Estimation for General Birth-Death Processes
暂无分享,去创建一个
Marc A Suchard | Forrest W. Crawford | Forrest W Crawford | Vladimir N Minin | M. Suchard | F. Crawford | V. Minin
[1] Sean Nee,et al. Birth-Death Models in Macroevolution , 2006 .
[2] S. Lahiri,et al. Density estimation in high and ultra high dimensions, regularization, and the L1 asymptotics , 2012 .
[3] G. Denardo,et al. Antilymphoma effects of anti-HLA-DR and CD20 monoclonal antibodies (Lym-1 and Rituximab) on human lymphoma cells. , 2004, Cancer biotherapy & radiopharmaceuticals.
[4] Marc A Suchard,et al. Fitting Birth-Death Processes to Panel Data with Applications to Bacterial DNA Fingerprinting. , 2010, The annals of applied statistics.
[5] I. Ibragimov,et al. On Sequential Estimation , 1975 .
[6] J. Felsenstein,et al. An evolutionary model for maximum likelihood alignment of DNA sequences , 1991, Journal of Molecular Evolution.
[7] Eric Renshaw,et al. Stochastic Population Processes: Analysis, Approximations, Simulations , 2011 .
[8] P. Green. On Use of the EM Algorithm for Penalized Likelihood Estimation , 1990 .
[9] Eric Renshaw,et al. Stochastic Population Processes , 2011 .
[10] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1967 .
[11] Will Tribbey,et al. Numerical Recipes: The Art of Scientific Computing (3rd Edition) is written by William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery, and published by Cambridge University Press, © 2007, hardback, ISBN 978-0-521-88068-8, 1235 pp. , 1987, SOEN.
[12] R. Sibly,et al. Likelihood-based estimation of microsatellite mutation rates. , 2003, Genetics.
[13] W J Lentz,et al. Generating bessel functions in mie scattering calculations using continued fractions. , 1976, Applied optics.
[14] A. Hobolth,et al. Statistical Applications in Genetics and Molecular Biology Statistical Inference in Evolutionary Models of DNA Sequences via the EM Algorithm , 2011 .
[15] Norman T. J. Bailey. The Elements of Stochastic Processes with Applications to the Natural Sciences , 1964 .
[16] Annie A. M. Cuyt,et al. Handbook of Continued Fractions for Special Functions , 2008 .
[17] I. Meilijson. A fast improvement to the EM algorithm on its own terms , 1989 .
[18] H. Ellegren,et al. Microsatellite evolution inferred from human– chimpanzee genomic sequence alignments , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[19] Ward Whitt,et al. Numerical Inversion of Laplace Transforms of Probability Distributions , 1995, INFORMS J. Comput..
[20] Tushar M. Goradia,et al. Multi-stage Markov analysis of progressive disease applied to melanoma , 1993 .
[21] Xiao-Li Meng,et al. Using EM to Obtain Asymptotic Variance-Covariance Matrices: The SEM Algorithm , 1991 .
[22] James D. Murray. Mathematical Biology: I. An Introduction , 2007 .
[23] David M. Young,et al. Conjugate Gradient Acceleration , 1981 .
[24] B. Roehner,et al. Application of Stieltjes theory for S-fractions to birth and death processes , 1983, Advances in Applied Probability.
[25] Mark M. Tanaka,et al. Estimating change rates of genetic markers using serial samples: applications to the transposon IS6110 in Mycobacterium tuberculosis. , 2003, Theoretical population biology.
[26] J. Kalbfleisch,et al. The Analysis of Panel Data under a Markov Assumption , 1985 .
[27] J. Reynolds,et al. ON ESTIMATING THE PARAMETERS OF A BIRTH-DEATH PROCESS , 1973 .
[28] Ian Holmes,et al. Evolutionary HMMs: a Bayesian approach to multiple alignment , 2001, Bioinform..
[29] P. A. P. Moran,et al. An introduction to probability theory , 1968 .
[30] H. Wall,et al. Analytic Theory of Continued Fractions , 2000 .
[31] I Holmes,et al. An expectation maximization algorithm for training hidden substitution models. , 2002, Journal of molecular biology.
[32] Mukarram Ahmad,et al. Continued fractions , 2019, Quadratic Number Theory.
[33] Haakon Waadeland,et al. Continued fractions with applications , 1994 .
[34] Chuanhai Liu,et al. Information matrix computation from conditional information via normal approximation , 1998 .
[35] M. Bladt,et al. Statistical inference for discretely observed Markov jump processes , 2005 .
