Title Pearson-Aitken algorithm to calculate mean values in truncated multivariate normal distributions

Title Pearson-Aitken algorithm to calculate mean values in truncated multivariate normal distributions

Usage

PA_algorithm(mu, covmat, target_id, lower, upper, K_i = NA, K_pop = NA)

Arguments

mu

vector of means

covmat

covariance matrix, contaning kinship coefficient and heritability on each entry (except diagnoal, which is 1 for full liabilities and h2 for genetic liabilities)

target_id

ID of target individual (or genetic liability), i.e. rowname in covmat to return expected genetic liability for

lower

vector of lower thresholds

upper

vector of upper thresholds

K_i

vector of stratified CIPs for each individual. Only used for estimating genetic liability under the mixture model.

K_pop

vector of population CIPs. Only used for estimating genetic liability under the mixture model.

Value

A list with two elements: est (expected genetic liability, given input data) and var (variance of genetic liability, given input data).