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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 computationTue, 11 Nov 2008 08:01:49 -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/2008/Nov/11/t12264158126j7jvfd4yzb1jf4.htm/, Retrieved Mon, 27 May 2024 21:58:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23563, Retrieved Mon, 27 May 2024 21:58:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Bivariate Kernel Density Estimation] [] [2008-11-11 15:01:49] [c0a347e3519123f7eef62b705326dad9] [Current]
F RMPD    [Partial Correlation] [] [2008-11-11 15:17:50] [29747f79f5beb5b2516e1271770ecb47]
F RMPD      [Trivariate Scatterplots] [] [2008-11-11 15:21:20] [29747f79f5beb5b2516e1271770ecb47]
F RMPD        [Hierarchical Clustering] [] [2008-11-11 15:27:51] [29747f79f5beb5b2516e1271770ecb47]
F RMPD        [Box-Cox Linearity Plot] [] [2008-11-11 15:33:03] [29747f79f5beb5b2516e1271770ecb47]
F RMPD        [Testing Mean with known Variance - Critical Value] [] [2008-11-11 16:11:09] [29747f79f5beb5b2516e1271770ecb47]
F RM            [Testing Mean with known Variance - p-value] [] [2008-11-11 16:21:44] [29747f79f5beb5b2516e1271770ecb47]
F RMP           [Testing Mean with known Variance - Type II Error] [] [2008-11-11 16:29:04] [29747f79f5beb5b2516e1271770ecb47]
- RMP           [Testing Mean with known Variance - Sample Size] [] [2008-11-11 16:34:38] [29747f79f5beb5b2516e1271770ecb47]
F                 [Testing Mean with known Variance - Sample Size] [] [2008-11-11 16:40:41] [29747f79f5beb5b2516e1271770ecb47]
F RM              [Testing Population Mean with known Variance - Confidence Interval] [] [2008-11-11 17:00:42] [29747f79f5beb5b2516e1271770ecb47]
F RM              [Testing Sample Mean with known Variance - Confidence Interval] [] [2008-11-11 17:05:19] [29747f79f5beb5b2516e1271770ecb47]
Feedback Forum
2008-11-24 17:50:40 [Jan Cavents] [reply] 
hier worden de verbanden grafisch weergegeven, liggen de punten dicht bij elkaar, dan zijn de verbanden groot, liggen ze verder van elkaar dan is er minder sprake van een verband.
2008-11-24 19:19:31 [Dorien Peeters] [reply] 
Hier zien we dat de verbanden grafisch worden weergegeven. Deze punten zeggen iets over de dichtheid, betrouwbaarheidsinterval. Hoe dichter de punten bij elkaar liggen, hoe sterker het verband is tussen de variabelen. Hier kunnen we toch spreken van een tamelijk sterk verband tussen de variabelen, op een paar punten na die ver van de rechte liggen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,6
96,9
105,6
102,8
101,7
104,2
92,7
91,9
106,5
112,3
102,8
96,5
101,0
98,9
105,1
103,0
99,0
104,3
94,6
90,4
108,9
111,4
100,8
102,5
98,2
98,7
113,3
104,6
99,3
111,8
97,3
97,7
115,6
111,9
107,0
107,1
100,6
99,2
108,4
103,0
99,8
115,0
90,8
95,9
114,4
108,2
112,6
109,1
105,0
105,0
118,5
103,7
112,5
116,6
96,6
101,9
116,5
119,3
115,4
108,5
111,5
108,8
121,8
109,6
112,2
119,6
104,1
105,3
115,0
124,1
116,8
107,5
115,6
116,2
116,3
119,0
111,9
118,6
106,7
Dataseries Y:
Download CSV
Histogram 
9,1
9,0
8,6
7,9
7,7
7,8
9,1
9,4
9,3
8,7
8,4
8,6
9,0
9,1
8,7
8,2
7,9
7,9
9,1
9,4
9,5
9,1
9,0
9,3
9,9
9,8
9,4
8,3
8,0
8,5
10,4
11,1
10,9
9,9
9,2
9,2
9,5
9,6
9,5
9,1
8,9
9,0
10,1
10,3
10,2
9,6
9,2
9,3
9,4
9,4
9,2
9,0
9,0
9,0
9,8
10,0
9,9
9,3
9,0
9,0
9,1
9,1
9,1
9,2
8,8
8,3
8,4
8,1
7,8
7,9
7,9
8,0
7,9
7,5
7,2
6,9
6,6
6,7
7,3

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'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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23563&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23563&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23563&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Bandwidth
x axis3.82821580785849
y axis0.235316323816059
Correlation
correlation used in KDE-0.315312508878959
correlation(x,y)-0.315312508878959

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.82821580785849 \tabularnewline
y axis & 0.235316323816059 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.315312508878959 \tabularnewline
correlation(x,y) & -0.315312508878959 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23563&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.82821580785849[/C][/ROW]
[ROW][C]y axis[/C][C]0.235316323816059[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.315312508878959[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.315312508878959[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23563&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23563&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 axis3.82821580785849
y axis0.235316323816059
Correlation
correlation used in KDE-0.315312508878959
correlation(x,y)-0.315312508878959


Figures (Output of Computation)

Input Parameters & R Code

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')