
 0.9155
 0.8961
 0.9127
 0.8857




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110497&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110497&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110497&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'George Udny Yule' @ 72.249.76.132







Bandwidth
x axis0.0474072821717292
y axis0.0173090826397725
Correlation
correlation used in KDE0.475424234973302
correlation(x,y)0.475424234973302

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.0474072821717292 \tabularnewline
y axis & 0.0173090826397725 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.475424234973302 \tabularnewline
correlation(x,y) & 0.475424234973302 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110497&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.0474072821717292[/C][/ROW]
[ROW][C]y axis[/C][C]0.0173090826397725[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.475424234973302[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.475424234973302[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110497&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110497&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 axis0.0474072821717292
y axis0.0173090826397725
Correlation
correlation used in KDE0.475424234973302
correlation(x,y)0.475424234973302



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')