Accession Number : AD0606162
Title : BAYES DECISION PROCEDURES FOR STIMULUS SAMPLING MODELS: I. NONSEQUENTIAL EXPERIMENTATION.
Descriptive Note : Scientific rept.,
Corporate Author : SYSTEM DEVELOPMENT CORP SANTA MONICA CALIF
Personal Author(s) : Dear,Robert E.
Report Date : 28 JUL 1964
Pagination or Media Count : 64
Abstract : In stimulus sampling models of learning, the probability distribution defined on the sequence of conditioning functions which are used in these models may be regarded as a distribution over parameters. Consequently, this probability distribution is interpreted as an a priori distribution and the appropriateness of Bayes decision procedures for solving statistical decision problems involving these models is shown. Using beta distributions as a tractable family of prior distributions over the parameters of the single element model, Bayes solutions are illustrated to: (1) the learning criterion problem, (2) parameter estimation problems, and (3) the optimal design of a learning experiment. (Author)
Descriptors : (*DECISION THEORY, SAMPLING), (*SAMPLING, DECISION THEORY), (*DISTRIBUTION THEORY, SAMPLING), LEARNING, STIMULATION(PHYSIOLOGY), MATHEMATICAL MODELS, STATISTICAL ANALYSIS
Distribution Statement : APPROVED FOR PUBLIC RELEASE