Quantile Regression for Random Variables on the Unit Interval
Employs a two-parameter family of
distributions for modelling random variables on the (0, 1) interval by
applying the cumulative distribution function (cdf) of one parent
distribution to the quantile function of another.
News
cdfquantreg 1.2.0 (2018-02-12)
Provide censored cdf-quantile regression analysis
Provide zero-/one- inflated model(Hurdle Model)
cdfquantreg 1.1.3 (2017-08-15)
Optimize influence and dfbeta function for checking influencial cases.
Update the predict function.
Other minor improvement and bug fixes.
cdfquantreg 1.1.2 (2017-05-15)
Minor improvement and fixed some bugs.
cdfquantreg 1.1.1 (2017-01-22)
Minor improvement and fixed some bugs.
Fixed syntax errors in generating BUGS models.
cdfquantreg 1.1.0 (2016-11-22)
A total of 21 new distributions have been added! Check cdfqrFamily() or ?cdfqrFamily for more details of the newly added distributions.
Fixed minor issues in S3 generic method.
Fixed syntax errors in generating BUGS models.
cdfquantreg 1.0.5 (2016-08-16)
Fix error in producing variance covariance matrix
Add confint() for generating confidence intervals for the coefficients
cdfquantreg 1.0.4 (2016-04-05)
Update the package manual
Reclassify the shapes of different cdf distributions (see ?cdfqrFamily)
Fixed the bug in producing negative parameter estimation results and warning message when using the Kumaraswamy distribution
cdfquantreg 1.0.3 (2016-03-05)
Fixed bugs:
Fixed minor issues in output.
Fixed issues caused by extreme values (approching 0 or 1) in plotting the density function.
cdfquantreg 1.0.2 (2016-02-08)
Fixed bugs:
Fixed problems in calling arcsinh-X distributions.
Minor improvement for ploting user defined distributions in plot.cdfqr().
cdfquantreg 1.0.1 (2016-01-25)
Fixed bugs and minor improvements:
Fixed namespace issues relating to functions: rq(),qq() and pq().
Minor improvement for print.cdfqr() and summary.cdfqr().
Fixed the problem in qrBugs in handling data object when the provided model is a null model.
Improvement for plot.cdfqr() with additional plot of the fitted results.
Changed the naming of the precision model/coefficients (model $sigma$ of a distribution) to the dispersion model/coefficiets to reduce the confusion (as $sigma$ is a dispersion parameter).