normal.mixture: Normal Mixture Model

In ArnaudDroitLab/RJMCMC: Bayesian hierarchical model for genome-wide profiling of nucleosome positions based on high-throughput short-read data (MNase-Seq data)

Description

Generation a value from a Normal Mixture distribution.

Usage

normal.mixture(i, k, weight, mu, sigma)

Arguments

i	a integer, a count parameter.
k	a positive integer value, the number of nucleosomes in the analyzed region.
weight	a vector of length k, the weight for each nucleosome. The sum of all weight values must be equal to 1. The length of weight must be equal to k.
mu	a vector of positive integer of length k, the positions of all the nucleosomes in the analyzed region. The length of weight must be equal to k.
sigma	a vector of length k, the variance for each nucleosome. The length of sigma must be equal to k.

Value

a numerical, the value generated from a Normal Mixture distribution.

Author(s)

Rawane Samb, Astrid Deschenes

Examples

## Return a value generated from a normal mixture
RJMCMC:::normal.mixture(i = 1L, k = 4L, weight = c(0.2, 0.3, 0.24, 0.26),
mu = c(12L, 15L, 25L, 44L), sigma = c(4, 7, 6, 5))

ArnaudDroitLab/RJMCMC documentation built on May 5, 2019, 7:06 a.m.