Flexible Regression in R

Q-Step is a £19.5 million programme designed to promote a step-change in quantitative social science training. Over a five-year period from 2013, fifteen universities across the UK are delivering specialist undergraduate programmes, including new courses, work placements and pathways to postgraduate study. Expertise and resources will be shared across the higher education sector through an accompanying support programme, which will also forge links with schools and employers.

Glasgow Q Step Centre

This short course will introduce techniques for non-linear regression in R.

Dr. Marnie LowSchool of Mathematics and StatisticsIn this session I will introduce flexible regression methods. The local nature of these methods allows us to effectively model complex non-linear relationships that are often present in data from a variety of backgrounds including environmental and health data. I will introduce and compare different nonparametric regression approaches for handling these complex relationships and show how we can combine multiple non-linear covariates into one model. Often our response variable is not normally distributed and thus I will also cover modelling data with a non-normal response e.g. a binary “survived” response.

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Flexible Regression in R

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Flexible Regression in R

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