summary.MCMCglmmPredictedProbs: Summary method for MCMCglmm predicted probabilities

In JWiley/postMCMCglmm: Average marginal predicted probabilities from Bayesian ordered probit models

Description

Optionally first marginalizes across all observations by taking the row means. If the predicted values only used the posterior means, highest posterior density (HPD) intervals cannot be generated, so only the means are returned. Otherwise, it calculates the mean predicted probability, as well as the HPD interval. This can either be per observation or marginalized.

Usage

  ## S3 method for class 'MCMCglmmPredictedProbs'
 summary(object,
    marginalize = FALSE, level = 0.95, ...)

Arguments

object	A MCMCglmmPredictedProbs object to summarize
marginalize	Logical whether or not to marginalize by taking the row means. Defaults to FALSE.
level	A numeric value, the value to use when calculating HPD intervals. Defaults to .95.
...	Not currently used.

Value

If HPD intervals are calculated, returns a list of matrices with the means, lower limit, and upper limit. If no HPD intervals are calculated, returns a list of means.

See Also

predict2.MCMCglmm, recycler

Examples

## Not run: 
  ## Make me!

## End(Not run)

JWiley/postMCMCglmm documentation built on May 7, 2019, 10:15 a.m.