A November 2019 special session in Riverside, California focused on the key role in abstract analysis plays in simplifying and solving fundamental problems in stochastic theory. The 13 mathematical papers discuss such matters as sufficient conditions for Lorentz ordering with common finite support, nonlinear parabolic equations with Robin boundary conditions and Hardy-Leray type inequalities, explicit transient probability of various Markov models, Eulerian polynomials and quasi-birth-death processes with time-varying-periodic rates, and the exponential-dual matrix method: applications to Markov chain analysis. Annotation ©2022 Ringgold, Inc., Portland, OR (protoview.com)
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Randall J. Swift, California State Polytechnic University, Pomona, CA.
Alan Krinik, California State Polytechnic University, Pomona, CA.
Jennifer M. Switkes, California State Polytechnic University, Pomona, CA.
Jason H. Park, University of Nevada, Las Vegas, NV.
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