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* Changes in quantregGrowth *
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version 0.3-0
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* Multiple ps() terms (with known lambda) are allowed in gcrq().
* plot.gcrq() gains argument 'term' to specify which smooth relationship to plot.
* gcrq() gains argument 'eps' to tune the distance between the fitted curves.
* ncross.rq.fitB() deleted; now ncross.rq.fitXB() makes the necessary job.
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version 0.2-0 (not on CRAN)
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* Nonparametric bootstrap resampling introduced (argument 'n.boot' in gcrq()).
* Methods summary.gcrq() and vcov.gcrq() introduced to return var-cov matrices based on bootstrap.
* Some very minor changes in plot.gcrq() to better control graphical display (when cv=TRUE)
* Some bugs fixed: gcrq() was not working with factors included in the linear predictor;
plot.gcrq() was not working for models including linear terms; the lambda set in ps() is now really lambda (it was actually sqrt(lambda)).
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version 0.1-3
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* Argument 'transf' added to cgrq() and plot.gcrq(). This argument can be useful when modelling bounded oucomes (whereby monotone transformations could be employed).
* The returned "gcrq" object now also includes 'fitted.values' and 'residuals'.
* gcrq() was not working with values of tau always greater than .5 (or always less then .5); also a single value of tau was not allowed.
* The objective values for taus < 0.5 returned in the 'rho' component of the fitted "gcrq" object were wrong.
* Some minor graphical arguments added to plot.gcrq() to better control graphical display.
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version 0.1-2
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* Argument 'interc' added to cgrq() to include B-splines and the model intercept.
* Some bugs fixed: gcrq() was not working with formulas such as 'gcrq(y~0+x)';
the component info.smooth was not correctly named in "gcrq" objects causing troubles
with predictQR() (thanks to Oscar Camacho for finding the error)
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version 0.1-1
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* First public release on CRAN