bvdist-norm2d | R Documentation |
Density, distribution function, and random generation for the bivariate normal distribution.
dnorm2d(x, y, rho = 0)
pnorm2d(x, y, rho = 0)
rnorm2d(n, rho = 0)
x, y |
two numeric vectors defining the x and y coordinates. |
n |
the number of random deviates to be generated, an integer value. |
rho |
the correlation parameter, a numeric value ranging between minus one and one, by default zero. |
pnorm2d
returns a two column matrix of probabilities for the bivariate
normal distribution function.
dnorm2d
returns a two column matrix of densities for the bivariate
normal distribution function.
rnorm2d
returns a two column matrix of random deviates generated from
the bivariate normal distribution function.
Adelchi Azzalini for the underlying pnorm2d
function,
Diethelm Wuertz for the Rmetrics R-port.
Azzalini A., (2004); The sn Package; R Reference Guide available from www.r-project.org.
Venables W.N., Ripley B.D., (2002); Modern Applied Statistics with S, Fourth Edition, Springer.
## dnorm2d -
# Bivariate Normal Density:
x <- (-40:40)/10
X <- grid2d(x)
z <- dnorm2d(X$x, X$y, rho = 0.5)
ZD <- list(x = x, y = x, z = matrix(z, ncol = length(x)))
# Perspective Density Plot:
persp(ZD, theta = -40, phi = 30, col = "steelblue")
# Contour Density Plot:
contour(ZD, main="Bivariate Normal Density")
## pnorm2d -
# Bivariate Normal Probability:
z <- pnorm2d(X$x, X$y, rho = 0.5)
ZP <- list(x = x, y = x, z = matrix(z, ncol = length(x)))
# Perspective Plot:
persp(ZP, theta = -40, phi = 30, col = "steelblue")
# Contour Plot:
contour(ZP)
## rnorm2d -
# Bivariate Normal Random Deviates
r <- rnorm2d(5000, rho=0.5)
# Scatter Plot:
plot(r, col="steelblue", pch=19, cex=0.5)
contour(ZD, add=TRUE, lwd=2, col="red")
# Hexagonal Binning:
plot(hexBinning(r))
contour(ZD, add=TRUE, lwd=2, col="black")
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