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...
In this paper we illustrate the use of alternative truncated regression estimators for the general l...
Truncated distributions arise naturally in many practical situations. In this note, we provide progr...
Truncated sample arise when one do not observe a certain segment of a population. This typically hap...
Problems with truncated data occur in many areas, complicating estimation and inference. Regarding l...
Problems with truncated data occur in many areas, complicating estimation and inference. Regarding l...
This thesis contributes in several ways to the existing knowledge on estimation of truncated, censor...
This article provides a semi parametric method for the estimation of truncated regression models wh...
This paper deals with the estimation of conditional quantiles of linear truncated regression models ...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
Semiparametric regression is a combination of parametric and semiparametric regression. This regress...
This paper considers estimation of truncated.and censored regression models with fixed effects. Up u...
Estimation in the linear regression model Y = beta'Z + epsilon is considered for the left trunc...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
In this paper we illustrate the use of alternative truncated regression estimators for the general l...
Truncated distributions arise naturally in many practical situations. In this note, we provide progr...
Truncated sample arise when one do not observe a certain segment of a population. This typically hap...
Problems with truncated data occur in many areas, complicating estimation and inference. Regarding l...
Problems with truncated data occur in many areas, complicating estimation and inference. Regarding l...
This thesis contributes in several ways to the existing knowledge on estimation of truncated, censor...
This article provides a semi parametric method for the estimation of truncated regression models wh...
This paper deals with the estimation of conditional quantiles of linear truncated regression models ...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
Semiparametric regression is a combination of parametric and semiparametric regression. This regress...
This paper considers estimation of truncated.and censored regression models with fixed effects. Up u...
Estimation in the linear regression model Y = beta'Z + epsilon is considered for the left trunc...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
In this paper we illustrate the use of alternative truncated regression estimators for the general l...
Truncated distributions arise naturally in many practical situations. In this note, we provide progr...
Truncated sample arise when one do not observe a certain segment of a population. This typically hap...