LEADER 04181nam 2200673Ia 450 001 9910782770903321 005 20220110142727.0 010 $a1-281-96006-3 010 $a9786611960063 010 $a0-387-73173-3 024 7 $a10.1007/978-0-387-73173-5 035 $a(CKB)1000000000699060 035 $a(EBL)417305 035 $a(OCoLC)317883310 035 $a(SSID)ssj0000244021 035 $a(PQKBManifestationID)11200450 035 $a(PQKBTitleCode)TC0000244021 035 $a(PQKBWorkID)10169332 035 $a(PQKB)11391630 035 $a(DE-He213)978-0-387-73173-5 035 $a(MiAaPQ)EBC417305 035 $a(Au-PeEL)EBL417305 035 $a(CaPaEBR)ebr10273525 035 $a(CaONFJC)MIL196006 035 $a(PPN)132863170 035 $a(EXLCZ)991000000000699060 100 $a20070918d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSemi-Markov chains and hidden semi-Markov models toward applications$b[electronic resource] $etheir use in reliability and DNA analysis /$fVlad Stefan Barbu and Nikolaos Limnios 205 $a1st ed. 2008. 210 $aNew York $cSpringer$d2008 215 $a1 online resource (232 p.) 225 1 $aLecture notes in statistics ;$vv. 191 300 $aDescription based upon print version of record. 311 $a0-387-73171-7 320 $aIncludes bibliographical references (p. [211]-220) and index. 327 $aDiscrete-Time Renewal Processes -- Semi-Markov Chains -- Non parametric Estimation for Semi-Markov Chains -- Reliability Theory for Discrete-Time Semi-Markov Systems -- Hidden Semi-Markov Model and Estimation. 330 $aThis book is concerned with the estimation of discrete-time semi-Markov and hidden semi-Markov processes. Semi-Markov processes are much more general and better adapted to applications than the Markov ones because sojourn times in any state can be arbitrarily distributed, as opposed to the geometrically distributed sojourn time in the Markov case. Another unique feature of the book is the use of discrete time, especially useful in some specific applications where the time scale is intrinsically discrete. The models presented in the book are specifically adapted to reliability studies and DNA analysis. The book is mainly intended for applied probabilists and statisticians interested in semi-Markov chains theory, reliability and DNA analysis, and for theoretical oriented reliability and bioinformatics engineers. It can also serve as a text for a six month research-oriented course at a Master or PhD level. The prerequisites are a background in probability theory and finite state space Markov chains. Vlad Stefan Barbu is associate professor in statistics at the University of Rouen, France, Laboratory of Mathematics ?Raphaël Salem.? His research focuses basically on stochastic processes and associated statistical problems, with a particular interest in reliability and DNA analysis. He has published several papers in the field. Nikolaos Limnios is a professor in Applied Mathematics at the University of Technology of Compiègne. His research interest concerns stochastic processes and statistics with application to reliability. He is the co-author of the books: Semi-Markov Processes and Reliability (Birkhäuser, 2001 with G. Oprisan) and Stochastic Systems in Merging Phase Space (World Scientific, 2005, with V.S. Koroliuk). 410 0$aLecture notes in statistics (Springer-Verlag) ;$vv. 191. 606 $aMarkov processes 606 $aReliability (Engineering)$xMathematical models 606 $aDNA$xAnalysis$xMathematical models 615 0$aMarkov processes. 615 0$aReliability (Engineering)$xMathematical models. 615 0$aDNA$xAnalysis$xMathematical models. 676 $a519.233 700 $aBarbu$b Vlad Stefan$01547564 701 $aLimnios$b N$g(Nikolaos)$0900137 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910782770903321 996 $aSemi-Markov chains and hidden semi-Markov models toward applications$93804011 997 $aUNINA