Computational statistics.QA276 0-471-46124-5 Computational statistics. Givens, Geof and Jennifer A. Hoeting. Wiley-Interscience, [c]2005 418 p. $89.95 Givens and Hoeting (both: statistics, Colorado State U.) give graduate-level students a practical background in order to study bioinformatics, ecology, medicine, computer vision, and stochastic finance. They begin by reviewing mathematical and statistical notation, Taylor's theorem In calculus, Taylor's theorem, named after the mathematician Brook Taylor, who stated it in 1712, gives the approximation of a differentiable function near a point by a polynomial whose coefficients depend only on the derivatives of the function at that point. , mathematical and statistical limit theories, probability distributions, likelihood and Bayesian inferences, Markov chains and computing. They proceed to optimizing and solving nonlinear equations, combinatorial optimization, EM optimization methods, numerical integration, simulation and Monte Carlo integration In mathematics, Monte Carlo integration is numerical quadrature using pseudorandom numbers. That is, Monte Carlo integration methods are algorithms for the approximate evaluation of definite integrals, usually multidimensional ones. , Markov chain Monte Carlo Markov chain Monte Carlo (MCMC) methods (which include random walk Monte Carlo methods), are a class of algorithms for sampling from probability distributions based on constructing a Markov chain that has the desired distribution as its equilibrium distribution. (and advanced topics in the subject), bootstrapping Bootstrapping A procedure used to calculate the zero coupon yield curve from market figures. Notes: Since the T-bills offered by the government are not available for every time period, the bootstrapping method is used to fill in the missing figures in order to derive the , nonparametric density estimation, bivariate bi·var·i·ate adj. Mathematics Having two variables: bivariate binomial distribution. Adj. 1. smoothing, and multivariate smoothing. They include exercises with each chapter. |
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