Estimating equations have found wide popularity recently in parametric problems, yielding
consistent estimators with asymptotically valid inferences obtained via the sandwich formula …

For the past two decades, the single-index model, a special case of projection pursuit
regression, has proven to be an efficient way of coping with the high-dimensional problem in …

We consider a generalized partially linear model E (Y| X, T)= G {XT β+ m (T)}, where G is a
known function, β is an unknown parameter vector, and m is an unknown function. We …

Aiming to explore the relation between the response y and the stochastic explanatory vector
variable X beyond the linear approximation, we consider the single-index model, which is a …

Background Learning the causal structure helps identify risk factors, disease mechanisms,
and candidate therapeutics for complex diseases. However, although complex biological …

In this paper we analyze a large class of semiparametric M-estimators for single-index
models, including semiparametric quasi-likelihood and semiparametric maximum likelihood …

We study semiparametric varying-coefficient partially linear models when some linear
covariates are not observed, but ancillary variables are available. Semiparametric profile …

Transfer learning is crucial for training models that generalize to unlabeled target
populations using labeled source data, especially in real-world studies where label scarcity …

Section S. 1 in the Supplement [5] includes the proofs of main and auxiliary results. Various
technical assumptions are compiled and discussed in Section S. 2, while Section S. 3 …

In this article, we study a class of semiparametric mixtures of regression models, in which the
regression functions are linear functions of the predictors, but the mixing proportions are …