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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 computationWed, 09 Dec 2009 11:23:18 -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/2009/Dec/09/t1260383044um0bnbfrug3rqs9.htm/, Retrieved Mon, 29 Apr 2024 13:11:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65119, Retrieved Mon, 29 Apr 2024 13:11:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [cs.shw.paper.univ...] [2009-12-09 17:46:01] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Kernel Density Estimation] [cs.shw.paper.biva...] [2009-12-09 18:23:18] [47f146dd9fb230449e079c6cbc92f5f5] [Current]
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Dataseries X:
1213.8
1245.6
1306.3
1255.8
1257.6
1287.8
1300.4
1320.9
1370.8
1327.3
1320
1345.3
1346.7
1395.4
1462
1491.6
1461.8
1477.9
1490.3
1521.1
1561.9
1552.6
1523.6
1548.3
1552.4
1587
1621.3
1648.7
1641.8
1650.6
1688.6
1670.7
1682.2
1678.9
1650.6
1662.4
1664.5
1683.2
1736.2
1747.6
1749
1759.7
1793.6
1817.4
1858.4
1839.9
1809.1
1877.7
1880.3
1930.9
2039.3
1992.7
1987.8
1984.4
2016.5
2016.7
2064.1
2031.5
2000.3
2057.8
2041.2
2093.2
2158.3
2128.8
2131.9
2170.3
2190.8
2217.7
2254.4
2223.3
2210.5
2250.8
2249.1
2288.6
2329.2
2313.8
2309.8
2345.9
2361.3
2372
2410.4
2398.5
2362.3
2419.1
2421.6
2465
2480.5
2506.1
2506.6
2525.8
2550
2578.3
2807.8
2815.3
2767.7
2815.4
2838.8
2864
2948.6
2922.8
2917.2
2936.8
2993.4
3007.8
3046.3
3011.5
2958.6
3019.8
2998.5
3040.4
3166
3110
3099.2
3150.3
3163.6
3182.6
3244.4
3223.2
3143.6
3217
3182.3
3217.2
3262.5
3227.9
3171.6
3219
3195.4
3221.6
3262.1
3179.5
3133.6
3219.2
3245
3265.3
3312.5
3383.6
3386.3
3411.1
3467.2
3487.7
3575.5
3571.5
3582.3
3637.1
3685
Dataseries Y:
2430.47
2516.3
2633.63
2799.84
3001.93
3229.29
3173.02
3322.08
3417.88
3486.95
3016.22
2709.61
2914.87
3203.08
3320.25
3446.25
3456.85
3566.53
3763.67
3607.75
3747.38
3623.91
3699.76
3629.61
3911.52
4281.47
4742.42
4522.42
4879.79
5059.11
5093.19
4941.81
4832.67
4876.18
5018.07
4780.34
4953.59
4622.32
4557.13
4560.03
4105.66
4004.89
4277.26
4245.98
4057.64
3931.42
3637.15
3339.91
3465.74
3571.25
3706.93
3584.17
3552.11
3695.24
3510
3357.7
3060.91
2736.98
2709.45
2314.96
2561.29
2663.49
2407.87
2237.74
2165.44
2098.89
2318.54
2315.49
2395.47
2474.07
2479.57
2386.92
2537.84
2567.13
2660.37
2696.28
2748.5
2663.32
2707.69
2669.36
2687.68
2650.24
2620.03
2668.47
2692.06
2737.67
2774.77
2819.19
2892.56
2866.08
2817.41
2934.75
3036.54
3139.5
3114.31
3261.3
3201.79
3264.53
3349.1
3446.17
3469.48
3507.13
3536.2
3359.05
3378.85
3449.15
3522.89
3551.04
3669.15
3602
3697.22
3760.9
3665.08
3708.8
3858.21
3933.16
3946.98
3794.29
3765.56
3820.33
3885.12
3752.67
3683.79
3240.75
3188.82
3017.98
3237.2
3182.53
2906.42
2881.35
2915.64
2635.13
2331.43
2159.04
2065.46
1983.48
1770.41
1815.99
2026.97
2124.81
2098.28
2291.39
2401.57
2453.89
2409.53




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65119&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]1 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=65119&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65119&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis175.869749449568
y axis214.944991560437
Correlation
correlation used in KDE-0.345471020666261
correlation(x,y)-0.345471020666261

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 175.869749449568 \tabularnewline
y axis & 214.944991560437 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.345471020666261 \tabularnewline
correlation(x,y) & -0.345471020666261 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65119&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]175.869749449568[/C][/ROW]
[ROW][C]y axis[/C][C]214.944991560437[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.345471020666261[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.345471020666261[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65119&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65119&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 axis175.869749449568
y axis214.944991560437
Correlation
correlation used in KDE-0.345471020666261
correlation(x,y)-0.345471020666261



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')