interpmarglcd: Finds marginals of multivariate logconcave maximum likelihood...

In LogConcDEAD: Log-Concave Density Estimation in Arbitrary Dimensions

Finds marginals of multivariate logconcave maximum likelihood estimators by integrating

Description

Integrates the maximum likelihood estimator of multivariate data over an appropriate subspace to produce axis-aligned marginals for use in plot.LogConcDEAD.

Usage

interpmarglcd(lcd, marg=1, gridlen=100)

Arguments

lcd	Output from mlelcd (of class "LogConcDEAD")
marg	An (integer) scalar indicating which margin is required
gridlen	An (integer) scalar indicating the size of the grid

Details

Given a multivariate log-concave maximum likelihood estimator in the form of an object of class "LogConcDEAD" and a margin marg, this function will compute the marginal density estimate \hat{f}_{n, \textrm{\tiny{marg}}}. The estimate is evaluated at gridlen equally spaced points in the range where the density estimate is nonzero. These points are given in the vector xo.

\hat{f}_{n, \textrm{\tiny{marg}}} is evaluated by integrating the log-concave maximum likelihood estimator \hat{f}_n over the other components. The marginal density is zero outside the range of xo.

For examples, see mlelcd.

Value

xo	Vector of values at which the marginal density is estimate is computed.
marg	Vector of values of the integrated maximum likelihood estimator at the locations xo

Author(s)

Madeleine Cule

Robert Gramacy

Richard Samworth

See Also

dmarglcd, mlelcd

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