Compute the posterior mean and variance of h at a new predictor values using approx method for MI BKMR fits

Source: R/ComputePostmeanHnew.approx.R

Compute the posterior mean and variance of h at a new predictor values

ComputePostmeanHnew.approx(
  fit,
  y = NULL,
  Z = NULL,
  X = NULL,
  Znew = NULL,
  sel = NULL
)

Arguments

fit

An object contatin the results return by the kmbayes function

y

a vector of outcome data of length n.

Z

an n-by-M matrix of predictor variables to be included in the h function. Each row represents an observation and each column represents an predictor.

X

an n-by-K matrix of covariate data where each row represents an observation and each column represents a covariate. Should not contain an intercept column.

Znew

matrix of new predictor values at which to predict new h, where each row represents a new observation. If set to NULL then will default to using the observed exposures Z

sel

selects which iterations of the MCMC sampler to use for inference

Value

A list of mean, variance, entire mean matrix and variance array