Rcpp_scaled_neg_log_hessian: Rcpp routine for computing the negative log-posterior Hessian...

In igbucur/MASSIVE: MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models

Description

Rcpp routine for computing the negative log-posterior Hessian of the MASSIVE model.

Usage

Rcpp_scaled_neg_log_hessian(J, N, SS, sigma_G, param_list, prior_sd, n = 2L)

Arguments

J	Integer number of genetic instrumental variables.
N	Integer number of observations.
SS	Numeric matrix containing first- and second-order statistics.
sigma_G	Numeric vector of genetic IV standard deviations.
param_list	List of IV model parameter values.
prior_sd	List of standard deviations for the parameter Gaussian priors.
n	Integer number of alleles (trials) for the binomial genetic variants.

Value

numeric matrix; negative log-posterior Hessian for the MASSIVE model.

igbucur/MASSIVE documentation built on Oct. 26, 2020, 1:26 a.m.