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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 12:01:46 -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/t1226430144omodpu93z5bsgqn.htm/, Retrieved Sun, 19 May 2024 09:37:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23837, Retrieved Sun, 19 May 2024 09:37:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

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] [Q1 bivariate dens...] [2008-11-10 13:19:59] [c5a66f1c8528a963efc2b82a8519f117]
F    D  [Bivariate Kernel Density Estimation] [q1 bivariate density] [2008-11-10 14:09:47] [c5a66f1c8528a963efc2b82a8519f117]
F           [Bivariate Kernel Density Estimation] [Q1] [2008-11-11 19:01:46] [5f3e73ccf1ddc75508eed47fa51813d3] [Current]
F RMPD        [Partial Correlation] [Q1 - Partial] [2008-11-11 19:08:58] [a0d819c22534897f04a2f0b92f1eb36a]
Feedback Forum
2008-11-24 17:01:46 [Stefanie Mertens] [reply] 
je hebt de juiste berekening gemaakt en een goede conclusie gegeven.
ik wou er nog aan toevoegen dat de kleuren in de grafiek duiden op de sterkte van de correlatie. Het rode duidt op een heel sterke correlatie en de gele kleur geeft een heel lage correlatie weer. in jouw grafiek is duidelijk te zien dat er een sterke positieve correlatie is tussen de twee variabelen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1515
1510
1225
1577
1417
1224
1693
1633
1639
1914
1586
1552
2081
1500
1437
1470
1849
1387
1592
1589
1798
1935
1887
2027
2080
1556
1682
1785
1869
1781
2082
2570
1862
1936
1504
1765
1607
1577
1493
1615
1700
1335
1523
1623
1540
1637
1524
1419
1821
1593
1357
1263
1750
1405
1393
1639
1679
1551
1744
1429
1784
Dataseries Y:
Download CSV
Histogram 
2718
2646
2551
2712
2606
2365
3533
3509
2912
3599
2719
2869
4085
2686
2545
3071
3388
2652
3190
2884
3295
3818
3226
3953
3810
2877
3515
3708
3450
3360
4110
4384
3729
4263
3505
3674
3911
2951
3317
3417
3498
2768
2899
3179
3011
3481
3015
2606
3530
2827
3120
2557
3645
2865
2587
2887
3429
2956
3098
2934
3269

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23837&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23837&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23837&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Bandwidth
x axis95.064371101708
y axis197.461425733098
Correlation
correlation used in KDE0.843223298829926
correlation(x,y)0.843223298829926

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 95.064371101708 \tabularnewline
y axis & 197.461425733098 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.843223298829926 \tabularnewline
correlation(x,y) & 0.843223298829926 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23837&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]95.064371101708[/C][/ROW]
[ROW][C]y axis[/C][C]197.461425733098[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.843223298829926[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.843223298829926[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23837&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23837&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 axis95.064371101708
y axis197.461425733098
Correlation
correlation used in KDE0.843223298829926
correlation(x,y)0.843223298829926


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 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')