genInits: Generate initialization for optimization

In corncob: Count Regression for Correlated Observations with the Beta-Binomial

Generate initialization for optimization

Description

Generate initialization for optimization

Usage

genInits(W, M, X, X_star, np, npstar, link, phi.link, nstart = 1, use = TRUE)

Arguments

W	Numeric vector of counts
M	Numeric vector of sequencing depth
X	Matrix of covariates associated with abundance (including intercept)
X_star	Matrix of covariates associated with dispersion (including intercept)
np	Number of covariates associated with abundance (including intercept)
npstar	Number of covariates associated with dispersion (including intercept)
link	ink function for abundance covariates
phi.link	ink function for dispersion covariates
nstart	Integer. Defaults to 1. Number of starts for optimization.
use	Boolean. Defaults to TRUE. Indicator of whether to use deterministic intialization.

Value

Matrix of initializations

Examples

set.seed(1)
seq_depth <- rpois(20, lambda = 10000)
my_counts <- rbinom(20, size = seq_depth, prob = 0.001) * 10
my_covariate <- cbind(rep(c(0,1), each = 10))
colnames(my_covariate) <- c("X1")

genInits(W = my_counts, M = seq_depth,
       X = cbind(1, my_covariate), X_star = cbind(1, my_covariate),
       np = 2, npstar = 2,
       link = "logit",
       phi.link = "logit", nstart = 2, use = TRUE)

corncob documentation built on May 29, 2024, 7:15 a.m.