decon (version 1.3-4)

bw.dboot2: A bootstrap bandwidth selection with resampling

Description

To compute the optimal bandwidth using the bootstrap method with resampling.

Usage

bw.dboot2(y,sig,h0='dboot1',error='normal',B=1000,grid=100,ub=2)

Arguments

y

The observed data. It is a vector of length at least 3.

sig

The standard deviation(s) $\sigma$. For homoscedastic errors, $sig$ is a single value. Otherwise, $sig$ is a vector of variances having the same length as $y$.

h0

An initial bandwidth parameter. The default vaule is the estimate from bw.dboot1.

error

Error distribution types: 'normal', 'laplacian' for normal and Laplacian errors, respectively.

B

Bootstrap number, default value 1000.

grid

the grid number to search the optimal bandwidth when a bandwidth selector was specified in bw. Default value "grid=100".

ub

the upper boundary to search the optimal bandwidth, default value is "ub=2".

Value

the selected bandwidth.

Details

Three cases are supported: (1) homo normal; (2) homo laplacian.

The integration was approximated by computing the average over a fine grid of points (1000 points).

References

Wang, X.F. and Wang, B. (2011). Deconvolution estimation in measurement error models: The R package decon. Journal of Statistical Software, 39(10), 1-24.

See Also

bw.dnrd, bw.dmise, bw.dboot1.

Examples

# NOT RUN {
n <- 1000
x <- c(rnorm(n/2,-2,1),rnorm(n/2,2,1))
## the case of homoscedastic normal error
sig <- .8
u <- rnorm(n, sd=sig)
w <- x+u
bw.dboot2(w,sig=sig)
## the case of homoscedastic laplacian error
sig <- .8
## generate laplacian error
u <- ifelse(runif(n) > 0.5, 1, -1) * rexp(n,rate=1/sig)
w <- x+u
bw.dboot2(w,sig=sig,error='laplacian')

# }