Synopsis
Contents: Introduction: Purpose. Separable Sigma-Algebras. Probability Space.- Discrimination Information and Sufficiency in a Sub-Sigma-Algebra: Discrimination Information-Integral Representation. Discrimination Information in a Sub-Sigma-Algebra. Sufficiency. Minimium Discrimination Information Theorem. Analysis of Information.- limiting Properties: Lower Semi-Continuity. Sequences of Sub-Sigma-Algebras. An Information Theoretic Approach. Monotonicity.- Product Measure Spaces: Generalized Contingency Tables. Markov Processes. Ornstein-Uhlenbeck Process. The Wiener Process. Different Covariance Functions. Gaussian Markov Processes.- Linear Discriminant Functional: Representation of a Random Vector. Examples. Poisson Process.- Canonical Correlation: Spectral Densities as Eigenvalues. Discrimination Information-Different Covariance Functions. Stationarily Related Processes.- References.- Index.
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