On positivity of orthogonal series and its applications in probability

Abstract

We give necessary and sufficient conditions for an orthogonal series to converge in the mean-squares to a nonnegative function. We present many examples and applications, in analysis and probability. In particular, we give necessary and sufficient conditions for a Lancaster-type of expansion with two sets of orthogonal polynomials $\left\{{\alpha }_n\right\}$ and $\left\{{\beta }_n\right\}$ to converge in means-squares to a nonnegative bivariate function. In particular, we study the properties of the set $C(\alpha ,\beta )$ of the sequences $\left\{c_n\right\},$ for which the above-mentioned series converge to a nonnegative function and give conditions for the membership to it. Further we show that the class of bivariate distributions for which a Lancaster type expansion can be found, is the same as the class of distributions having all conditional moments in the form of polynomials in the conditioning random variable.

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Cited by in corpus (1)

• Stationary, Markov, stochastic processes with polynomial conditional moments and continuous paths