rand.eff.coord.desc.unpenalized {messi} | R Documentation |
Cyclical coordinate descent algorithm for the M-step in the EM Algorithm for the maximizing the soft constraint model likelihood.
Description
Cyclical coordinate descent algorithm for the M-step in the EM Algorithm for the maximizing the soft constraint model likelihood.
Usage
rand.eff.coord.desc.unpenalized(
Y,
M,
A,
C = NULL,
first.moment,
second.moment,
err.tol.out = 1e-08,
err.tol.med = 1e-08,
max.itr = 10000
)
Arguments
Y |
A (n x 1) continuous outcome vector. |
M |
A (n x p_m) matrix of mediators. |
A |
A (n x 1) vector of exposures. |
C |
A (n x p_c) matrix of confounders and adjustment covariates. If there are no confounders or adjustment covariates set C = NULL. |
first.moment |
Posterior expectation of the total effect parameter. |
second.moment |
Posterior expection of the squared total effect parameter. |
err.tol.out |
Termination condition for cyclical coordinate descent algorithm with respect to the outcome model parameters. |
err.tol.med |
Termination condition for cyclical coordinate descent algorithm with respect to the mediator model parameters. |
max.itr |
Maximum number of iterations for cyclical coordinate descent algorithm. |
Value
A list containing point estimates of the soft constraint model parameters and an indicator of whether the algorithm converges.