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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, 28 Nov 2010 16:24:36 +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/Nov/28/t1290961352hzt72r5arpvveus.htm/, Retrieved Thu, 02 May 2024 18:41:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=102639, Retrieved Thu, 02 May 2024 18:41:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [Bivariate density...] [2008-11-14 00:47:52] [7a4703cb85a198d9845d72899eff0288]
-  MPD  [Bivariate Kernel Density Estimation] [Paper - Wisselkoe...] [2010-11-28 15:16:48] [4a7069087cf9e0eda253aeed7d8c30d6]
-   PD      [Bivariate Kernel Density Estimation] [Paper - Werkloosh...] [2010-11-28 16:24:36] [cfd788255f1b1b5389e58d7f218c70bf] [Current]
- RMPD        [Central Tendency] [Paper - Robustnes...] [2010-11-28 17:01:51] [4a7069087cf9e0eda253aeed7d8c30d6]
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Dataseries X:
376.974
377.632
378.205
370.861
369.167
371.551
382.842
381.903
384.502
392.058
384.359
388.884
386.586
387.495
385.705
378.67
377.367
376.911
389.827
387.82
387.267
380.575
372.402
376.74
377.795
376.126
370.804
367.98
367.866
366.121
379.421
378.519
372.423
355.072
344.693
342.892
344.178
337.606
327.103
323.953
316.532
306.307
327.225
329.573
313.761
307.836
300.074
304.198
306.122
300.414
292.133
290.616
280.244
285.179
305.486
305.957
293.886
289.441
288.776
299.149
306.532
309.914
313.468
314.901
309.16
316.15
336.544
339.196
326.738
320.838
318.62
331.533
335.378
Dataseries Y:
49.2
50.221
51.573
53.091
53.337
54.978
57.885
67.099
67.169
69.796
70.6
71.982
73.957
75.273
76.322
77.078
77.954
79.238
82.179
83.834
83.744
84.861
86.478
88.29
90.287
91.23
92.38
92.506
94.172
94.728
96.581
97.344
98.346
98.214
98.366
98.768
99.832
99.976
99.961
100.164
99.964
99.304
104.008
104.644
103.95
104.263
104.241
105.141
106.018
105.866
105.944
106.379
105.082
104.915
107.026
107.306
107.051
107.922
108.571
110.234
112.353
113.646
114.561
115.1
115.24
116.571
119.35
119.95
119.081
119.915
120.663
122.335
124.206




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=102639&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=102639&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102639&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Bandwidth
x axis8.43191266369603
y axis6.51347770513499
Correlation
correlation used in KDE-0.74188361636946
correlation(x,y)-0.74188361636946

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 8.43191266369603 \tabularnewline
y axis & 6.51347770513499 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.74188361636946 \tabularnewline
correlation(x,y) & -0.74188361636946 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102639&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]8.43191266369603[/C][/ROW]
[ROW][C]y axis[/C][C]6.51347770513499[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.74188361636946[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.74188361636946[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102639&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102639&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 axis8.43191266369603
y axis6.51347770513499
Correlation
correlation used in KDE-0.74188361636946
correlation(x,y)-0.74188361636946



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')