Abstract Recently, Liu (1993) estimator draws an important attention to estimate the
regression parameters for an ill-conditioned linear regression model when the vector of …

In the context of a partially linear regression model, shrinkage semiparametric estimation is
considered based on the Stein-rule. In this framework, the coefficient vector is partitioned …

In this paper, we consider optimal shrinkage estimation strategies for the regression
parameter matrix in multivariate multiple regression models. It uses the context of two …

In this paper, we establish three identities which play a crucial role in deriving the asymptotic
distributional risk function and the asymptotic distributional bias of a large class of estimators …

In this paper, we study a constrained estimation problem in a multivariate measurement
error regression model. In particular, we derive the joint asymptotic normality of the …

We study a two‐sample homogeneity testing problem, in which one sample comes from a
population with density f (x) and the other is from a mixture population with mixture density …

The empirical likelihood estimation approach has been used in statistical applications. In
this paper, we consider a stratified random sample subject to measurement error and with …

In this dissertation, we consider an estimation problem of the regression coefficients in both
multiple regression model and multivariate multiple regression model with several unknown …

We consider improved estimation strategies for the parameters in a capital asset pricing
model under a general linear constraint; we suggest candidate subspace, a preliminary test …

Pooling data from various sources to improve the parameter estimation is an important
problem from the practitioner's perspective. If the pooling procedure is carried out …