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 |