[36] Ward Whitt,et al. Computing Laplace Transforms for Numerical Inversion Via Continued Fractions , 1999, INFORMS J. Comput..
[37] R. Durrett,et al. Equilibrium distributions of microsatellite repeat length resulting from a balance between slippage events and point mutations. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[38] W. Amos. Mutation Biases and Mutation Rate Variation Around Very Short Human Microsatellites Revealed by Human–Chimpanzee–Orangutan Genomic Sequence Alignments , 2010, Journal of Molecular Evolution.
[39] William B. Jones,et al. APPLICATION OF STIELTJES FRACTIONS TO BIRTH-DEATH PROCESSES , 1977 .
[40] Chuanhai Liu,et al. The dynamic ‘expectation–conditional maximization either’ algorithm , 2012 .
[41] Eugene V. Koonin,et al. Biological applications of the theory of birth-and-death processes , 2005, Briefings Bioinform..
[42] F. J. Anscombe,et al. Topics in the Investigation of Linear Relations Fitted by the Method of Least Squares , 1967 .
[43] D. Oakes. Direct calculation of the information matrix via the EM , 1999 .
[44] P. A. P. Moran,et al. Estimation Methods for Evolutive Processes , 1951 .
[45] D N Stivers,et al. Relative mutation rates at di-, tri-, and tetranucleotide microsatellite loci. , 1997, Proceedings of the National Academy of Sciences of the United States of America.
[46] Hua Zhou,et al. Graphics Processing Units and High-Dimensional Optimization. , 2010, Statistical science : a review journal of the Institute of Mathematical Statistics.
[47] S. Tyekucheva,et al. The genome-wide determinants of human and chimpanzee microsatellite evolution. , 2007, Genome research.
[48] P. R. Parthasarathy,et al. Exact transient solution of a state-dependent birth-death process , 2006 .
[49] C. Crainiceanu,et al. Fast Adaptive Penalized Splines , 2008 .
[50] Kenneth Lange,et al. Numerical analysis for statisticians , 1999 .
[51] G. Denardo. Concepts in radioimmunotherapy and immunotherapy: Radioimmunotherapy from a Lym-1 perspective. , 2005, Seminars in oncology.
[52] Ernst Joachim Weniger,et al. Nonlinear sequence transformations for the acceleration of convergence and the summation of divergent series , 1989 .
[53] P. Moran,et al. THE ESTIMATION OF THE PARAMETERS OF A BIRTH AND DEATH PROCESS. , 1953 .
[54] H. Andersson,et al. Stochastic Epidemic Models and Their Statistical Analysis , 2000 .
[55] Samuel Karlin,et al. The classification of birth and death processes , 1957 .
[56] H. Ellegren. Microsatellites: simple sequences with complex evolution , 2004, Nature Reviews Genetics.
[57] R. Durrett,et al. Dinucleotide repeats in the Drosophila and human genomes have complex, length-dependent mutation processes. , 2003, Molecular biology and evolution.
[58] Stephen M. Krone,et al. Ancestral Processes with Selection , 1997, Theoretical population biology.
[59] Niels Keiding,et al. Estimation in the birth process , 1974 .
[60] A. Bhargava,et al. Mutational Dynamics of Microsatellites , 2010, Molecular biotechnology.
[61] A. Jensen,et al. Markoff chains as an aid in the study of Markoff processes , 1953 .
[62] Asger Hobolth,et al. SIMULATION FROM ENDPOINT-CONDITIONED, CONTINUOUS-TIME MARKOV CHAINS ON A FINITE STATE SPACE, WITH APPLICATIONS TO MOLECULAR EVOLUTION. , 2009, The annals of applied statistics.
[63] C. Schlötterer. Evolutionary dynamics of microsatellite DNA , 2000, Chromosoma.
[64] B. Dujon,et al. Comparative Genomics and Molecular Dynamics of DNA Repeats in Eukaryotes , 2008, Microbiology and Molecular Biology Reviews.
[65] Niels Keiding. Maximum Likelihood Estimation in the Birth-and-Death Process , 1975 .
[66] R. Jennrich,et al. Conjugate Gradient Acceleration of the EM Algorithm , 1993 .
[67] Fabrice Guillemin,et al. Excursions of birth and death processes, orthogonal polynomials, and continued fractions , 1999, Journal of Applied Probability.
[68] R M May,et al. The reconstructed evolutionary process. , 1994, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[69] D. Rubin,et al. The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence , 1994 .
[70] Charles Elkan,et al. Expectation Maximization Algorithm , 2010, Encyclopedia of Machine Learning.
[71] James C. Frauenthal,et al. Stochastic Epidemic Models , 1980 .
