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| akj | Density estimation using adaptive kernel method |
| anova.rq | Anova function for quantile regression fits |
| anova.rqlist | Anova function for quantile regression fits |
| bandwidth.rq | bandwidth selection for rq functions |
| barro | Barro Data |
| boot.rq | Bootstrapping Quantile Regression |
| CobarOre | Cobar Ore data |
| coef.nlrq | Function to compute nonlinear quantile regression estimates |
| deviance.nlrq | Function to compute nonlinear quantile regression estimates |
| engel | Engel Data |
| fitted.nlrq | Function to compute nonlinear quantile regression estimates |
| formula.nlrq | Function to compute nonlinear quantile regression estimates |
| formula.rq | Linear Quantile Regression Object |
| khmaladze.test | Tests of Location and Location Scale Hypothesis for Linear Models |
| khmaladzize | Function to compute Khmaladze Transformation |
| 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 |
| lprq | locally polynomial quantile regression |
| Mammals | Garland(1983) Data on Running Speed of Mammals |
| nlrq | Function to compute nonlinear quantile regression estimates |
| nlrq.control | Set control parameters for nlrq |
| nlrqModel | Function to compute nonlinear quantile regression estimates |
| plot.qss1 | Default Ploting Method for rqss() |
| plot.qss2 | Default Ploting Method for rqss() |
| plot.rq.process | plot the coordinates of the quantile regression process |
| plot.rqss | Default Ploting Method for rqss() |
| plot.summary.rqs | plot the coordinates of the quantile regression process |
| plot.table.rq | Table of Quantile Regression Results |
| predict.nlrq | Function to compute nonlinear quantile regression estimates |
| predict.qss | Predict based on nonparametric quantile regression smoothing spline component |
| predict.qss1 | Predict based on nonparametric quantile regression smoothing spline component |
| predict.qss2 | Predict based on nonparametric quantile regression smoothing spline component |
| predict.rq | Quantile Regression Prediction |
| predict.rqs | Quantile Regression Prediction |
| print.anova.rq | Anova function for quantile regression fits |
| print.nlrq | Function to compute nonlinear quantile regression estimates |
| print.rq | Print an rq object |
| print.rqs | Print an rq object |
| print.summary.nlrq | Function to compute nonlinear quantile regression estimates |
| print.summary.rq | Print Quantile Regression Summary Object |
| print.summary.rqs | Print Quantile Regression Summary Object |
| qss | Additive Nonparametric Terms for rqss Fitting |
| qss1 | Additive Nonparametric Terms for rqss Fitting |
| qss2 | Additive Nonparametric Terms for rqss Fitting |
| ranks | Quantile Regression Ranks |
| 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.fn | Quantile Regression Fitting via Interior Point Methods |
| rq.fit.fnb | Quantile Regression Fitting via Interior Point Methods |
| rq.fit.fnc | Quantile Regression Fitting via Interior Point Methods |
| rq.fit.pfn | Preprocessing Algorithm for 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.rank | Anova function for quantile regression fits |
| rq.wfit | Function to choose method for Weighted Quantile Regression |
| rqProcess | Compute Quantile Regression Process |
| rqss | Additive Quantile Regression Smoothing |
| rrs.test | Quantile Regression Rankscore Test |
| standardize | Function to standardize the quantile regression process |
| summary.nlrq | Function to compute nonlinear quantile regression estimates |
| summary.rq | Summary methods for Quantile Regression |
| summary.rqs | Summary methods for Quantile Regression |
| table.rq | Table of Quantile Regression Results |
| tau.nlrq | Function to compute nonlinear quantile regression estimates |
| triogram.fidelity | Additive Nonparametric Terms for rqss Fitting |
| triogram.penalty | Additive Nonparametric Terms for rqss Fitting |
| untangle.specials | Additive Quantile Regression Smoothing |
| [.terms | Additive Quantile Regression Smoothing |