Abstract:Library of Congress Cataloging-in-Publication Data Schoutens, Wim. Stochastic processes and orthogonal polynomials / Wim Schoutens. p. cm.-(Lecture notes in statistics; 146) Includes bibliographical references and index.
“…More recent work has shown that an important class of orthogonal polynomials belongs to the Askey scheme of the hypergeometric polynomials [17]. In this section, we briefly review the theory of hypergeometric orthogonal polynomials; we adopt the notation of [21,22].…”
Section: The Askey Scheme Of Hypergeometric Orthogonal Polynomialsmentioning
confidence: 99%
“…The Askey scheme, which is represented as a tree structure in figure 1 (following [22]), classifies the hypergeometric orthogonal polynomials and indicates the limit relations between them. The 'tree' starts with the Wilson polynomials and the Racah polynomials on the top.…”
Section: The Askey Schemementioning
confidence: 99%
“…For a detailed account of the limit relations of Askey scheme, the interested reader should consult [21] and [22].…”
“…More recent work has shown that an important class of orthogonal polynomials belongs to the Askey scheme of the hypergeometric polynomials [17]. In this section, we briefly review the theory of hypergeometric orthogonal polynomials; we adopt the notation of [21,22].…”
Section: The Askey Scheme Of Hypergeometric Orthogonal Polynomialsmentioning
confidence: 99%
“…The Askey scheme, which is represented as a tree structure in figure 1 (following [22]), classifies the hypergeometric orthogonal polynomials and indicates the limit relations between them. The 'tree' starts with the Wilson polynomials and the Racah polynomials on the top.…”
Section: The Askey Schemementioning
confidence: 99%
“…For a detailed account of the limit relations of Askey scheme, the interested reader should consult [21] and [22].…”
“…Since corr(ξ k−1 , ξ k ) = t k−1 /t k = 0, ±1, the assumption [33, (10)] holds true, too. Finally, notice that Weso lowski's α k = 1, and his (27) we see that D = 0 if and only if C = b. Thus [33, (11)] hold true.…”
Section: Conditional Variancesmentioning
confidence: 85%
“…We can solve this equation for E(X 3 u |F ≤s ), as (27) implies that C = b. Using (24) and (19), the answer simplifies to…”
Abstract. We show that stochastic processes with linear conditional expectations and quadratic conditional variances are Markov, and their transition probabilities are related to a three-parameter family of orthogonal polynomials which generalize the Meixner polynomials. Special cases of these processes are known to arise from the non-commutative generalizations of the Lévy processes.
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