rBP: Generate random values from a beta-Poisson model

In nghiavtr/BPSC: Beta-Poisson Model for Single-Cell RNA-seq Data Analyses

Description

Generate random values from a beta-Poisson model

Usage

rBP(n, alp, bet, lam1 = 1, lam2 = 1, prob0 = 0)

Arguments

n	The number of random data points
alp	A non-negative value, the parameter of Beta function (alpha)
bet	A non-negative value, the parameter of Beta function (beta)
lam1	A non-negative value, the parameter for scaling
lam2	A non-negative value, the parameter for smoothing, used for BP4 or BP5
prob0	A non-negative value in [0;1), the parameter for the portion of fixed density of zero in the distribution, used for BP5

Value

A vector of the generated data points

Examples

set.seed(2015)
#BP3
bp.vec=rBP(100,0.2,1.5,200)
hist(bp.vec, prob=TRUE)
#BP4
bp.vec=rBP(100,0.6,1.5,20,0.05)
hist(bp.vec, prob=TRUE)
#BP5
bp.vec=rBP(100,0.2,1.5,200,0.1,0.05)
hist(bp.vec, prob=TRUE)

nghiavtr/BPSC documentation built on May 23, 2019, 4:42 p.m.