linconGauss: Sample Gaussian distribution with linear constraints Taking... In linconGaussR: Sampling Multivariate Normal Distribution under Linear Constraints

Description

Sample Gaussian distribution with linear constraints Taking truncated sample of Gaussian distribution over a linear constraint domain.

Usage

 1 2 3 4 5 6 7 8 9 10 11 linconGauss( n, A, b, Sigma, mu, x_init = NULL, intersection = TRUE, n_retry_init = 1000, nskp = 5 )

Arguments

 n number of samples to take A a matrix with M by D dimensions, the linear constraints, such that Ax+b>=0 b the offset of the linear constraints with dimension M such that Ax+b>=0 Sigma covariance matrix of the Gaussian mu mean vector of the Gaussian x_init the sample to start with, if NULL, a sample will be drawn using rejection method intersection bool whether sample from the intersection or the union of the linear constraints, default true, sample from the intersection n_retry_init how many times to try finding a initial value nskp how many sample to skip during the sampling routine

Value

a matrix with truncated sample, row as samples

Examples

 1 2 3 4 5 6 my_sample <- linconGauss(100, diag(2),c(0,0),diag(2),c(0,0)) MASS_sample <- MASS::mvrnorm(1000,c(0,0),diag(2)) plot(MASS_sample) points(my_sample,col = "red") abline(h=0) abline(v=0)

linconGaussR documentation built on Oct. 26, 2021, 5:06 p.m.