posteriors | R Documentation |
Extract posterior model probability estimates (either normalized
estimates or sampling frequencies) from BayesMfp
objects.
posteriors(BayesMfpObject, ind = 1)
BayesMfpObject |
a valid |
ind |
|
The vector of probability estimates.
Daniel Saban\'es Bov\'e
## construct a BayesMfp object set.seed(19) x1 <- rnorm (n=15) x2 <- rbinom (n=15, size=20, prob=0.5) x3 <- rexp (n=15) y <- rt (n=15, df=2) test <- BayesMfp (y ~ bfp (x1, max = 2) + bfp (x2, max = 2) + uc (x3), nModels = 100, method="exhaustive") ## this works: posteriors(test) ## this must not work: ## SoDA::muststop(posteriors(test, ind=2)) ## only if we do model sampling there are model frequencies: test2 <- BayesMfp (y ~ bfp (x1, max = 2) + bfp (x2, max = 2) + uc (x3), nModels = 100, method="sampling") posteriors(test2, ind=2)
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