COVID work

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

Resources for R and basic analysis

Color scheme for presentations etc.


Daniel J. McDonald © 2022. All rights reserved.

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