## CV, publication list and general information

Link to my Iris page

List of publications

## Software

Link to the latest version of our R package
'mia' (Statistical Modelling and Radiomics Tools for Medical
Imaging Analysis).

To install the
package, run these instructions within R:

library(devtools)

install_github("ericwol/mia")

library(mia)

## Teaching (2019-20)

- ST2001 / Introduction to Biostatistics

- ST4060 / Computer Intensive Statistical Analytics I

- ST4061 / Computer Intensive Statistical Analytics II

- ST6015 / Computer Analytical Techniques for Actuarial Applications

- ST6041 / Statistical Analytics Implementations II

- ST4090 / Current Topics in Statistics I - TBC

## Some resources about R, computational statistics and statistical learning

### + Keeping up

Follow Hadley Wickham himself or check out his website...

Arthur Charpentier's blog and Twitter...

... and find your own track from there.

### + Some books with online resources

The Elements of Statistical Learning by Hastie, Tibshirani
and Friedman

Introduction to Statistical Learning by James, Witten,
Hastie and Tibshirani

"Time Series Analysis and Its Applications: With R
Examples" by Schumway and Stoffer

Arthur Charpentier's
"Computational Actuarial Science With R"

### + Official CRAN resources for R

The R Project:
http://cran.r-project.org/

Introduction to R (html):
http://cran.r-project.org/doc/manuals/R-intro.html

Introduction to R (pdf):
http://cran.r-project.org/doc/manuals/R-intro.pdf

Introduction to the R language:
http://cran.r-project.org/doc/manuals/R-lang.html

### + Other online tutorials and helpful links

Freakonometrics points to 2 minute-long
video tutorials:
http://freakonometrics.hypotheses.org/9069

With statistical examples:
http://www.cyclismo.org/tutorial/R/

With more advanced statistical examples:
http://www.r-tutor.com/

Another presentation of R with interesting links: https://www.guru99.com/r-tutorial.html

R or Python???
An infographic (2015)

Advanced R with C/C++ integration:
"Advanced R" by Hadley Wickham

This paper:
A great introduction to Rcpp by its authors Douglas Bates and Dirk Eddelbuettel

See also
this post on fast linear modeling...

Useful if using Rcpp:
C++ Armadillo library

Also useful if using Rcpp:
Rcpp's gallery!

Advanced R memory usage:
"Advanced R" by Hadley Wickham (again!)

Also to speed things up:
Parallel Programming with GPUs and R

Also on memory usage:
A useful overview by Matthew C Keller

On cmpfun(), R's compiler, and R code profiling:
an illustrated guide by Noam Ross

Freakonometrics:
http://freakonometrics.hypotheses.org

Addicted to R's great library on R graphics:
"Improving-the-graph-gallery"

A good talk about R:
The R Language The Good The Bad And The Ugly - John Cook

Lots and lots of interesting posts on 'Revolutions':
(Must still get my head around that one!)

For some more exotic stuff:
http://blog.r-enthusiasts.com/ (used to be at http://romainfrancois.blog.free.fr)

A UNIX-oriented approach:
http://zoonek2.free.fr/UNIX/48_R/01.html