Estimate allele effects matrix, B hat, with Rcpp functions

rcpp_calc_Bhat(X, Sigma_inv, Y)

Arguments

X

dn by df block-diagonal design matrix that incorporates genetic info for two markers. Note that we can use the same marker data twice.

Sigma_inv

dn by dn inverse covariance matrix, where its inverse, ie, Sigma, is often composed as \(K \otimes V_g + I_n \otimes V_e\)

Y

dn by 1 matrix, ie, a column vector, of d phenotypes' measurements

Value

a df by 1 matrix of GLS-estimated allele effects

Examples

X1 <- as.matrix(rbinom(n = 100, size = 1, prob = 1 / 2)) X <- gemma2::stagger_mats(X1, X1) Sigma_inv <- diag(200) Y <- runif(200) rcpp_calc_Bhat(X = X, Sigma_inv = Sigma_inv, Y = Y)
#> [,1] #> [1,] 0.5180447 #> [2,] 0.4910063