bkmr: ComputePostmeanHnew.approx – R documentation

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ComputePostmeanHnew.approx

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

Function to approximate the posterior mean and variance as a function of the estimated model parameters (e.g., tau, lambda, beta, and sigsq.eps)

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

`fit`	An object containing the results returned by a 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`	logical expression indicating samples to keep; defaults to keeping the second half of all samples

Bayesian Kernel Machine Regression

v0.2.0

GPL-2

Authors

Jennifer F. Bobb [aut, cre]

Initial release