ickde: Interval-Censored Kernel Density Estimation

In ICE: Iterated Conditional Expectation

Description

Iterated conditional expectation kernel density estimation using a local constant. The bandwidth is assumed fixed. (See the example for a way to get a quick ballpark estimate of the bandwidth.) The gaussian, epanechnikov and biweight kernels can be used. Note that the bandwidth estimate would have to be adjusted before using with epanechnikov or biweight.

Usage

ickde(I, h, f, m, n.iterations = 10, x1, xm, right.limit = 10000,kernel="gaussian", old=TRUE)

Arguments

I	A matrix with two columns, consisting of left and right endpoints of the interval data
h	A scalar bandwidth
f	An initial estimate of the density at a sequence of grid points (optional; if this is used, do not specify m)
m	The number of (equally-spaced) grid points at which the density is to be estimated
n.iterations	The maximum number of iterations allowed
x1	The left-most grid point (optional)
xm	The right-most grid point (optional)
right.limit	For right-censored data, the value to be used as an artificial right endpoint for the intervals
kernel	character argument indicated choice of kernel; current choices are "gaussian", "epanechnikov", "biweight"
old	logical value, indicating whether denominators in conditional expectation calculation should use the previous value of the density estimate.

Value

An object of class IC

Author(s)

W.J. Braun

References

Braun, J., Duchesne, T. and Stafford, J.E. (2005) Local likelihood density estimation for interval censored data. Canadian Journal of Statistics 33: 39-60.

Examples

 tmp <- apply(ICHemophiliac, 1, mean)
 h <- try(dpik(tmp), silent=T) # dpik() will work if KernSmooth is loaded
 if (class(h) !="numeric" ) h <- .9  # this makes the example work 
                       # if KernSmooth is not loaded
 estimate <- ickde(ICHemophiliac, m=200, h=h)
 plot(estimate, type="l")

Example output

Loading required package: KernSmooth
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009

ICE documentation built on May 2, 2019, 3:03 a.m.