1.0
* Added support for L2 penalization(alpha=0);
* hqreg: changed argument "loss" to "method" and an option "squared" to "ls".
1.1
* loss.hqreg.R: corrected a mistake in function "qloss".
1.2
* cv.hqreg: added two new arguments, "fold.id" for predefined cross-validation
folds, and "type.measure" for inclusion of general error measures "mse" and
"mae".
* loss.hqreg: modified definition depending on "type.measure".
1.3
* cv.hqreg: enabled parallel computing for cross-validation with a new argument "ncores"
* hqreg: set the default value of "gamma" for Huber loss to be IQR(y)/10
* plot.hqreg, plot.cv.hqreg: changed argument "log.x" to "log.l"
* removed computational redundancy and reduced memory allocation in source code
* corrected typos in documentation
1.4
* new function "hqreg_raw" for fitting models on raw data without preprocessing
* hqreg_raw contains a boolean argument "intercept" which can be set to FALSE to allow a "no-intercept" fit
* hqreg: no longer support preprocess = "none" since the package now has a specific function hqreg_raw for that situation
* modified plot, predict function accordingly for the situation without an intercept
* cv.hqreg: added a new argument FUN that take values from either "hqreg" or "hqreg_raw" to include cross validation
functionality for hqreg_raw
* robustified the optimization algorithm for extreme cases in quantile regression when tau is close to 0 or 1