This is the internal MVMRcML-BIC function of mr_mvcML.
MVmr_cML(
b_exp,
b_out,
se_bx,
Sig_inv_l,
n,
K_vec = as.numeric(c()),
random_start = 1L,
min_theta_range = -0.5,
max_theta_range = 0.5,
maxit = 100L,
thres = 1e-04
)A list
Estimated causal effect from MVMR-cML-BIC
Invalid IVs selected by MVMR-cML-BIC
A vector of negative log-likelihood corresponding to each K.
A vector of candidate K's
A matrix of causal parameter estimates, each column corresponds to a candidate K.
A vector of successful convergence indicators corresponding to each K.
Indicator of successful convergence, 0 means success, 1 means failure.
Data perturbation with successful convergence
The length of BIC_invalid.
A m*L matrix of SNP effects on the exposure variable.
A m*1 matrix of SNP effects on the outcome variable.
A m*L matrix of standard errors of b_exp.
A list of the inverse of m covariance matrices.
The smallest sample size of the L+1 GWAS dataset.
Sets of candidate K's, the constraint parameter representing number of invalid IVs.
Number of random start points, default is 1.
The lower bound of the uniform distribution for each initial value for theta generated from.
The upper bound of the uniform distribution for each initial value for theta generated from.
Maximum number of iterations for each optimization, default is 100.
Threshold for convergence criterion.