A B C D E F G H I K L M N P Q R S T U misc
| AIC.nlrq | Function to compute nonlinear quantile regression estimates | 
| AIC.rq | Linear Quantile Regression Object | 
| AIC.rqs | Linear Quantile Regression Object | 
| AIC.rqss | RQSS Objects and Summarization Thereof | 
| akj | Density Estimation using Adaptive Kernel method | 
| anova.rq | Anova function for quantile regression fits | 
| anova.rqlist | Anova function for quantile regression fits | 
| anova.rqs | Anova function for quantile regression fits | 
| bandwidth.rq | bandwidth selection for rq functions | 
| barro | Barro Data | 
| boot.crq | Bootstrapping Censored Quantile Regression | 
| boot.rq | Bootstrapping Quantile Regression | 
| boot.rq.mcmb | Bootstrapping Quantile Regression | 
| boot.rq.pwxy | Preprocessing weighted bootstrap method | 
| boot.rq.pwy | Bootstrapping Quantile Regression | 
| boot.rq.pxy | Preprocessing bootstrap method | 
| boot.rq.spwy | Bootstrapping Quantile Regression | 
| boot.rq.wxy | Bootstrapping Quantile Regression | 
| boot.rq.xy | Bootstrapping Quantile Regression | 
| Bosco | Boscovich Data | 
| ChangeLog | FAQ and ChangeLog of a package | 
| CobarOre | Cobar Ore data | 
| coef.crq | Functions to fit censored quantile regression models | 
| coef.nlrq | Function to compute nonlinear quantile regression estimates | 
| combos | Ordered Combinations | 
| critval | Hotelling Critical Values | 
| crq | Functions to fit censored quantile regression models | 
| crq.fit.pen | Functions to fit censored quantile regression models | 
| crq.fit.por | Functions to fit censored quantile regression models | 
| crq.fit.por2 | Functions to fit censored quantile regression models | 
| crq.fit.pow | Functions to fit censored quantile regression models | 
| Curv | Functions to fit censored quantile regression models | 
| deviance.nlrq | Function to compute nonlinear quantile regression estimates | 
| dither | Function to randomly perturb a vector | 
| dynrq | Dynamic Linear Quantile Regression | 
| end.dynrq | Dynamic Linear Quantile Regression | 
| engel | Engel Data | 
| extractAIC.nlrq | Function to compute nonlinear quantile regression estimates | 
| extractAIC.rq | Linear Quantile Regression Object | 
| FAQ | FAQ and ChangeLog of a package | 
| fitted.nlrq | Function to compute nonlinear quantile regression estimates | 
| fitted.rqss | RQSS Objects and Summarization Thereof | 
| formula.nlrq | Function to compute nonlinear quantile regression estimates | 
| formula.rq | Linear Quantile Regression Object | 
| gasprice | Time Series of US Gasoline Prices | 
| Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| Hill.fit | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| index.dynrq | Dynamic Linear Quantile Regression | 
| KhmaladzeTest | Tests of Location and Location Scale Shift Hypotheses for Linear Models | 
| kselect | Quicker Sample Quantiles | 
| kuantile | Quicker Sample Quantiles | 
| kunique | Quicker Sample Quantiles | 
| LassoLambdaHat | Lambda selection for QR lasso problems | 
| latex | Make a latex version of an R object | 
| latex.summary.rqs | Make a latex table from a table of rq results | 
| latex.table | Writes a latex formatted table to a file | 
| latex.table.rq | Table of Quantile Regression Results | 
| lm.fit.recursive | Recursive Least Squares | 
| logLik.nlrq | Function to compute nonlinear quantile regression estimates | 
| logLik.rq | Linear Quantile Regression Object | 
| logLik.rqs | Linear Quantile Regression Object | 
| logLik.rqss | RQSS Objects and Summarization Thereof | 
| lprq | locally polynomial quantile regression | 
| Mammals | Garland(1983) Data on Running Speed of Mammals | 
| MelTemp | Daily maximum temperatures in Melbourne, Australia | 
| Munge | Munge rqss formula | 
| nlrq | Function to compute nonlinear quantile regression estimates | 
| nlrq.control | Set control parameters for nlrq | 
| nlrqModel | Function to compute nonlinear quantile regression estimates | 
| ParetoTest | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| Peirce | C.S. Peirce's Auditory Response Data | 
| Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| Pickands.fit | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| plot.KhmaladzeTest | Plot a KhmaladzeTest object | 
| plot.qss1 | Plot Method for rqss Objects | 
| plot.qss2 | Plot Method for rqss Objects | 
| plot.qts1 | Plot Method for rqss Objects | 
| plot.rq.process | plot the coordinates of the quantile regression process | 
| plot.rqs | Visualizing sequences of quantile regressions | 
| plot.rqss | Plot Method for rqss Objects | 
| plot.summary.crqs | Summary methods for Censored Quantile Regression | 
| plot.summary.rq | Visualizing sequences of quantile regression summaries | 
| plot.summary.rqs | Visualizing sequences of quantile regression summaries | 
| plot.summary.rqss | Plot Method for rqss Objects | 
| plot.table.rq | Table of Quantile Regression Results | 
| predict.crq | Functions to fit censored quantile regression models | 
| predict.crqs | Functions to fit censored quantile regression models | 
| predict.nlrq | Function to compute nonlinear quantile regression estimates | 
| predict.qss1 | Predict from fitted nonparametric quantile regression smoothing spline models | 
