Draws samples from a log-concave maximum likelihood
estimate. The estimate should be specified in the form of an object of
class "LogConcDEAD", the result of a call to
mlelcd.
rlcd(n=1, lcd, method=c("Independent","MH"))A numeric matrix with nsample rows, each row corresponding to a point
in \(R^d\) drawn from the distribution with density defined by lcd.
A scalar integer indicating the number of samples required
Object of class "LogConcDEAD" (typically output from
mlelcd)
Indicator of the method used to draw samples, either via independent rejection sampling (default choice) or via Metropolis-Hastings
Yining Chen
Madeleine Cule
Robert Gramacy
Richard Samworth
This function by default uses a simple rejection sampling scheme to draw independent random samples from a log-concave maximum likelihood estimator. One can also use the Metropolis-Hastings option to draw (dependent) samples with a higher acceptance rate.
For examples, see mlelcd.
Cule, M. L., Samworth, R. J., and Stewart, M. I. (2010) Maximum likelihood estimation of a multi-dimensional log-concave density J. Roy. Statist. Soc., Ser. B. (with discussion), 72, 545-600.
Gopal, V. and Casella, G. (2010) Discussion of Maximum likelihood estimation of a log-concave density by Cule, Samworth and Stewart J. Roy. Statist. Soc., Ser. B., 72, 580-582.
mlelcd