FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

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 computationMon, 02 Nov 2009 22:54:51 +0100
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/02/t12571989135aw7kpuvy6skzuf.htm/, Retrieved Mon, 12 May 2025 20:14:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53021, Retrieved Mon, 12 May 2025 20:14:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact610

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [3/11/2009] [2009-11-02 21:54:51] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
-   PD    [Bivariate Kernel Density Estimation] [] [2009-11-03 21:01:32] [74be16979710d4c4e7c6647856088456]
- R PD    [Bivariate Kernel Density Estimation] [bivariate kendall...] [2009-11-04 15:27:00] [757146c69eaf0537be37c7b0c18216d8]
-   PD    [Bivariate Kernel Density Estimation] [] [2009-11-04 15:32:31] [8d2349dc1d6314bc274adc9ad027c980]
-   PD    [Bivariate Kernel Density Estimation] [] [2009-11-04 15:34:54] [4d62210f0915d3a20cbf115865da7cd4]
-   PD    [Bivariate Kernel Density Estimation] [ws 6 bp] [2009-11-04 22:24:45] [6e4e01d7eb22a9f33d58ebb35753a195]
-   PD    [Bivariate Kernel Density Estimation] [bivariate kernel ...] [2009-11-05 10:35:10] [cd6314e7e707a6546bd4604c9d1f2b69]
-    D    [Bivariate Kernel Density Estimation] [WS 6 Bivariate Ke...] [2009-11-05 10:43:11] [b103a1dc147def8132c7f643ad8c8f84]
-   PD    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-11-05 12:01:19] [4395c69e961f9a13a0559fd2f0a72538]
-   PD    [Bivariate Kernel Density Estimation] [Workshop 6] [2009-11-05 12:21:06] [03557919bc1ce1475f4920f6a43c36b0]
-   PD    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-11-05 12:32:59] [f5d341d4bbba73282fc6e80153a6d315]
-    D      [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-11-10 11:39:02] [f5d341d4bbba73282fc6e80153a6d315]
-             [Bivariate Kernel Density Estimation] [tg10] [2009-11-10 14:36:57] [a21bac9c8d3d56fdec8be4e719e2c7ed]
- R             [Bivariate Kernel Density Estimation] [ws6] [2009-11-15 22:32:43] [3fc64fd7a52ce121dfe13dba27bf6e5b]
-               [Bivariate Kernel Density Estimation] [PA10] [2009-12-15 10:12:22] [a21bac9c8d3d56fdec8be4e719e2c7ed]
-             [Bivariate Kernel Density Estimation] [tvd10] [2009-11-10 15:02:31] [42ad1186d39724f834063794eac7cea3]
-   PD        [Bivariate Kernel Density Estimation] [WS6 Biv Kernel De...] [2009-11-12 16:28:52] [445b292c553470d9fed8bc2796fd3a00]
-   PD    [Bivariate Kernel Density Estimation] [shwws6vr1] [2009-11-05 13:58:58] [2b2cfeea2f5ac2a1bcb842baaf1415ef]
-   PD    [Bivariate Kernel Density Estimation] [Shwws6v1] [2009-11-05 13:58:47] [5f89c040fdf1f8599c99d7f78a662321]
-   PD    [Bivariate Kernel Density Estimation] [bivariate kernel ...] [2009-11-05 15:29:28] [eaf42bcf5162b5692bb3c7f9d4636222]
-    D    [Bivariate Kernel Density Estimation] [shw6: Bivariate K...] [2009-11-05 18:47:08] [3c8b83428ce260cd44df892bb7619588]
-   PD    [Bivariate Kernel Density Estimation] [ws6 bivariate ker...] [2009-11-06 12:52:23] [8b1aef4e7013bd33fbc2a5833375c5f5]
-           [Bivariate Kernel Density Estimation] [] [2009-11-11 10:26:25] [08fc5c07292c885b941f0cb515ce13f3]
-   PD    [Bivariate Kernel Density Estimation] [Workshop 6] [2009-11-06 13:45:23] [786e067c4f7cec17385c4742b96b6dfa]
-   PD    [Bivariate Kernel Density Estimation] [Workshop 6] [2009-11-06 13:48:01] [786e067c4f7cec17385c4742b96b6dfa]
-   PD    [Bivariate Kernel Density Estimation] [ws 6] [2009-11-06 20:08:14] [b5908418e3090fddbd22f5f0f774653d]
-    D    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-11-07 09:22:48] [3b0db66ac8145b1be856a517e2900332]
-   PD    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-11-07 13:52:27] [d46757a0a8c9b00540ab7e7e0c34bfc4]
-    D      [Bivariate Kernel Density Estimation] [Energiedragers-In...] [2009-12-19 18:36:48] [73863f7f907331e734eff34b7de6fc83]
-   PD    [Bivariate Kernel Density Estimation] [SHWWS6link9] [2009-11-08 10:07:33] [a66d3a79ef9e5308cd94a469bc5ca464]
-   PD    [Bivariate Kernel Density Estimation] [Workshop 6 Bivari...] [2009-11-08 11:58:08] [f924a0adda9c1905a1ba8f1c751261ff]
-   PD    [Bivariate Kernel Density Estimation] [SHW WS6 - Kernel ...] [2009-11-08 13:06:27] [253127ae8da904b75450fbd69fe4eb21]
-   PD    [Bivariate Kernel Density Estimation] [] [2009-11-08 16:11:26] [cf890101a20378422561610e0d41fd9c]
-    D    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-11-08 16:21:36] [e2a6b1b31bd881219e1879835b4c60d0]
-   PD    [Bivariate Kernel Density Estimation] [] [2009-11-08 20:07:26] [badc6a9acdc45286bea7f74742e15a21]
-   PD    [Bivariate Kernel Density Estimation] [] [2009-11-09 08:32:40] [2c5be225250d91402426bbbf07a5e2b3]
-   PD    [Bivariate Kernel Density Estimation] [WS 6 Bivariate Ke...] [2009-11-09 09:26:35] [83058a88a37d754675a5cd22dab372fc]
-    D    [Bivariate Kernel Density Estimation] [Workshop 6 - 7.1] [2009-11-09 09:38:36] [f1a50df816abcbb519e7637ff6b72fa0]
-    D    [Bivariate Kernel Density Estimation] [workshop 6 - 7.2] [2009-11-09 09:40:35] [f1a50df816abcbb519e7637ff6b72fa0]
-    D    [Bivariate Kernel Density Estimation] [workshop 6 - 7.3] [2009-11-09 09:42:07] [f1a50df816abcbb519e7637ff6b72fa0]
-    D    [Bivariate Kernel Density Estimation] [workshop 6 - 7.4] [2009-11-09 09:43:50] [f1a50df816abcbb519e7637ff6b72fa0]
-   PD    [Bivariate Kernel Density Estimation] [Workshop 6] [2009-11-09 09:44:01] [3e19a07d230ba260a720e0e03e0f40f2]
- R  D      [Bivariate Kernel Density Estimation] [WS6] [2009-11-14 15:43:15] [9f35ad889e41dd0c9322ca60d75b9f47]
-    D    [Bivariate Kernel Density Estimation] [workshop 6 - 7.5] [2009-11-09 09:45:35] [f1a50df816abcbb519e7637ff6b72fa0]
-    D    [Bivariate Kernel Density Estimation] [workshop 6 - 7.6] [2009-11-09 09:47:04] [f1a50df816abcbb519e7637ff6b72fa0]
-   PD    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-11-09 10:22:31] [134dc66689e3d457a82860db6471d419]
-   PD    [Bivariate Kernel Density Estimation] [WS 6 bivariate ] [2009-11-09 12:38:55] [830e13ac5e5ac1e5b21c6af0c149b21d]
-   PD    [Bivariate Kernel Density Estimation] [WS 6: Bivariate K...] [2009-11-09 12:44:15] [74be16979710d4c4e7c6647856088456]
-   PD    [Bivariate Kernel Density Estimation] [] [2009-11-09 18:15:08] [ee35698a38947a6c6c039b1e3deafc05]