| predict.qss2 | Predict from fitted nonparametric quantile regression smoothing spline models | 
| predict.rq | Quantile Regression Prediction | 
| predict.rq.process | Quantile Regression Prediction | 
| predict.rqs | Quantile Regression Prediction | 
| predict.rqss | Predict from fitted nonparametric quantile regression smoothing spline models | 
| print.anova.rq | Anova function for quantile regression fits | 
| print.crq | Functions to fit censored quantile regression models | 
| print.dynrq | Dynamic Linear Quantile Regression | 
| print.dynrqs | Dynamic Linear Quantile Regression | 
| print.Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| print.KhmaladzeTest | Print a KhmaladzeTest object | 
| print.nlrq | Function to compute nonlinear quantile regression estimates | 
| print.Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| print.rq | Print an rq object | 
| print.rqs | Print an rq object | 
| print.rqss | RQSS Objects and Summarization Thereof | 
| print.summary.crq | Summary methods for Censored Quantile Regression | 
| print.summary.crqs | Summary methods for Censored Quantile Regression | 
| print.summary.dynrq | Dynamic Linear Quantile Regression | 
| print.summary.dynrqs | Dynamic Linear Quantile Regression | 
| print.summary.Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| print.summary.nlrq | Function to compute nonlinear quantile regression estimates | 
| print.summary.Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| print.summary.rq | Print Quantile Regression Summary Object | 
| print.summary.rqs | Print Quantile Regression Summary Object | 
| print.summary.rqss | Summary of rqss fit | 
| q489 | Even Quicker Sample Quantiles | 
| qrisk | Function to compute Choquet portfolio weights | 
| qss | Additive Nonparametric Terms for rqss Fitting | 
| qss1 | Additive Nonparametric Terms for rqss Fitting | 
| qss2 | Additive Nonparametric Terms for rqss Fitting | 
| QTECox | Function to obtain QTE from a Cox model | 
| qts1 | Additive Nonparametric Terms for rqss Fitting | 
| ranks | Quantile Regression Ranks | 
| rearrange | Rearrangement | 
| resid.rqss | RQSS Objects and Summarization Thereof | 
| residuals.nlrq | Return residuals of an nlrq object | 
| rq | Quantile Regression | 
| rq.fit | Function to choose method for Quantile Regression | 
| rq.fit.br | Quantile Regression Fitting by Exterior Point Methods | 
| rq.fit.conquer | Optional Fitting Method for Quantile Regression | 
| rq.fit.fnb | Quantile Regression Fitting via Interior Point Methods | 
| rq.fit.fnc | Quantile Regression Fitting via Interior Point Methods | 
| rq.fit.hogg | weighted quantile regression fitting | 
| rq.fit.lasso | Lasso Penalized Quantile Regression | 
| rq.fit.pfn | Preprocessing Algorithm for Quantile Regression | 
| rq.fit.pfnb | Quantile Regression Fitting via Interior Point Methods | 
| rq.fit.ppro | Preprocessing fitting method for QR | 
| rq.fit.qfnb | Quantile Regression Fitting via Interior Point Methods | 
| rq.fit.scad | SCADPenalized Quantile Regression | 
| rq.fit.sfn | Sparse Regression Quantile Fitting | 
| rq.fit.sfnc | Sparse Constrained Regression Quantile Fitting | 
| rq.object | Linear Quantile Regression Object | 
| rq.process.object | Linear Quantile Regression Process Object | 
| rq.test.anowar | Anova function for quantile regression fits | 
| rq.test.rank | Anova function for quantile regression fits | 
| rq.wfit | Function to choose method for Weighted Quantile Regression | 
| rqProcess | Compute Standardized Quantile Regression Process | 
| rqs.fit | Function to fit multiple response quantile regression models | 
| rqss | Additive Quantile Regression Smoothing | 
| rqss.fit | Additive Quantile Regression Smoothing | 
| rqss.object | RQSS Objects and Summarization Thereof | 
| sfn.control | Set Control Parameters for Sparse Fitting | 
| sfnMessage | Sparse Regression Quantile Fitting | 
| srisk | Markowitz (Mean-Variance) Portfolio Optimization | 
| start.dynrq | Dynamic Linear Quantile Regression | 
| summary.crq | Summary methods for Censored Quantile Regression | 
| summary.crqs | Summary methods for Censored Quantile Regression | 
| summary.dynrq | Dynamic Linear Quantile Regression | 
| summary.dynrqs | Dynamic Linear Quantile Regression | 
| summary.Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| summary.nlrq | Function to compute nonlinear quantile regression estimates | 
| summary.Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models | 
| summary.rcrqs | Summary methods for Quantile Regression | 
| summary.rq | Summary methods for Quantile Regression | 
| summary.rqs | Summary methods for Quantile Regression | 
| summary.rqss | Summary of rqss fit | 
| table.rq | Table of Quantile Regression Results | 
| tau.nlrq | Function to compute nonlinear quantile regression estimates | 
| time.dynrq | Dynamic Linear Quantile Regression | 
| triogram.fidelity | Additive Nonparametric Terms for rqss Fitting | 
| triogram.penalty | Additive Nonparametric Terms for rqss Fitting | 
| uis | UIS Drug Treatment study data | 
| untangle.specials | Additive Quantile Regression Smoothing | 
| [.terms | Additive Quantile Regression Smoothing |