Tag Archives: lqmm

linear quantile mixed models and related software

Day on Quantile Regression at the Royal Statistical Society – London, 29 May

An exciting one-day meeting organized by the RSS General Applications Section will take place in London on 29th May 2013. In the morning, the workshop will have a tutorial in quantile regression with hands-on using the R package quantreg. The research session in the afternoon will have three excellent speakers. Full programme and registration details here.

I’ve uploaded lqmm 1.02 into CRAN. A few bugs have been fixed. I made a substantial change  to the function boot.lqmm which provides bootstrapped standard errors of the coefficients estimates. The starting values used in each bootstrap sample are by default those from a least squares fit (startQR = FALSE). In previous versions of the package, starting values were taken from the fitted object (startQR = TRUE) to speed up convergence in each bootstrap sample. However, this causes the standard errors to be under-estimated.

lqmm package

The lqmm package in on CRAN! This package provides commands for fitting linear quantile mixed models (LQMMs). LQMMs complement the mixed-effects models for the mean by providing estimation of conditional quantiles as function of fixed and random effects. More details can be found here and here. More posts on lqmm will follow but feel free to drop me a line if you want to know more.