Wrapper around the Gibbs Sampler that returns formatted liability estimates for the proband

Wrapper around the Gibbs Sampler that returns formatted liability estimates for the proband

Usage

Gibbs_estimator(cov, tbl, out, tol = 0.01, burn_in = 1000, phen_names = NULL)

Arguments

cov

Covariance (kinship matrix times heritability with corrected diagonal) matrix

tbl

Tibble with lower and upper bounds for the Gibbs sampler

out

Vector indicating if genetic ans/or full liabilities should be estimated

tol

Convergence criteria, tolerance

burn_in

Number of burn-in iterations

phen_names

Names of the phenotypes being analyzed

Value

Formatted liability estimate(s) and standard error(s) of the mean for the proband.

Examples

# uninformative sampling:
Gibbs_estimator(cov = diag(3), tbl = tibble::tibble(lower = rep(-Inf, 3),
upper = rep(Inf, 3)), out = 1:2, tol = 0.01, burn_in = 1000)
#> # A tibble: 1 × 4
#>   genetic_est genetic_se  full_est full_se
#>         <dbl>      <dbl>     <dbl>   <dbl>
#> 1    -0.00323    0.00323 -0.000767 0.00318