Professor Lars Rönnegård
My curriculum vitae and contact information
My list of publications and some useful R code
Some presentations and courses I have given through the years
I am involved in an NIH-financed research project on genetics of fox behaviour and domestication led by Anna Kukekova at University of Illinois.
To find out more about the project take a look at the 10-minute presentation from Verge Science.
In 2017, I published a book Data Analysis Using Hierarchical Generalized Linear Models with R
, which I coauthored together with two of the most leading researchers in the field, prof Y. Lee and M. Noh. The book includes several data examples with accomponying R code using the packages developed by our research groups.
All the R code used in the book is available here and I have also made a first draft for a
blog based on the book.
I am a researcher and lecturer in the Statistics group at Dalarna University since April 2008 (professor since 2012). I am also a guest professor at the Dep. of Animal Breeding and Genetics at SLU, Uppsala. In 2016, I was appointed the position as Dean of Dalarna University.
I was a postdoctoral researcher in the Carlborg lab at the Linnaeus Centre for Bioinformatics April 2005 till March 2008.
I defended my PhD in March 2003, at the Swedish University of Agricultural Sciences, Uppsala, on the subject "Selection, Maternal Effects and Inbreeding in Reindeer Husbandry". My thesis includes theoretical and applied papers in both ecology and animal genetics. Part of my research was made in collaboration with prof. J.A. Woolliams at Roslin Institute, Edinburgh. After my PhD I was appointed Head of Statistics at Dalarna University and I was responsible for the development of a new Master Program in Statistics. During this time (2003-2005) I collaborated with the research department at Sveriges Riksbank, which resulted in a novel paper on capital risk assessment.
Version 2.0 of the hglm package is available, including: spatial modelling, new model selection tools, possibility to add linear predictors for the random effect variances.
Together with my colleagues I have developed the R package hglm which fits Hierarchical Generalized Linear Models, i.e. generalized linear models with random effects. See plot of number of downloads per day from CRAN in 2015 and Andrew Gelman's review here.
I have developed the RepeatABEL package , which extends the GenABEL package to allow repeated observations per individual and uses the hglm package for fast computations.
I have also implemented my vQTL methodology in the scanonevar function in Karl Broman's package R/qtl