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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 computationSun, 09 Nov 2008 14:19:51 -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/09/t12262656333dgbd0aeu0whdwq.htm/, Retrieved Sun, 19 May 2024 10:48:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22881, Retrieved Sun, 19 May 2024 10:48:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact169
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Testing Population Proportion - Critical Value] [vraag 1] [2008-11-09 20:15:31] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM    [Minimum Sample Size - Testing Proportions] [vraag 4] [2008-11-09 20:51:51] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM D      [Bivariate Kernel Density Estimation] [vraag 1] [2008-11-09 21:19:51] [3dc594a6c62226e1e98766c4d385bfaa] [Current]
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Dataseries X:
440427
386715
291787
278253
300903
327695
471590
442850
387181
420099
289850
392468
549174
415506
356662
338612
359886
410547
495272
474588
442893
477793
336263
449838
451406
439690
401513
326472
369464
429525
464658
510691
513151
538609
398949
511635
554318
515879
488122
401716
453358
464884
571868
497485
538214
502396
349385
502427
514106
527537
495918
376847
420552
442679
478422
483796
529032
482991
354287
459146
473744
478642
426208
348908
321310
Dataseries Y:
1.90
1.76
1.76
1.98
1.84
1.86
1.57
1.77
1.61
1.74
1.73
1.78
2.00
1.81
1.88
1.97
1.90
1.87
1.77
1.76
1.77
1.86
1.76
1.77
1.76
1.83
1.84
1.79
1.90
1.94
1.89
1.80
1.76
1.81
1.77
1.81
1.98
1.90
1.97
2.03
2.06
1.94
1.83
1.72
1.81
1.75
1.84
1.82
1.89
2.01
2.17
2.19
2.20
2.07
1.82
1.91
2.04
1.84
1.81
1.89
1.94
1.99
2.00
2.14
1.85




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22881&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22881&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22881&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis33861.6330065604
y axis0.0434957764644146
Correlation
correlation used in KDE0.0485675870912289
correlation(x,y)0.0485675870912289

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 33861.6330065604 \tabularnewline
y axis & 0.0434957764644146 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.0485675870912289 \tabularnewline
correlation(x,y) & 0.0485675870912289 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22881&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]33861.6330065604[/C][/ROW]
[ROW][C]y axis[/C][C]0.0434957764644146[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.0485675870912289[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.0485675870912289[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22881&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22881&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 axis33861.6330065604
y axis0.0434957764644146
Correlation
correlation used in KDE0.0485675870912289
correlation(x,y)0.0485675870912289



Parameters (Session):
par1 = 98 ; par2 = 0.8571 ; par3 = 0.69 ; par4 = 0.05 ;
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')