Statistical Inference under the Multispecies Coalescent: Methods and TheoryGenetics.Statistics.The rising availability of genome-scale data for a large number of species has allowed for more in-depth studies of
In this work, we will focus on three intimately related factors that are often overlooked as a consequence of the aforementioned gap between theory and practice in network science: (1) The obscured quality of the data. (2) The choice of representation. (3) The suitability of the methods. W...
Probability Theory and Statistical Inference: Econometric Modeling with Observational Data. Cambridge University Press, Cambridge, 1999.A. Spanos . 1999. "Probability theory and statistical inference: Econometric modeling with observational data", .
The following topics are covered: distribution theory, principles of statistical inference, linear models, categorical data analysis, Bayesian approach, nonparametric methods. Extensive tables complete the text. Problems, exercises and their solutions are given at the end of each chapter which makes the...
Doubt over the trustworthiness of published empirical results is not unwarranted and is often a result of statistical mis-specification: invalid probabilistic assumptions imposed on data. Now in its second edition, this bestselling textbook offers a comprehensive course in empirical research methods, teac...
and define the likelihood ratio statistic Tn=2log(L1L0) where the notation indicates dependence on the the sample size n. Suppose the model satisfies the same regularity conditions as are needed for the asymptotic properties of the MLE— in particular, we require that L(θ) be at least...
Given two decision rules d and d′, we say d strictly dominates d′ if R(θ,d)≤R(θ,d′) for all values of θ, and R(θ,d)<R(θ,d′) for at least one θ. Any decision rule which is strictly dominated by another decision rule is said to be inadmissible. If a decision rul...
Natural computing for mechanical systems research: A tutorial overview 2011, Mechanical Systems and Signal ProcessingKeith Worden, ... James J. Hensman 6 Statistical learning theory and kernel methods 6.1 Structural risk minimisation The material of this section and the next has been discussed in con...
Peter Bühlmannis Professor of Statistics at ETH Zürich. His main research areas are high-dimensional statistical inference, machine learning, graphical modeling, nonparametric methods, and statistical modeling in the life sciences. He is currently editor of the Annals of Statistics. He was awarded a...
doi:10.1007/978-4-431-55978-8_7Shun-ichiAmariPrakasa Rao, B.L.S.: Asymptotic Theory of Statistical Inference, Wiley, New York, 1987.Prakasa Rao, B.L.S. (1987) Asymptotic Theory of Statistical Inference, Wiley, New York.