  Conditional Equi-concentration of Types on I-projections (ICET) and Extended
Gibbs Conditioning Principle (EGCP) provide an extension of Conditioned Weak
Law of Large Numbers and of Gibbs Conditioning Principle to the case of
non-unique Relative Entropy Maximizing (REM) distribution (aka I-projection).
ICET and EGCP give a probabilistic justification to REM under rather general
conditions. mu-projection variants of the results are introduced. They provide
a probabilistic justification to Maximum Probability (MaxProb) method.
'REM/MaxEnt or MaxProb?' question is discussed, briefly. Jeffreys Conditioning
Principle is mentioned.
