Download or read book Nonparametric Estimation of Some Transition Probabilities in a Partially Observed Markov Illness death Process with Biological Applications written by Jochen Mau and published by . This book was released on 1983 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Estimation in a Markov Illness death Process from Interval Censored Observations with Missing Intermediate Transition Status written by Halina Frydman and published by . This book was released on 2007 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Maximum Likelihood Estimation for a Periodically Observed Markov illness death Process written by Halina Frydman and published by . This book was released on 1991 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Nonparametric Estimation Procedure for a Partially Observed Three State Markov Chain with Irreversible Transitions written by H. Frydman and published by . This book was released on 1989 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Estimation of the Integrated Intensity Function of an Unobservable Transition in Markov Illness death Processes written by Jochen Mau and published by . This book was released on 1983 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book General Birth death Processes written by Forrest Wrenn Crawford and published by . This book was released on 2012 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: A birth-death process is a continuous-time Markov chain that counts the number of particles in a system over time. Each particle can give birth to another particle or die, and the rate of births and deaths at any given time depends on how many extant particles there are. Birth-death processes are popular modeling tools in evolution, population biology, genetics, epidemiology, and ecology. Despite the widespread interest in birth-death models, no efficient method exists to evaluate the finite-time transition probabilities in a process with arbitrary birth and death rates. Statistical inference of the instantaneous particle birth and death rates also remains largely limited to continuously-observed processes in which per-particle birth and death rates are constant. The lack of theoretical progress in developing statistical tools for dealing with data from birth-death processes has hindered their adoption by applied researchers, and represents a major research frontier in statistical inference for stochastic processes. In this dissertation, I seek to fill this apparent void in three ways. First, I develop mathematical theory and computational tools for computing transition probabilities for general birth-death processes. Second, I develop algorithms for maximum likelihood estimation of rate parameters in discretely observed processes. Third, I derive probability distributions for characteristics of certain birth-death models that are fundamental in macroevolutionary studies. In each case, I give practical applications of the methodology, and show how unsolved problems can be attacked using these techniques.

Download or read book Nonparametric Estimation of Transition Intensities and Transition Probabilities written by N. Keiding and published by . This book was released on 1987 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Non parametric Estimation in an illness death Model when the Transition Times are Interval censored and One Transition is Not Observed written by Halina Frydman and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Research Reports written by Halina Frydman and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Likelihood based Inference for Partially Observed Multi type Markov Branching Processes written by Jason Xu and published by . This book was released on 2016 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov branching processes are a class of continuous-time Markov chains (CTMCs) frequently used in stochastic modeling with ubiquitous applications. Bivariate or multi-type processes are necessary to model phenomena such as competition, predation, or infection, but often feature large or uncountable state spaces, rendering many general CTMC techniques impractical. We present spectral techniques to compute the transition probabilities and related quantities discretely and unevenly observed multi-type branching processes, enabling likelihood-based inference. Our technique reduces these calculations to low dimensional integration, and analogously enables calculation of related terms such as expected sufficient statistics within an expectation maximization (EM) algorithm. We rigorously assess our EM algorithm in several simulation studies applied to a birth-death-shift (BDS) model, and apply it to estimate intrapatient time evolution of IS6110 transposable element, a genetic marker frequently used during epidemiological studies of Mycobacterium tuberculosis. Further, we incorporate our methods for computing transition probabilities within a compressed sensing framework, demonstrating scalability in the presence of sparsity. Finally, we extend these ideas to loss function estimation of in vivo hematopoietic rates from single-cell lineage tracking data, and develop efficient Bayesian methods for fitting general stochastic epidemic models to discretely observed time series data and partially observed incidence data.

Download or read book Birth and Death Processes and Markov Chains written by Zikun Wang and published by . This book was released on 1992 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Estimation in Markov Processes written by George G. Roussas and published by . This book was released on 1967 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Estimation Based on Censored Observations of a Markov Reneval Process written by R. D. Gill and published by . This book was released on 1978 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Current Index to Statistics Applications Methods and Theory written by and published by . This book was released on 1987 with total page 866 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.

Download or read book Mathematical Reviews written by American Mathematical Society and published by American Mathematical Society(RI). This book was released on 1986-12 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Estimation Based on Censored Observation of a Markov Renewal Process written by R. D. Gill and published by . This book was released on 1978 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Partially Observable Markov Decision Processes with Applications written by Dale J. Hockstra and published by . This book was released on 1973 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study examines a class of partially observable sequential decision models motivated by the process of machine maintenance and corrective action or medical diagnosis and treatment. Emphasis is placed on the dynamics of the state, i.e., the possibility that the machine (disease) state changes during the decision process. This is incorporated in the form of a Markov chain. It is also assumed that the state is only indirectly observable via outputs probabilistically related to the state. The end result is a model which is a discrete time Markov decision process with a continuous state space, a finite action space, and a special transition structure. (Modified author abstract).