Information Theory and Statistics

absolutely continuous analysis in table asymptotically distributed B₁ best unbiased estimates binomial distributions binomial population probability canonical correlation Component due component in table conjugate distribution convex function corollary covariance matrix Cramér defined degrees of freedom discrimination information statistic distributed as x² divergence equality error component example fi(x H₁ homogeneous Î(H₁ independent observations Information D.F. Ĵ(H₁ k₁ k₂ lemma linear discriminant function log f(x log M₂(7 m₁ M₂(T minimum discrimination information multinomial distribution multivariate normal N₁ N₂ noncentral normal distribution normal populations Note null hypothesis H₂ P₁ P₂ partitioning Pijk Poisson distribution Poisson population Prob probability measure probability of success problem regression respectively samples specified sufficient statistic Suppose theorem 2.1 Total unbiased estimates usual x² variance x/N₁ x₁ Xijk y₁ μ₁ Σ Σ σ² ΣΣ Στ