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dc.contributor.editorVassiliou, Panagiotis-Christos
dc.contributor.editorGeorgiou, Andreas C.
dc.date.accessioned2025-08-12T08:13:01Z
dc.date.available2025-08-12T08:13:01Z
dc.date.issued2025
dc.identifierONIX_20250812T095121_9783725832231_162
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/165213
dc.description.abstractMathematics is publishing a Special Issue to honor Prof. Sally McClean on the occasion of her semi-retirement and in recognition of her important research contributions. Sally Ida McClean was born in Belfast and received her first degree, an M.A. in Mathematics, from the University of Oxford in 1970. She earned an M.Sc. in Mathematical Statistics and Operations Research from Cardiff University in 1972, and completed her Ph.D. in 1976 at Ulster University at Coleraine. Her contribution to mathematical modeling in healthcare planning is enormous, and, in particular, her studies on improving the wellbeing of the elderly are greatly respected amongst her peers. She is currently a Professor of Mathematics at Ulster University. Her main research interests are in Stochastic Modeling and Optimization for Healthcare Planning and Computer Science. Stochastic processes are some of the most important tools in many areas of science, such as biology, operational research, the social sciences, stochastic finance, etc. Important characteristics in these areas evolve with time in a relatively random way, and since stochastic processes are mainly sequences or families of random variables, in which their index represents time, they are the natural tool to use. The theory and applications of stochastic processes emerged in the genesis of one of the richest ones, that is, Brownian motion. This was rather unexpected since Brownian motion is a beautiful object which is at the same time a martingale, a Gaussian process, a diffusion, a Levy process, a Markov process, etc.—concepts that were discovered quite latter in the evolution of time.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
dc.subject.classificationthema EDItEUR::P Mathematics and Science
dc.subject.otherMarkov-type model
dc.subject.otherprocess mining
dc.subject.otherSmart Homes
dc.subject.otherconvolution of gamma mixture models
dc.subject.otherdynamical systems
dc.subject.otherstability analysis
dc.subject.otherasymptotic behavior
dc.subject.otherKalman filters
dc.subject.otherepidemiological modelling
dc.subject.otherCOVID-19
dc.subject.otherDEA
dc.subject.otherbilevel optimization
dc.subject.otherstochastic conditions
dc.subject.otherresource allocation
dc.subject.otherstrong ergodicity
dc.subject.othernonhomogeneous Markov systems
dc.subject.otherrate of convergence
dc.subject.otherMarkov chains
dc.subject.othernon homogeneous
dc.subject.othercontinuous time
dc.subject.otherregime switching processes
dc.subject.otherestimation
dc.subject.othercalibration
dc.subject.otherhealth insurance
dc.subject.otherlong-term care
dc.subject.otherEuler distribution
dc.subject.otherHeine distribution
dc.subject.othernegative q-binomial distribution
dc.subject.otherq-binomial distribution
dc.subject.otherq-factorial moments
dc.subject.otherq-logarithmic distribution
dc.subject.otherq-poisson distribution
dc.subject.otherintergenerational social mobility
dc.subject.otherMarkov processes
dc.subject.otherESS
dc.subject.othersemi-Markov model
dc.subject.otherMarkov model
dc.subject.otherattainability
dc.subject.othermaintainability
dc.subject.otherstate reunion
dc.subject.othermanpower planning
dc.subject.otherhealthcare
dc.subject.othersemi-Markov systems
dc.subject.otherpopulation structure
dc.subject.othercost evaluation
dc.subject.otherMarkov stochastic process
dc.subject.otherKolmogorov equation
dc.subject.otherdifferential equation
dc.subject.otherperturbation theory
dc.subject.othersensitivity analysis
dc.subject.otherstability
dc.subject.otherrobustness
dc.subject.otherergodicity coefficient
dc.subject.otherstationary distribution
dc.subject.othersequential measures
dc.subject.otherconvolution product
dc.subject.othersemi-Markov processes
dc.subject.otherasymptotic results
dc.subject.otherlicense assisted access
dc.subject.othercoexistence
dc.subject.otherclear channel assessment
dc.subject.otherMarkov chain
dc.subject.othern/a
dc.titleStochastic Processes and Their Applications
dc.title.alternativeIn Honor of Prof. Sally McClean
dc.typebook
oapen.identifier.doi10.3390/books978-3-7258-3224-8
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783725832231
oapen.relation.isbn9783725832248
oapen.pages216


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