correctIntegral: Normalizes Log-Concave Density

In fmlogcondens: Fast Multivariate Log-Concave Density Estimation

Description

correctIntegral normalizes a log-concave density parametrized by a set of hyperplane parameters. Works by calculating y = log(f(x)) for each data point in X, normalizing y, and then recalculating a and b.

Usage

correctIntegral(X, mu, a, b, cvh)

Arguments

X	Set of data points (one sample per row)
mu	Mean vector of X that gets added back to X
a	Matrix where rows are hyperplane normals
b	Vector where entries are intercepts of hyperplanes
cvh	Matrix where each row is a set of indices of points in X describing one face of conv(X)

Value

Normalized hyperplane parameters (for the uncentered X <- X + mu)

a, b	Hyperplane parameters of the normalized density.
y	Vector with values y_i = log(f(X_)) of the normalized density.
aSparse, bSparse	Input hyperplane parameters.

Examples

# draw samples from normal distribution
X <- matrix(rnorm(200),100,2) 
# calculate parameters of convex hull of X
r <- calcCvxHullFaces(X)
# draw random parameters of 10 hyperplanes
a <- matrix(runif(10*2),10,2)
b <- runif(10)

# calculate parameters of convex hull of X
params <- correctIntegral(X,rep(0,2),a,b,r$cvh)

fmlogcondens documentation built on May 2, 2019, 8:29 a.m.