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Description of Statistical Computation

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 computationThu, 02 Dec 2010 11:50:11 +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/02/t1291290507fqapug7p8wiptdo.htm/, Retrieved Sun, 05 May 2024 10:05:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104220, Retrieved Sun, 05 May 2024 10:05:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140

Tree of Dependent Computations

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] [Subsititutie appelen] [2010-12-02 11:50:11] [2fa539864aa87c5da4977c85c6885fac] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,25 	1,23 	1,20 	1,15 	1,13 	1,17 	1,22 	1,21 	1,15 	1,24 	1,16 	1,30 	1,30 	1,26 	1,29 	1,29 	1,35 	1,35 	1,45 	1,43 	1,43 	1,41 	1,46 	1,78 	1,79 	1,66 	1,56 	1,53 	1,47 	1,47 	1,45 	1,41 	1,45 	1,46 	1,38 	1,45 	1,48 	1,48 	1,51 	1,45 	1,42 	1,43 	1,43 	1,44 	1,41 	1,35 	1,43 	1,70 	1,63 	1,57 	1,47 	1,39 	1,34 	1,28 	1,26 	1,26
Dataseries Y:
Download CSV
Histogram 
1,89 	1,84 	1,83 	1,80 	1,77 	1,75 	1,73 	1,71 	1,73 	1,75 	1,78 	1,99 	1,98 	1,94 	1,95 	1,91 	1,90 	1,86 	1,90 	1,88 	1,87 	1,89 	1,97 	2,14 	2,15 	2,06 	1,95 	1,94 	1,92 	1,89 	1,87 	1,87 	1,88 	1,92 	1,94 	2,14 	2,10 	2,02 	1,96 	1,93 	1,87 	1,85 	1,87 	1,88 	1,90 	1,90 	2,00 	2,21 	2,07 	1,96 	1,92 	1,82 	1,75 	1,70 	1,70 	1,73

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104220&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104220&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104220&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Figures (Output of Computation)

Input Parameters & R Code

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')