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Applied Regression Analysis - MATH5806 | ||||||||||||||||||||||||||||||||||||||
Description Introduction to flexible and modern approaches to statistical computing with strong emphasis on applications and computing. Linear and nonlinear models; ridge regression; nonparametric regression using kernel smoothers and smoothing splines; bandwidth selection for kernel smoothers; generalised linear models; generalised additive models; analysis of residuals; projection pursuit regression and principal component regression. Statistical packages include R.
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