MAP_bayes: Calculate MAP (maximum a posteriori) estimates for a...

In JGCRI/gcamland: GCAM Land Allocation Module

Description

The MAP estimate is the estimate in each model group with the highest posterior probability density. The results are reported in a data frame that contains the MAP values of all of the parameters, for all model groups, along with the in-sample deviance.

Usage

MAP_bayes(
  samples,
  modelgroup = "expectation.type",
  reportvars = NULL,
  lp = "lp_"
)

Arguments

samples	Monte Carlo samples, given either as a grand table or a list of ScenarioInfo objects
modelgroup	Vector of names of columns that define the model groupings. The default is the single column expectation.type.
reportvars	Vector of names of variables for which to report expectations. The default is all parameter values.
lp	Name of the column containing the log posterior probability. Ignored if weighted==FALSE.

JGCRI/gcamland documentation built on Oct. 6, 2020, 5:30 p.m.