get_ML_solution: Function for deriving maximum likelihood solution given...

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

Description

Function for deriving maximum likelihood solution given values for scale-free confounding coefficients.

Usage

get_ML_solution(SS, skappa_X, skappa_Y, sigma_G)

Arguments

SS	Numeric matrix containing first- and second-order statistics.
skappa_X	Numeric scale-free confounding coefficient on exposure.
skappa_Y	Numeric scale-free confounding coefficient on outcome.
sigma_G	Numeric vector of instrument standard deviations.

Value

List of parameters on the ML manifold with the same values for the scaled confounding coefficients (skappa_X, skappa_Y).

Examples

J <- 5 # number of instruments
par <- random_Gaussian_parameters(J)
generate_data_MASSIVE_model(N = 1000, n = 2, p = rep(0.3, J), par)

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