kde_d {rlcv}

Multivariate kernel density

Description

Multivariate kernel density

Usage

kde_d(x.obs, x.new = NULL, h, stud = FALSE)

Arguments

x.obs

Training (observed) data (n1 by d matrix, d>=2)

x.new

Evaluation data (n2 by d matrix, d>=2); default to x.obs

h

Bandwidth (d vector)

stud

Indicator for whether data are studentized; default to FALSE

Details

For multivariate distributions, bandwidth is calculated for studentized data.

Value

Density evaluated at x.new

Author(s)

Ximing Wu [e-mail]

References

Wu, Ximing (2019), "Robust Likelihood Cross Validation for Kernel Density Estimation," Journal of Business and Economic Statistics, 37(4): 761-770.

Examples

x=matrix(rnorm(200),ncol=2)
x.new=matrix(rnorm(100),ncol=2)
h=c(1,1)
f=kde_d(x.new=x.new,x.obs=x,h=h)