# hatA: Compute the smoothing matrix of the smoothed log-concave... In LogConcDEAD: Log-Concave Density Estimation in Arbitrary Dimensions

## Description

This function computes the matrix \hat{A} of the smoothed log-concave maximum likelihood estimator

## Usage

 1 hatA(lcd) 

## Arguments

 lcd Object of class "LogConcDEAD" (typically output from mlelcd)

## Details

This function evaluates the the matrix \hat{A} of the smoothed log-concave maximum likelihood estimator, which is positive definite, and equals the difference between the sample covariance matrix and the covariance matrix of the fitted log-concave maximum likelihood density estimator.

For examples, see mlelcd

## Value

A matrix equals \hat{A} of the smoothed log-concave maximum likelihood estimator

## Note

Details of the computational aspects can be found in Chen and Samworth (2011).

Yining Chen

Robert Gramacy

Richard Samworth

## References

Chen, Y. and Samworth, R. J. (2013) Smoothed log-concave maximum likelihood estimation with applications Statist. Sinica, 23, 1373-1398. http://arxiv.org/abs/1102.1191v4

cov.LogConcDEAD