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Statistical Modelling and Computing - MATH3821 | |||||||||||||||||||||||||||||||||||||||||||||||
Description Introduction to flexible and modern approaches to statistical modelling and statistical computing. Theory, applications and computation for linear models, generalised linear models, the Bayesian linear model, nonparametric regression using kernel smoothers and smoothing splines, nonparametric density estimation and bandwidth selection. Applications of simulation in statistical inference including Monte Carlo simulation, bootstrap methods, and Markov chain Monte Carlo. Statistical packages include R or Splus.
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