# Code/Links

## COVID work

- Delphi Research Group at Carnegie Mellon University
- BC COVID-19 Modelling Group

## R packages for recent papers and publications

(See github/dajmcdon or my publications page for others)

- fkf:
**Fast Kalman Filter.**Very fast Kalman filtering and smoothing. - sparsegl
**Sparse Group Lasso.**Efficient implementation of sparse group lasso with optional bound constraints on the coefficients. It supports the use of a sparse design matrix as well as returning coefficient estimates in a sparse matrix. Furthermore, it correctly calculates the degrees of freedom to allow for information criteria rather than cross-validation with very large data. Finally, the interface to compiled code avoids unnecessary copies and allows for the use of long integers. - dpf:
**Discrete particle filtering.**This package greedily estimates switching Kalman filters*fast*. Also useful for analysis of musical tempos. - AIMER:
**Amplified, Initially Marginal, Eigenvector Regression.**As described in Ding, L. and McDonald, D.J., “Predicting phenotypes from microarrays using amplified, initially marginal, eigenvector regression”. A better version of supervised principal components analysis. - cplr:
**Compressed penalized linear regression.**As described in Homrighausen, D. and McDonald, D.J., “Compressed and penalized linear regression.”

## Random potentially useful stuff

- Beamer user guide
- Color scheme creator
- Advice for getting a job (potentially useful to non-statisticians)
- Minimal make files
- Nice LaTeX tables

## Resources for R and basic analysis

- R for Data Science, a nice textbook from Hadley Wickham
- Happy Git with R, good exposition on setting up and combining R and Git
- Basic text mining in R
- Fix common Github+R issues, the dreaded rpostback askpass error
- ggplot2
- My handout for Rmarkdown, see also Cosma’s version from which this derives
- My handout on Rmarkdown and parallel computing for my lab
- The batchtools package for easy cluster parallelization
- My (very brief) introduction to programming
- My (very brief) introduction to statistical graphics
- The official intro, “An Introduction to R”, available online in html and pdf
- My CSS template for presentations in R+slidy