پديد آورنده :
بشكار، اسماعيل
عنوان :
توزيع فاز- نوع در مدل بندي تصادفي و برآورد پارامترهاي آن
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
آمار اقتصادي و اجتماعي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده علوم رياضي
صفحه شمار :
ده،99ص.: مصور،جدول،نمودار
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
صفيه محمودي
توصيفگر ها :
اطلاع فيشر , الگوريتم EM , نيوتن-رافسون
تاريخ نمايه سازي :
8/11/92
استاد داور :
افشين پرورده، سعيد پولادساز
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Phase Type Distribution in StochasticModeling and Estimating Its Parameters Esmaeil Bashkar e bashkar@math iut ac ir 2013 Department of Mathematical Sciences Isfahan University of Technology Isfahan 84156 83111 Iran Supervisor Dr Sa eh Mahmoodi mahmoodi@cc iut ac ir Advisor Dr Ali Rejali a rejali@cc iut ac ir 2010 MSC 05C15 53C42 Keywords Phase type distributions Fisher information EM algorithm Newton Raphson AbstractA random variable that is de ned as the absorption time of a nite state Markov chain is said to havea phase type or simply PH distribution When the Markov chain is continuous time the distributionis continuous and for the discrete time Markov chains it will be a discrete phase type distribution Inthis thesis we will focus on the continuous phase type one The distribution and density functions of aPH distribution can be expressed in terms of T where is the initial state probability distributionand T is the in nitesimal generator corresponding to the transient states of the Markov chain Thepair T is known as a representation of the PH distribution The dimension of T is said to be theorder of the representation This thesis is concerned with the statistical inference for phase type distributions The main aim ofit is to estimate the parameters and T Under certain regularity conditions the maximum likelihoodestimator MLE is a good point estimator possessing some of the optimality properties consistency e ciency and asymptotic normality The thesis is focused on nding maximum likelihood estimatorsof phase type distributions for continuous case The Expectation Maximization EM algorithm andNewton Raphson NR method are applied for this purpose Fisher information has applications in nding the variance of an estimator as well as in theasymptotic behavior of maximum likelihood estimates This thesis discussed on an explicit formulafor computing the observed Fisher information matrix for continuous phase type distributions whichis needed to estimate the Fisher information matrix
استاد راهنما :
صفيه محمودي
استاد داور :
افشين پرورده، سعيد پولادساز
