Utilities for Quantiles
Transformations
Mid-distribution Functions
Extract Coefficients
Extract Coefficients
Extract Coefficients
Extract Coefficients
Mid-distribution Functions
Directional Quantile Classification
Control parameters for dqc estimation
Extract Fitted Values from Mid-Quantile Transformation Models
Extract Fitted Values from Quantile Regression Models for Counts
Extract Fitted Values from Quantile Regression Transformation Models
Goodness-of-Fit Tests for Quantile Regression Models
Khmaladze Test
Marginal Effects
QR-based Multiple Imputation
Recover Ordinary Conditional Quantiles from Conditional Mid-Quantiles
Mid-distribution Functions
Mid-Quantile Regression for Discrete Responses
Control parameters for midrq estimation
Control parameters for gradient search estimation
Plot Quantile Functions
Plot Mid-distribution Functions
Quantile-based Summary Statistics for Location, Scale and Shape
Predictions from Mid-Quantile Regression Models
Predictions from Conditional LSS Objects
Predictions from Quantile Ratio Regression Models
Predictions from rq.counts Objects
Predictions from Quantile Regression Transformation Models
Predictions from Restricted Quantile Regression Models
Print Mid-distribution Functions
Print Directional Quantile Classification Objects
Print Goodness-of-Fit Test for Quantile Regression Models
Print Mid-distribution Functions
Print Mid-Quantile Models
Print Quantile-based Summary Statistics for Location, Scale and Shape
Print Quantile Ratio Regression Models
Print rq.counts
Print Transformation Models
Print Restricted Quantile Regression Models
Exact Confidence Intervals for Quantiles
Quantile-based Summary Statistics for Location, Scale and Shape
Quantile Ratio Regression
Internal Qtools objects
Utilities for Quantilies
Residuals from a midrq Objects
Residuals from an rq.counts Object
Residuals from an rqt Objects
Quantile Regression for Counts
Restricted Regression Quantiles
Sparsity Estimation
Summary for Mid-Quantile Regression Models
Summary for Quantile Ratio Regression Models
Summary for Quantile Regression Tranformation Models
Summary for Restricted Quantile Regression Models
Quantile Regression Transformation Models
Variance-Covariance Matrix for a Fitted Mid-Quantile Regression Model ...
Variance-Covariance Matrix for a Fitted Quantile Ratio Regression Mode...
Functions for unconditional and conditional quantiles. These include methods for transformation-based quantile regression, quantile-based measures of location, scale and shape, methods for quantiles of discrete variables, quantile-based multiple imputation, restricted quantile regression, directional quantile classification, and quantile ratio regression. A vignette is given in Geraci (2016, The R Journal) <doi:10.32614/RJ-2016-037> and included in the package.