hatA: Compute the smoothing matrix of the smoothed log-concave...

In LogConcDEAD: Log-Concave Density Estimation in Arbitrary Dimensions

Compute the smoothing matrix of the smoothed log-concave maximum likelihood estimator

Description

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

Usage

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).

Author(s)

Yining Chen

Madeleine Cule

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. https://arxiv.org/abs/1102.1191v4

See Also

cov.LogConcDEAD

LogConcDEAD documentation built on April 6, 2023, 1:11 a.m.