# 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.