Titlebook: Embryonic Stem Cells; John R. Masters,Bernhard O. Palsson,James A. Thoms Book 2007 Springer Science+Business Media B.V. 2007 cell.cell dif

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Tenneille Ludwig,James A. Thomsonplores the practical applicability of novel Bayesian statist.Bayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide ran

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Stephen Mingerred data are studied when the exact times of the events are of interest and these exact times are not directly observed but are only known to fall within some intervals formed by the observation times. Panel count data are under investigation when the exact times of the recurrent events are not of i

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Zhi-Jian Zhang,Jason S. Meyer,Su-Chun Zhangpect to observed data. For example, the number of binomial demands may not have been recorded and may have to be estimated. Similarly, the exposure time in the Poisson distribution may have to be estimated. One may not always be able to tell the exact number of failures that have occurred, because o

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Vanessa T. Angeles,Renee A. Reijo Perapect to observed data. For example, the number of binomial demands may not have been recorded and may have to be estimated. Similarly, the exposure time in the Poisson distribution may have to be estimated. One may not always be able to tell the exact number of failures that have occurred, because o

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Nadav Sharon,Nissim Benvenistyhese problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemented using custom-written routines or existing general purpose commercial or open-source software. This book uses an open-source program called OpenB

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Sharon Gerecht,Jason A. Burdick,Christopher Cannizzaro,Gordana Vunjak-Novakovic The fundamental reason for these advances is that the statistics of many natural signals, when decomposed in such bases, are substantially simplified. Choosing a basis that is adapted to statistical properties of the input signal is a classical problem. The traditional solution is principal compone