Estimation and inference methods for models for conditional quantile functions:
Linear and nonlinear parametric and non-parametric (total variation penalized) models
for conditional quantiles of a univariate response and several methods for handling
censored survival data. Portfolio selection methods based on expected shortfall
risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press,
Versions of quantreg between 3.70 and 4.75 were removed from the CRAN archive due to uncertainties over the licensing status of the fortran code in src/cholesky.f. As of 9 March 2012, original authors of cholesky.f, Esmond Ng and Barry Peyton, have now, very kindly, given permission to use cholesky.f under an open source license. They have requested that their code be credited via the following two publications: Esmond G. Ng and Barry W. Peyton, "Block sparse Cholesky algorithms on advanced uniprocessor computers". SIAM J. Sci. Stat. Comput. 14 (1993), pp. 1034-1056. John R. Gilbert, Esmond G. Ng, and Barry W. Peyton, "An efficient algorithm to compute row and column counts for sparse Cholesky factorization". SIAM J. Matrix Anal. Appl. 15 (1994), pp. 1075-1091. Use of the sparse Cholesky code in cholesky.f in quantreg is limited to calls to rqss() or to rq with method = "sfn". In the event that readers wish to access the intermediate versions of quantreg that have been removed from CRAN, they will be available at: http://www.econ.uiuc.edu/~roger/research/rq/quantreg Current versions are best accessed from CRAN and its many mirrors.