This is a lower level routine called by rq() to compute quantile regression methods using the Frisch-Newton algorithm. It allows the call to specify linear inequality constraints to which the fitted coefficients will be subjected. The constraints are assumed to be formulated as Rb >= r.
● Data Source:
CranContrib
● Keywords: regression
● Alias: rq.fit.fnc
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plot.rqss
(Package: quantreg) :
Plot Method for rqss Objects
Takes a fitted rqss object produced by rqss() and plots the component smooth functions that make up the ANOVA decomposition. Since the components "omit the intercept" the estimated intercept is added back in – this facilitates the comparison of quantile fits particularly. For models with a partial linear component or several qss components it may be preferable to plot the output of predict.rqss. Note that these functions are intended to plot rqss objects only, attempting to plot summary.rqss objects just generates a warning message.
● Data Source:
CranContrib
● Keywords: iplot, regression, smooth
● Alias: plot.qss1, plot.qss2, plot.rqss, plot.summary.rqss
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qss
(Package: quantreg) :
Additive Nonparametric Terms for rqss Fitting
In the formula specification of rqss nonparametric terms are specified with qss. Both univariate and bivariate specifications are possible, and qualitative constraints may also be specified for the qss terms.
● Data Source:
CranContrib
● Keywords: robust, smooth
● Alias: qss, qss1, qss2, triogram.fidelity, triogram.penalty
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plot.summary.rqs
(Package: quantreg) :
Visualizing sequences of quantile regression summaries
A sequence of coefficient estimates for quantile regressions with varying tau parameters is visualized along with associated confidence bands.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: plot.summary.rqs
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These are objects of class "rq". They represent the fit of a linear conditional quantile function model.
● Data Source:
CranContrib
● Keywords: regression
● Alias: AIC.rq, AIC.rqs, extractAIC.rq, formula.rq, logLik.rq, logLik.rqs, rq.object
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plot.rq
(Package: quantreg) :
plot the coordinates of the quantile regression process
Function to plot quantile regression process.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: plot.rq.process
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KhmaladzeTest
(Package: quantreg) :
Tests of Location and Location Scale Shift Hypotheses for Linear Models
Tests of the hypothesis that a linear model specification is of the location shift or location-scale shift form. The tests are based on the Doob-Meyer Martingale transformation approach proposed by Khmaladze(1981) for general goodness of fit problems, and adapted to quantile regression by Koenker and Xiao (2002).
● Data Source:
CranContrib
● Keywords: htest
● Alias: KhmaladzeTest, khmaladzize, qdensity
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combos
(Package: quantreg) :
Ordered Combinations
All m combinations of the first n integers taken p at a time are computed and return as an p by m matrix. The columns of the matrix are ordered so that adjacent columns differ by only one element. This is just a reordered version of combn in base R, but the ordering is useful for some applications.
● Data Source:
CranContrib
● Keywords: utilities
● Alias: combos
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akj
(Package: quantreg) :
Density Estimation using Adaptive Kernel method
Univariate adaptive kernel density estimation a la Silverman. As used by Portnoy and Koenker (1989).
● Data Source:
CranContrib
● Keywords: smooth
● Alias: akj
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latex
(Package: quantreg) :
Make a latex version of an R object
Generic function for converting an R object into a latex file.
● Data Source:
CranContrib
● Keywords: IO
● Alias: latex
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providing 
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