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Single-index quantile regression models are important tools in semiparametric regression to provide a comprehensive view of the conditional distributions of a response variable. This methods is especially useful when the data is heterogeneous or heavy tailed.
We provides functions that allow users to fit Single-Index Quantile Regression model via an efficient iterative local linear approach. It also provides functions to do prediction, estimate standard errors of the single-index coefficients via bootstrap, and visualize the estimated univariate function. Please see W., Y., Y. (2010) at here for details.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.