data(Hald)
hald.gprior = bas.lm(Y~ ., data=Hald, prior="g-prior", alpha=13,
modelprior=beta.binomial(1,1),
initprobs="eplogp")
hald.gprior
plot(hald.gprior)
summary(hald.gprior)
image(hald.gprior, subset=-1, vlas=0)
hald.coef = coefficients(hald.gprior)
hald.coef
plot(hald.coef)
predict(hald.gprior, hald.gprior$X[,-1], top=5) # do not include the intercept in the design matrix
fitted(hald.gprior, type="HPM")
hald.gprior = bas.lm(Y~ ., data=Hald, n.models=2^4,
prior="g-prior", alpha=13, modelprior=uniform(),
initprobs="eplogp")
hald.EB = update(hald.gprior, newprior="EB-global")
hald.bic = update(hald.gprior,newprior="BIC")
hald.zs = update(hald.bic, newprior="ZS-null")
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