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CPD120: Online workshop - Semiparametric regression with R

  • 30 Sep 2020
  • 11:00 AM
  • 2 Oct 2020
  • 1:00 PM
  • via Zoom
  • 11


  • Registration and payment before 1 September 2020

    Please send proof of your full-time student status to
  • Registration and payment before 1 September 2020
  • Registration and payment before 1 September 2020
  • Registration and payment before 1 September 2020
  • Registration and payment from 1 September 2020

    Please email proof of full-time student status to
  • Registration and payment from 1 September 2020
  • Registration and payment from 1 September 2020
  • Registration and payment from 1 September 2020

Registration is closed

Please join us for the following online workshop

Semiparametric Regression with R

to be held over three days:

11:00am-1:00pm (Australian Eastern Standard Time) Wednesday 30th September 2020

11:00am-1:00pm (Australian Eastern Standard Time) Thursday 1st October 2020

11:00am-1:00pm (Australian Eastern Standard Time) Friday 2nd October 2020

About the presenter

Matt P. Wand is a Distinguished Professor of Statistics at the University of Technology Sydney. He has held faculty appointments at Harvard University, Rice University, Texas A&M University, the University of New South Wales and the University of Wollongong. Professor Wand is an elected fellow of the Australian Academy of Science, the American Statistical Association and the Institute of Mathematical Statistics. He was awarded two of the Australian Academy of Science's medals for statistical research: the Moran Medal in 1997 and the Hannan Medal in 2013. In 2014 he was awarded the Statistical Society of Australia's Pitman Medal. He has served as an associate editor for several journals including Biometrika, Journal of the American Statistical Association and Statistica Sinica. He has co-authored 2 books, more than 120 journal articles and 6 R packages on semiparametric regression and related areas.

Further details about Professor Wand’s research, and every paper he has written, are on the website.

About the course

Semiparametric regression methods build on parametric regression models by allowing more flexible relationships between the predictors and the response variables. Examples of semiparametric regression include generalized additive models, additive mixed models and spatial smoothing. The presenter's goal is to provide an easy-to-follow applied course on semiparametric regression methods using R. There is a vast literature on the semiparametric regression methods. However, most of it is geared towards researchers with advanced knowledge of statistical methods. This course is intended for applied statistical analysts who have some familiarity with R.

This short course explains the techniques and benefits of semiparametric regression in a concise and modular fashion. Spline functions, linear mixed models and Bayesian hierarchical models are shown to play an important role in semiparametric regression. There will be a strong emphasis on implementation in R and rstan with most of the short-course spent doing computing exercises.

The workshop is based on the in-press book “Semiparametric Regression with R” by  J. Harezlak, D. Ruppert and M.P. Wand (Springer, 2018), with website, and has the companion methodology and theory book “Semiparametric Regression” by D. Ruppert, M.P. Wand and R.J. Carroll (Cambridge University Press, 2003), with website.

Target Audience

Most of the course will be geared towards researchers with intermediate to advanced knowledge of statistical, particularly regression, methods.

Learning Objectives

1. Introduction to semiparametric regression at the applied level

2. Implementation of the presented methods in R and rstan

3. Application of the newly learned methods to a variety of datasets


Early Bird rates (Registration and payment before 1 September)

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Rates from 1 September 

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Cancellation Policy

Cancellations received prior to Wednesday, 23 September 2020 will be refunded, minus a $25 administration fee.

From then onwards no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to

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