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Author's title

Author*Unverified author*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationFri, 05 Oct 2012 06:07:22 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Oct/05/t1349431992pnx35ydn2qn1zpt.htm/, Retrieved Thu, 02 May 2024 15:25:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=172180, Retrieved Thu, 02 May 2024 15:25:28 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [Long Feedback vs....] [2012-10-05 10:07:22] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
149
152
139
154
83
89
159
22
96
148
116
158
212
128
186
95
224
159
105
106
213
173
159
90
243
167
165
150
159
119
162
187
164
203
161
176
85
127
153
0
109
54
91
163
139
124
137
121
153
113
148
66
221
179
166
174
7
188
61
41
149
244
148
92
145
166
152
197
85
108
165
150
99
153
185
142
105
163
67
191
94
156
156
157
146
161
132
112
161
99
105
27
97
151
131
166
135
163
116
157
111
145
162
163
145
124
259
59
131
187
151
64
64
44
109
153
147
90
105
83
116
42
116
148
168
73
74
155
125
0
56
116
30
128
138
114
0
77
49
9
57
96
74
164
177
69
162
99
21
151
202
186
66
183
153
214
163
75
120
188
188
160
104
177
126
158
124
60
76
99
157
139
78
162
249
93
186
108
159
74
49
96
0
110
134
0
13
4
108
101
80
96
60
116
158
87
132
97
77
113
90
63
112
127
82
39
84
106
80
136
42
74
90
101
91
133
77
74
77
95
114
140
95
86
NA
55
48
98
54
147
121
126
113
54
98
95
110
28
70
73
56
139
89
88
90
85
102
86
NA
34
130
96
0
102
100
4
76
80
65
24
NA
117
20
65
94
68
94
52
98
92
89
115
3
101
64
77
32
4
79
118
123
59
51
7
99
52
56
97
66
Dataseries Y:
7,5
2,5
6,0
8,0
2,5
3,0
5,5
NA
1,0
6,5
2,5
1,0
1,5
1,0
5,5
3,5
5,5
8,5
6,5
6,5
2,0
5,5
4,5
2,0
0,0
2,0
5,0
1,0
0,5
5,0
4,0
2,0
4,0
2,5
0,0
5,0
6,5
NA
5,5
NA
4,0
2,5
5,0
5,5
2,0
3,5
3,0
4,0
0,5
3,0
6,5
3,0
4,5
4,0
4,5
3,0
0,0
7,5
NA
NA
5,5
4,0
7,5
7,0
5,5
2,5
4,5
7,0
3,5
4,0
2,0
4,0
0,0
5,5
5,0
4,0
2,0
3,0
0,0
1,0
2,5
5,5
6,0
3,0
0,5
5,5
3,5
NA
2,5
NA
4,5
NA
4,5
4,5
6,0
2,5
2,0
7,5
2,5
5,0
0,0
5,0
6,5
5,0
6,5
6,0
5,5
6,0
5,0
4,5
5,5
3,5
NA
4,0
5,5
7,0
5,0
1,0
7,5
6,0
5,0
1,0
7,0
5,0
5,5
3,5
2,5
6,5
7,0
NA
0,0
4,5
6,0
0,0
8,5
5,0
NA
NA
3,5
NA
0,0
7,5
6,0
3,5
0,5
5,5
6,0
1,5
NA
5,5
9,0
3,5
3,5
4,0
5,0
6,5
6,0
1,5
0,5
7,5
4,5
5,0
6,0
5,0
5,5
6,0
NA
1,5
3,5
7,5
1,0
6,5
NA
6,5
1,5
0,5
4,0
6,5
7,0
3,5
NA
2,5
NA
1,5
3,0
NA
NA
NA
4,0
2,5
4,0
4,0
2,5
7,5
5,5
4,5
4,0
0,0
0,0
2,5
4,0
1,0
4,5
3,5
0,5
3,0
6,0
5,5
5,0
6,0
0,0
4,5
3,5
3,0
2,5
7,5
5,5
7,0
3,5
3,0
0,0
4,5
3,0
0,0
NA
3,0
5,0
1,5
4,5
0,0
3,5
2,5
6,0
1,0
5,5
8,0
1,0
0,0
5,0
0,5
6,0
5,0
1,5
3,5
2,0
1,5
4,5
3,0
NA
5,5
3,0
8,0
0,0
2,5
7,0
NA
2,5
6,0
2,5
0,0
NA
6,0
0,0
2,5
5,5
1,0
0,0
1,0
3,5
1,5
5,0
7,0
NA
5,0
3,5
3,5
NA
0,0
4,0
5,5
4,0
0,0
2,0
1,5
5,5
NA
5,5
3,0
3,0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=172180&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=172180&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=172180&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'Herman Ole Andreas Wold' @ wold.wessa.net







Bandwidth
x axis11.6507301375024
y axis0.675992324698476
Correlation
correlation used in KDE0.275549233876586
correlation(x,y)0.275549233876586

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 11.6507301375024 \tabularnewline
y axis & 0.675992324698476 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.275549233876586 \tabularnewline
correlation(x,y) & 0.275549233876586 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=172180&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]11.6507301375024[/C][/ROW]
[ROW][C]y axis[/C][C]0.675992324698476[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.275549233876586[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.275549233876586[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=172180&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=172180&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 axis11.6507301375024
y axis0.675992324698476
Correlation
correlation used in KDE0.275549233876586
correlation(x,y)0.275549233876586



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ; par8 = terrain.colors ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ; par8 = terrain.colors ;
R code (references can be found in the software module):
par8 <- 'terrain.colors'
par7 <- 'Y'
par6 <- 'Y'
par5 <- '0'
par4 <- '0'
par3 <- '0'
par2 <- '50'
par1 <- '50'
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
par4 <- as(par4,'numeric')
par5 <- as(par5,'numeric')
library('GenKern')
x <- x[!is.na(y)]
y <- y[!is.na(y)]
y <- y[!is.na(x)]
x <- x[!is.na(x)]
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
if (par8 == 'terrain.colors') mycol <- terrain.colors(100)
if (par8 == 'rainbow') mycol <- rainbow(100)
if (par8 == 'heat.colors') mycol <- heat.colors(100)
if (par8 == 'topo.colors') mycol <- topo.colors(100)
if (par8 == 'cm.colors') mycol <- cm.colors(100)
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=mycol, axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$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')