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

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

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.