This paper extends the linearized maximum rank correlation (LMRC) estimation proposed
by Shen et al.(2023) to the setting where the covariate is a function. However, this extension …

Semiparametric models are useful in econometrics, social sciences and medicine
application. In this paper, a new estimator based on least square methods is proposed to …

We propose a semiparametric method to estimate average treatment effects in observational
studies based on the assumption of unconfoundedness. Assume that the propensity score …

Estimation of the average treatment effect is one of the crucial problems in clinical trials for
two or multiple treatments. The covariate‐adaptive randomization methods are often applied …

The projection pursuit regression (PPR) has played an important role in statistical modeling.
It can be used both as a data model for statistical interpretation and as an algorithmic model …

Developing high-dimensional statistical inference method to identify the individual features
associated with the response is very important in analyzing large-scale datasets from …

Single‐index model is a very popular and powerful semiparametric model. As an
improvement of the maximum rank correlation estimator, Shen et al. proposed the linearized …