[72] R. Page,et al. Rates and patterns of gene duplication and loss in the human genome , 2005, Proceedings of the Royal Society B: Biological Sciences.
[73] David Levin,et al. Development of non-linear transformations for improving convergence of sequences , 1972 .
[74] Jeffery P. Demuth,et al. The Evolution of Mammalian Gene Families , 2006, PloS one.
[75] P. A. P. Moran,et al. Random processes in genetics , 1958, Mathematical Proceedings of the Cambridge Philosophical Society.
[76] D. Falush,et al. A threshold size for microsatellite expansion. , 1998, Molecular biology and evolution.
[77] Fabrice Guillemin,et al. Continued Fraction Analysis of the Duration of an Excursion in an M/M/∞ System , 1998, Journal of Applied Probability.
[78] Ward Whitt,et al. The Fourier-series method for inverting transforms of probability distributions , 1992, Queueing Syst. Theory Appl..
[79] J. Kingman. On the genealogy of large populations , 1982, Journal of Applied Probability.
[80] K. Lange. A gradient algorithm locally equivalent to the EM algorithm , 1995 .
[81] Charles R. Doss,et al. Great Expectations: EM Algorithms for Discretely Observed Linear Birth-Death-Immigration Processes , 2010 .
[82] T. Moon. The expectation-maximization algorithm , 1996, IEEE Signal Process. Mag..
[83] J. H. Darwin. THE BEHAVIOUR OF AN ESTIMATOR FOR A SIMPLE BIRTH AND DEATH PROCESS , 1956 .
[84] W. Amos,et al. Quantifying ascertainment bias and species-specific length differences in human and chimpanzee microsatellites using genome sequences. , 2006, Molecular biology and evolution.
[85] A. Hobolth,et al. Summary Statistics for Endpoint-Conditioned Continuous-Time Markov Chains , 2011, Journal of Applied Probability.
[86] G. Blanch,et al. Numerical Evaluation of Continued Fractions , 1964 .
[87] S. Karlin,et al. The differential equations of birth-and-death processes, and the Stieltjes moment problem , 1957 .
[88] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[89] Jean-Yves Dauxois,et al. Bayesian inference for linear growth birth and death processes , 2004 .
[90] W. Leighton,et al. Numerical Continued Fractions , 1942 .
[91] Ronald W. Wolff,et al. Problems of Statistical Inference for Birth and Death Queuing Models , 1965 .
[92] Ward Whitt,et al. Numerical inversion of probability generating functions , 1992, Oper. Res. Lett..
[93] Asger Hobolth,et al. A Markov chain Monte Carlo Expectation Maximization Algorithm for Statistical Analysis of DNA Sequence Evolution with Neighbor-Dependent Substitution Rates , 2008 .
[94] Raazesh Sainudiin,et al. Microsatellite Mutation Models , 2004, Genetics.
[95] Feller William,et al. An Introduction To Probability Theory And Its Applications , 1950 .
[96] P. Flajolet,et al. The formal theory of birth-and-death processes, lattice path combinatorics and continued fractions , 2000, Advances in Applied Probability.
[97] Forrest W. Crawford,et al. Transition probabilities for general birth–death processes with applications in ecology, genetics, and evolution , 2011, Journal of Mathematical Biology.
[98] Christof Schütte,et al. Generator estimation of Markov jump processes , 2007, J. Comput. Phys..
[99] A. R. Barnett,et al. Coulomb and Bessel functions of complex arguments and order , 1986 .
[100] L. Beckett,et al. On the analysis of count data of birth‐and‐death process type: with application to molecularly targeted cancer therapy , 2007, Statistics in medicine.
[101] William B. Jones,et al. A survey of truncation error analysis for Padé and continued fraction approximants , 1993 .
[102] J. Staněk,et al. Stochastic Epidemic Models , 2006 .
[103] W. Press,et al. Numerical Recipes: The Art of Scientific Computing , 1987 .
[104] J. A. Murhy,et al. Some Properties of Continued Fractions with Applications in Markov Processes , 1975 .
[105] T. Louis. Finding the Observed Information Matrix When Using the EM Algorithm , 1982 .
[106] K. Eckert,et al. Every microsatellite is different: Intrinsic DNA features dictate mutagenesis of common microsatellites present in the human genome , 2009, Molecular carcinogenesis.
[107] Kurt Hornik,et al. The Comprehensive R Archive Network , 2012 .
[108] Marc A Suchard,et al. Counting labeled transitions in continuous-time Markov models of evolution , 2007, Journal of mathematical biology.