LEADER 00730nam0-22002771i-450 001 990002596550403321 005 20230323130718.0 035 $a000259655 035 $aFED01000259655 035 $a(Aleph)000259655FED01 035 $a000259655 100 $a20000920d1905----km-y0itay50------ba 101 0 $aita 102 $aIT 200 1 $aElementi di computisteria$fdi STELLA 205 $a3ª Ed. riveduta ed ampliata 210 $aNapoli$cChimeri$d1905 215 $a234 p.$d23 cm 700 1$aStella,$bA.$0378181 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002596550403321 952 $aDEP-PLT7-17-RA$bs.i.$fECA 959 $aECA 996 $aElementi di computisteria$9434122 997 $aUNINA LEADER 01702nam 2200493I 450 001 9910704025003321 005 20250513224843.0 035 $a(CKB)5470000002437407 035 $a(OCoLC)927410526 035 $a(EXLCZ)995470000002437407 100 $a20151103j199205 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApproximation methods for stochastic petri nets /$eby Hauke Jörg Jungnitz 210 1$aTroy, New York :$cRensselaer Polytechnic Institute, Electrical, Computer, and Systems Engineering Department,$dMay 1992. 215 $a1 online resource (viii, 170 pages) $cillustrations 225 1 $aNASA-CR ;$v191851 225 1 $aCIRSSE report ;$v#119 300 $aTitle from title screen (viewed on Nov. 3, 2015). 300 $a"May 1992." 320 $aIncludes bibliographical references (pages 162-170). 517 $aApproximation methods for stochastic petri nets / 606 $aPetri nets$2nasat 606 $aRobotics$2nasat 606 $aSISO (control systems)$2nasat 606 $aStochastic processes$2nasat 606 $aSynchronism$2nasat 615 7$aPetri nets. 615 7$aRobotics. 615 7$aSISO (control systems) 615 7$aStochastic processes. 615 7$aSynchronism. 700 $aJungnitz$b Hauke Jo?rg$01421818 712 02$aRensselaer Polytechnic Institute.$bElectrical, Computer, and Systems Engineering Department, 801 0$bGPO 801 1$bGPO 801 2$bGPO 906 $aBOOK 912 $a9910704025003321 996 $aApproximation methods for stochastic petri nets$93544142 997 $aUNINA LEADER 03622nam 22006135 450 001 9910255458903321 005 20250505001401.0 010 $a981-10-6557-8 024 7 $a10.1007/978-981-10-6557-6 035 $a(CKB)3790000000544588 035 $a(DE-He213)978-981-10-6557-6 035 $a(MiAaPQ)EBC5214685 035 $z(PPN)258852445 035 $a(PPN)223953903 035 $a(EXLCZ)993790000000544588 100 $a20180102d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistical Modelling of Survival Data with Random Effects $eH-Likelihood Approach /$fby Il Do Ha, Jong-Hyeon Jeong, Youngjo Lee 205 $a1st ed. 2017. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2017. 215 $a1 online resource (XIV, 283 p. 23 illus.) 225 1 $aStatistics for Biology and Health,$x2197-5671 311 08$a981-10-6555-1 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Classical Survival Analysis -- H-likelihood Approach to Random-E?ects Models -- Simple Frailty Models -- Multi-Component Frailty Models -- Competing Risks Frailty Models -- Variable Selection for Frailty Models -- Mixed-E?ects Survival Models -- Joint Model for Repeated Measures and Survival Data -- Further Topics -- A Formula for ?tting ?xed and random e?ects -- References -- Index. 330 $aThis book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (?frailtyHL?), while the real-world data examples together with an R package, ?frailtyHL? in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to researchers in medical and genetics fields, graduate students, and PhD (bio) statisticians.      . 410 0$aStatistics for Biology and Health,$x2197-5671 606 $aStatistics 606 $aBiometry 606 $aMathematical statistics$xData processing 606 $aStatistical Theory and Methods 606 $aBiostatistics 606 $aStatistics and Computing 615 0$aStatistics. 615 0$aBiometry. 615 0$aMathematical statistics$xData processing. 615 14$aStatistical Theory and Methods. 615 24$aBiostatistics. 615 24$aStatistics and Computing. 676 $a610.72 700 $aHa$b Il Do$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767638 702 $aJeong$b Jong-Hyeon$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLee$b Youngjo$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910255458903321 996 $aStatistical Modelling of Survival Data with Random Effects$91961541 997 $aUNINA