Page 214 - Applied Probability
P. 214

9. Descent Graph Methods
                                                                                            199
                                      References
                              9.15
                               [1] Baum LE (1972) An inequality and associated maximization tech-
                                   nique in statistical estimation for probabilistic functions of Markov
                                   processes. Inequalities 3:1–8
                               [2] Bishop DT, Williamson JA, Skolnick MH (1983) A model for restric-
                                   tion fragment length distributions. Amer J Hum Genet 35:795–815
                               [3] Dausset J, Cann H, Cohen D, Lathrop M, Lalouel J-M, White R (1990)
                                   Centre d’Etude du Polymorphisme Humain (CEPH): Collaborative
                                   genetic mapping of the human genome. Genomics 6:575–577
                               [4] Devijver PA (1985) Baum’s forward-backward algorithm revisited.
                                   Pattern Recognition Letters 3:369–373
                               [5] Ehm MG, Cottingham RW Jr, Kimmel M (1996) Error detection in
                                   genetic linkage data using likelihood based methods. Amer J Hum
                                   Genet 58:225–234
                               [6] Feller W (1968) An Introduction to Probability Theory and its Appli-
                                   cations, Vol 1, 3rd ed. Wiley, New York
                               [7] Gelfand AE, Smith AFM (1990) Sampling-based approaches to calcu-
                                   lating marginal densities. J Amer Stat Assoc 85:398–409

                               [8] Geman S, Geman D (1984) Stochastic relaxation, Gibbs distributions
                                   and the Bayesian restoration of images. IEEE Trans Pattern Anal
                                   Machine Intell 6:721–741
                               [9] Geyer CJ (1991) Markov chain Monte Carlo maximum likelihood.
                                   Computing Science and Statistics: Proceedings of the 23rd Symposium
                                   on the Interface, Keramidas EM, editor, Interface Foundation, Fairfax,
                                   VA pp 156–163
                              [10] Gilks WR, Richardson S, Spiegelhalter DJ, editors, (1996) Markov
                                   Chain Monte Carlo in Practice. Chapman and Hall, London
                              [11] Grimmett GR, Stirzaker DR (1992) Probability and Random Processes,
                                   2nd ed. Oxford University Press, Oxford
                              [12] Guo SW, Thompson EA (1992) A Monte Carlo method for combined
                                   segregation and linkage analysis. Amer J Hum Genet 51:1111–1126

                              [13] Hastings WK (1970) Monte Carlo sampling methods using Markov
                                   chains and their applications. Biometrika 57:97–109

                              [14] Jennison C (1993) Discussion on the meeting of the Gibbs sampler and
                                   other Markov chain Monte Carlo methods. J Roy Stat Soc B 55:54–56
   209   210   211   212   213   214   215   216   217   218   219