Research interests
Pi
problem
and Maximum
Probability (MaxProb)
method.
Relative Entropy Maximization (REM/MaxEnt)
as an asymptotic instance
of MaxProb.
Probabilistic justification of MaxProb and REM/MaxEnt via
Conditional Law of Large Numbers.
Parametric and empirical extensions
of REM/MaxEnt.
Phi
problem
and Bayesian
Maximum
Probability (MAP) method.
Maximum Non-parametric Likelihood (MNPL) as an asymptotic instance
of
MAP.
Probabilistic justification of MAP and MNPL via Bayesian Law of
Large
Numbers.
Large-deviations approach to Bayesian non-parametric consistency.
Estimating Equations and Empirical Likelihood.
Misc: Jeffreys entropy maximization, Golan, Judge & Miller's Generalized MaxEnt, Maximum Entropy Production, Graph entropy, statistical evidence, spam filtering.
A brief survey of some of these subjects can be found here.
Affiliations
Marian Grendár