Probability, Stochastic Processes and Optimization

doi:10.3390/books978-3-0365-9437-8

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Keywords

probabilistic optimization; spherical distribution; multi-variate calculus; hypergeometric functions; transition kernel; system of ordinary differential equations; linear regression analysis; theorem of existence and uniqueness; implicit function theorem; method of moments; precious metals; gold; silver; algorithmic trading; futures; asymptotics; goodness-of-fit; Monte Carlo simulation; Rayleigh distribution; Stein characterization; Malliavin calculus; fourth moment theorem; multiple stochastic integrals; multivariate normal approximation; Gaussian fields; random variable; mean; geometric mean; entropy; cumulative residual entropy; Lindley distribution; Markov chains; Markov operators; finitely additive Markov chains; finitely additive measures; invariant measures; decompositions of Markov chains; binomial crossover; differential evolution; fixed-budget analysis; evolutionary computation; approximation error; exponentially modified Laplace distribution; moments; skewness and kurtosis coefficients; asymmetric piecewise linear systems; transmissibility factors; Lyapunov equation; ϕ-deformed (Naudts) entropy; divergence; relative group entropy; generalized Fisher metric; Fisher-like metric; MaxEnt problem; the alpha power inverse Weibull distribution; step stress partially accelerated life testing; adaptive progressive hybrid censored data; loss functions; continuous evolutionary algorithm; Markov chain; martingale; drift analysis; Wald’s equation; computational complexity; optimal control; Lyapunov function; system of stochastic differential equations; Markov switches; Poisson perturbations; immigration; access to employment; regression and classification models; collinearity and reverse causality checks; performance comparisons and reporting; triangulation; cross-validations; full support for replication of results

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Probability, Stochastic Processes and Optimization

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December 2023

298 pages

ISBN978-3-0365-9436-1 (Hardback)
ISBN978-3-0365-9437-8 (PDF)

https://doi.org/10.3390/books978-3-0365-9437-8

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This is a Reprint of the Special Issue Probability, Stochastic Processes and Optimization that was published in

Computer Science & Mathematics

Engineering

Physical Sciences

Public Health & Healthcare

Summary

The present reprint encompasses all the articles that have been accepted and published in the Special Issue entitled "Probability, Stochastic Processes and Optimization". In applied research, Probability Theory is usually regarded as a distant, often-neglected relative of Statistics. This Special Issue attempted to rectify this misconception by publishing papers presenting novel applications and original models from the natural, computer, or social sciences, based on Probability and Stochastic Processes.