truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models. Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP. The package contains functions for the estimation of semi-parametric truncated linear regression models using three different estimators: the symmetrically trimmed least squares, quadratic mode, and left truncated estimators, all of which have been shown to have good asymptotic and finite sample properties. The package also provides functions for the analysis of the estimated models. Data from the environmental sciences are used to illustrate the functions in the package.
Keywords for this software
References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Kong, Cui-Juan; Liang, Han-Ying: Empirical likelihood of conditional quantile difference with left-truncated and dependent data (2020)
- Andriyana, Y.; Gijbels, I.; Verhasselt, A.: Quantile regression in varying-coefficient models: non-crossing quantile curves and heteroscedasticity (2018)
- Maria Karlsson, Anita Lindmark: truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models (2014) not zbMATH