nkden {funfits}R Documentation

Normal kernel density estimate

Usage

nkden(data, bandwidth, n.points, grid)

Arguments

data A vector or matrix of oberservations. Rows are considerd to be independent random samples from a continous distribution.
bandwidth The bandwidht for the kernels estimates in the scale of standard deviation for the normal density.
n.points Number of equally spaced points to evaluate a univariate density estimate.
grid A vector or matrix of values to evaluate the estimate.The defautl is to use the data.

Value

A list where x is the points used for evaluation, y the density estimates at these points and bandwidths and h the vector of bandwidths. If more than one bandwidth is given then the estimates are arranged as columns in the matrix y.

See Also

nkreg, nkden.cv, ksmooth

Examples


# univariate estimate with several bandwidths

nkden( minitri$swim, c(2.0,4.0,6.0),n.points=150)-> look 
matplot( look$x, look$y, type="l") # plot all of them togther



# a bivariate estimate

nkden( minitri[,1:2], 2.0) -> look2
# create gridded surface from values at data points.

interp( look2$x[,1], look2$x[,2], look2$y) -> surface
persp(surface, xlab="swim", ylab="bike")


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