plot.kdde | R Documentation |
Plot for kernel density derivative estimate for 1- to 3-dimensional data.
## S3 method for class 'kdde'
plot(x, ...)
x |
object of class |
... |
other graphics parameters:
and those used in |
For kdde
objects, the function headers for the different dimensional data are
## univariate plot(fhat, ylab="Density derivative function", cont=50, abs.cont, alpha=1, ...) ## bivariate plot(fhat, which.deriv.ind=1, cont=c(25,50,75), abs.cont, display="slice", zlab="Density derivative function", col, col.fun, alpha=1, kdde.flag=TRUE, thin=3, transf=1, neg.grad=FALSE, ...) ## trivariate plot(fhat, which.deriv.ind=1, display="plot3D", cont=c(25,50,75), abs.cont, colors, col, col.fun, ...)
Plots for 1-d and 2-d are sent to graphics window. Plot for 3-d is sent to graphics/RGL window.
In addition to the display options inherited from plot.kde
, the
first derivative has display="quiver"
. This is a quiver plot
where the size and direction of the arrow indicates the
magnitude/direction of the density gradient. See quiver
from
the pracma package for more details.
plot.kde
## univariate example
data(tempb)
fhat1 <- kdde(x=tempb[,"tmin"], deriv.order=1) ## gradient [df/dx, df/dy]
plot(fhat1, xlab="Min. temp.", col.cont=4) ## df/dx
points(20,predict(fhat1, x=20))
## bivariate example
fhat1 <- kdde(x=tempb[,c("tmin", "tmax")], deriv.order=1)
plot(fhat1, display="quiver")
## gradient [df/dx, df/dy]
fhat2 <- kdde(x=tempb[,c("tmin", "tmax")], deriv.order=2)
plot(fhat2, which.deriv.ind=2, display="persp", phi=10)
plot(fhat2, which.deriv.ind=2, display="filled.contour")
## d^2 f/(dx dy): blue=-ve, red=+ve
s2 <- kcurv(fhat2)
plot(s2, display="filled.contour", alpha=0.5, lwd=1)
## summary curvature
## trivariate example
data(iris)
fhat1 <- kdde(iris[,2:4], deriv.order=1)
plot(fhat1)
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