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Author's title

Author*Unverified author*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationThu, 13 Dec 2007 14:16:16 -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/2007/Dec/13/t119757964471odrewqy6sllzo.htm/, Retrieved Sun, 05 May 2024 17:01:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3735, Retrieved Sun, 05 May 2024 17:01:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [totaal VS suiker] [2007-12-13 21:16:16] [a98121933c09d0d44a9f89053acd1df1] [Current]
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Dataseries X:
105.3
103
103.8
103.4
105.8
101.4
97
94.3
96.6
97.1
95.7
96.9
97.4
95.3
93.6
91.5
93.1
91.7
94.3
93.9
90.9
88.3
91.3
91.7
92.4
92
95.6
95.8
96.4
99
107
109.7
116.2
115.9
113.8
112.6
113.7
115.9
110.3
111.3
113.4
108.2
104.8
106
110.9
115
118.4
121.4
128.8
131.7
141.7
142.9
139.4
134.7
125
113.6
111.5
108.5
112.3
116.6
115.5
120.1
132.9
128.1
129.3
132.5
131
124.9
120.8
122
122.1
127.4
135.2
137.3
135
136
138.4
134.7
138.4
133.9
133.6
141.2
151.8
155.4
156.6
161.6
160.7
156
159.5
168.7
169.9
169.9
185.9
Dataseries Y:
112,1
104,2
102,4
100,3
102,6
101,5
103,4
99,4
97,9
98
90,2
87,1
91,8
94,8
91,8
89,3
91,7
86,2
82,8
82,3
79,8
79,4
85,3
87,5
88,3
88,6
94,9
94,7
92,6
91,8
96,4
96,4
107,1
111,9
107,8
109,2
115,3
119,2
107,8
106,8
104,2
94,8
97,5
98,3
100,6
94,9
93,6
98
104,3
103,9
105,3
102,6
103,3
107,9
107,8
109,8
110,6
110,8
119,3
128,1
127,6
137,9
151,4
143,6
143,4
141,9
135,2
133,1
129,6
134,1
136,8
143,5
162,5
163,1
157,2
158,8
155,4
148,5
154,2
153,3
149,4
147,9
156
163
159,1
159,5
157,3
156,4
156,6
162,4
166,8
162,6
168,1




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3735&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3735&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3735&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Bandwidth
x axis7.5695365966444
y axis6.44291647460835
Correlation
correlation used in KDE0.866885086695083
correlation(x,y)0.866885086695083

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 7.5695365966444 \tabularnewline
y axis & 6.44291647460835 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.866885086695083 \tabularnewline
correlation(x,y) & 0.866885086695083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3735&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]7.5695365966444[/C][/ROW]
[ROW][C]y axis[/C][C]6.44291647460835[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.866885086695083[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.866885086695083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3735&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3735&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 axis7.5695365966444
y axis6.44291647460835
Correlation
correlation used in KDE0.866885086695083
correlation(x,y)0.866885086695083



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')