Free Statistics

of Irreproducible Research!

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 computationFri, 13 Nov 2009 07:59:28 -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/2009/Nov/13/t1258124426z5tavz620jj40b4.htm/, Retrieved Sat, 04 May 2024 02:05:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56762, Retrieved Sat, 04 May 2024 02:05:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [3/11/2009] [2009-11-02 21:10:41] [b98453cac15ba1066b407e146608df68]
-    D  [Notched Boxplots] [] [2009-11-09 10:28:17] [023d83ebdf42a2acf423907b4076e8a1]
- RMPD    [Box-Cox Linearity Plot] [] [2009-11-09 12:13:26] [023d83ebdf42a2acf423907b4076e8a1]
-    D      [Box-Cox Linearity Plot] [W6 Box Cox ] [2009-11-13 14:48:51] [d31db4f83c6a129f6d3e47077769e868]
- RMP           [Bivariate Kernel Density Estimation] [W6 Bivariate Kern...] [2009-11-13 14:59:28] [852eae237d08746109043531619a60c9] [Current]
Feedback Forum

Post a new message
Dataseries X:
107.25
105.80
102.90
100.00
98.55
108.70
110.14
113.04
115.94
117.39
118.84
120.29
118.84
115.94
114.49
110.14
110.14
120.29
121.74
121.74
121.74
121.74
124.64
128.99
127.54
120.29
108.70
104.35
107.25
127.54
134.78
134.78
126.09
118.84
120.29
123.19
124.64
123.19
118.84
117.39
114.49
124.64
126.09
126.09
123.19
121.74
123.19
126.09
126.09
124.64
123.19
120.29
115.94
118.84
117.39
117.39
115.94
114.49
114.49
115.94
115.94
114.49
115.94
111.59
104.35
108.70
105.80
101.45
101.45
101.45
104.35
105.80
102.90
98.55
92.75
88.41
94.20
111.59
114.49
108.70
100.00
95.65
100.00
111.59
115.94
Dataseries Y:
105.9
117.6
113.6
115.9
118.9
77.6
81.2
123.1
136.6
112.1
95.1
96.3
105.7
115
105.7
105.7
111.1
82.4
60
107.3
99.3
113.5
108.9
100.2
103.9
138.7
120.2
100.2
143.2
70.9
85.2
133
136.6
117.9
106.3
122.3
125.5
148.4
126.3
99.6
140.4
80.3
92.6
138.5
110.9
119.6
105
109
129.4
148.6
101.4
134.8
143.7
81.6
90.3
141.5
140.7
140.2
100.2
125.7
119.6
134.7
109
116.3
146.9
97.4
89.4
132.1
139.8
129
112.5
121.9
121.7
123.1
131.6
119.3
132.5
98.3
85.1
131.7
129.3
90.7
78.6
68.9
79.1




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=56762&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=56762&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56762&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 axis3.74171693183232
y axis9.6362595378109
Correlation
correlation used in KDE-0.124083572780831
correlation(x,y)-0.124083572780831

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.74171693183232 \tabularnewline
y axis & 9.6362595378109 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.124083572780831 \tabularnewline
correlation(x,y) & -0.124083572780831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56762&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.74171693183232[/C][/ROW]
[ROW][C]y axis[/C][C]9.6362595378109[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.124083572780831[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.124083572780831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56762&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56762&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 axis3.74171693183232
y axis9.6362595378109
Correlation
correlation used in KDE-0.124083572780831
correlation(x,y)-0.124083572780831



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')