Modelling Nonlinearity with Normal Polynomial Expansions
Apr 30 1987
Polynomial expansions of the normal probability density function are proposed as a class of models for unobserved components. Operational procedures for Bayesian inference in these models are developed, as are methods for combining a sequence of such models and evaluation of the hypotheses of normality and symmetry. The contributions of the paper are illustrated with an application to daily rates of change in stock price.