[Truncated]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.40
96.40
101.90
106.20
81.00
94.70
101.00
109.40
102.30
90.70
96.20
96.10
106.00
103.10
102.00
104.70
86.00
92.10
106.90
112.60
101.70
92.00
97.40
97.00
105.40
102.70
98.10
104.50
87.40
89.90
109.80
111.70
98.60
96.90
95.10
97.00
112.70
102.90
97.40
111.40
87.40
96.80
114.10
110.30
103.90
101.60
94.60
95.90
104.70
102.80
98.10
113.90
80.90
95.70
113.20
105.90
108.80
102.30
99.00
100.70
115.50
Dataseries Y:
Download CSV
Histogram 
109.20
88.60
94.30
98.30
86.40
80.60
104.10
108.20
93.40
71.90
94.10
94.90
96.40
91.10
84.40
86.40
88.00
75.10
109.70
103.00
82.10
68.00
96.40
94.30
90.00
88.00
76.10
82.50
81.40
66.50
97.20
94.10
80.70
70.50
87.80
89.50
99.60
84.20
75.10
92.00
80.80
73.10
99.80
90.00
83.10
72.40
78.80
87.30
91.00
80.10
73.60
86.40
74.50
71.20
92.40
81.50
85.30
69.90
84.20
90.70
100.30

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53021&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]3 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=53021&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53021&T=0

As an alternative you can also use a QR Code:  
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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Bandwidth
x axis3.51003377176526
y axis5.14633268825879
Correlation
correlation used in KDE0.565259717157914
correlation(x,y)0.565259717157914

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.51003377176526 \tabularnewline
y axis & 5.14633268825879 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.565259717157914 \tabularnewline
correlation(x,y) & 0.565259717157914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53021&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.51003377176526[/C][/ROW]
[ROW][C]y axis[/C][C]5.14633268825879[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.565259717157914[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.565259717157914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53021&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53021&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Bandwidth
x axis3.51003377176526
y axis5.14633268825879
Correlation
correlation used in KDE0.565259717157914
correlation(x,y)0.565259717157914


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')