On probabilistic aspects of Chebyshev polynomials

Paweł J. Szabłowski

Statistics & Probability Letters, 2019, vol. 145, issue C, 205-215

Abstract: The main goal of this note is to provide new, mostly multidimensional densities, compactly supported and list many of its properties that enable effective calculations. The idea of obtaining such densities is firstly to build some one-dimensional densities depending on many parameters and then treat the constructed in this way distributions as conditional ones. Then of course by imposing certain distribution on the parameters and multiplying the two distributions we arrive at new multivariate distribution. To enable effective calculations, we utilize nice, simple and widely known properties of Chebyshev polynomials. Thus, in particular, the one-dimensional distribution mentioned above will have a form of arcsine distribution multiplied by some rational function. The fact that we use Chebyshev polynomials allows us to calculate all moments of this one-dimensional distribution as well as to find a family of polynomials that are orthogonal with respect to this distribution.

Keywords: Chebyshev polynomials; Fourier series; Lancaster type expansions; Families of conditional densities; Symmetric rational functions; Symmetric polynomials (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1016/j.spl.2018.08.017

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