Constrained estimators of treatment parameters in semiparametric models

Abstract

Semiparametric models are generalizations of parametric regression models. We present a method of estimation of treatment effects in a semiparametric model with one smoothing term under additional conditions on their linear functions and its application to hypothesis testing.

Restricted Estimation in Partially Linear Errors-in-Variables Models

“…As a result, we extend, on the one hand, the method in Shalabh et al (2007) to the partially linear models, and on the other hand, the results in Przystalski and Krajewski (2007) to the case of measurement errors. We shall assume that the constraints are of the form…”

“…For a partially linear model, Przystalski and Krajewski (2007) presented a method of estimation of treatment effects under additional conditions on their linear functions and its application to hypothesis testing.…”

Erratum to “Constrained estimators of treatment parameters in semiparametric models” [Statist. Probab. Lett. 77 (2007) 914–919]

“…This note is aimed at correcting a minor mistake in the proof of Theorem 3.1 in Przystalski and Krajewski (2007). The notation is the same as that in Przystalski and Krajewski (2007).…”