predict.bas

predict

An object of class BAS, created by <code>bas</code>

object

dataframe, new matrix or vector of data for predictions. May 
    include a column for the intercept or just the predictor variables.
  If a dataframe, the variables are extracted using model.matrix using
  the call that created 'object'.

newdata

a scalar integer M.  If supplied, subset the top M models,
  based on posterior probabilities for model predictions and BMA.

Type of predictions required. "Link" which is on the
  scale of the linear predictor is the only option currently.

type

Predictions under model averaging from a BMA object of
  class inheriting from 'bas'.

regression

Package for Bayesian Model Averaging in linear models and
	     generalized linear models using stochastic or
	     deterministic sampling without replacement from posterior
	     distributions.  Prior distributions on coefficients are
	     from Zellner's g-prior or mixtures of g-priors
	     corresponding to the Zellner-Siow Cauchy Priors or the
	     Liang et al hyper-g priors (JASA 2008) or mixtures of
	     g-priors in GLMS of Li and Clyde 2015. Other model
	     selection criteria include AIC and BIC. Sampling
	     probabilities may be updated based on the sampled models
	     using Sampling w/out Replacement or an MCMC algorithm
	     samples models using the BAS tree structure as an efficient
	     hash table. Allows uniform or beta-binomial prior distributions on
	     models, and may force variables to always be included.

predict.bas: Prediction Method for an object of class BMA

Description

Usage

Arguments

Value

Details

See Also

Examples