Usage
blvcm_bin(pheno, geno, model = 3, iter = 30000, burnin = 500, var = -1, lambda = 0.2,
cov = 0, init = c(0, 0))
Arguments
pheno
An $N$ x $3$ phenotypic data matrix (trait, family number, zyg=1 for MZ, 2 for DZ), where $N$ is the number of subjects. The trait must be 0 or 1.
geno
An $N$ x $K$ genotypic data matrix, where $N$ is the number of subjects and $K$ is the number of rare variants. The value can be 0 or 1. A missing genotype is represented by -9, which will be imputated by BLVCM based on HWE.
model
Twin model: 3 for ACE model, 2 for AE model, 1 for independent subjects
iter
The number of MCMC iterations (must be positive). The default value is 30000.
burnin
The number of burn-ins (must be positive). The default value is 500.
var
The variance hyperparameters (must be positive) in the priors for $\beta$ and $\gamma$. The default value is 1.
lambda
The threshold $\lambda$ (must be positive) for hypothesis test. The default value is 0.2.
cov
A matrix of other covariates to be adjusted.
init
Initial values for $\beta$ and $\gamma$. The default values are 0. The initial value for $\beta$ must be non-negative.