Asymptotic properties of robust regression estimators are well known. However, it is not always clear what the best strategy for confidence intervals and hypothesis testing when sample size very large, since distribution residuals coming from estimates has unknown small samples. In present work we propose an analysis various strategies estimating variance-covariance matrix S at variation n p, c...

Skewed data is the main issue in statistical models in healthcare costs. Data transformation is a conventional method to decrease skewness, but there are some disadvantages. Some recent studies have employed generalized linear models (GLMs) and Cox proportional hazard regression as alternative estimators. The aim of this study was to investigate how well these alternative estimators perform in ...

We consider nonparametric regression models in which the regression function is a step function, and construct a convolution estimator for the response density that has the same bias as the usual estimators based on the responses, but a smaller asymptotic variance.

We prove √ n-consistency and asymptotic normality of a generalized semiparametric regression estimator that includes as special cases Ichimura’s semiparametric least squares estimator for single index models, and the estimator of Klein and Spady for the binary choice regression model. Two function expansions reveal a type of U-process structure in the criterion function; then new U-process maxi...

Multicollinearity negatively affects the efficiency of maximum likelihood estimator (MLE) in both linear and generalized models. The Kibria Lukman (KLE) was developed as an alternative to MLE handle multicollinearity for regression model. In this study, we proposed Logistic Kibria-Lukman (LKLE) logistic We theoretically established superiority condition new over MLE, ridge (LRE), Liu (LLE), Liu...

This paper addresses the use of temperature measurements to estimate product compositions in distillation columns. A simple linear multivariate calibration procedure based on steady-state data is used, which requires minimal modeling effort. It is found that these principal-component-regression (PCR) and partial-least-squares (PLS) estimators perform well, even for multicomponent mixtures, pres...

We study the estimation error of constrained M -estimators, and derive explicit upper bounds on the expected estimation error determined by the Gaussian width of the constraint set. Both of the cases where the true parameter is on the boundary of the constraint set (matched constraint), and where the true parameter is strictly in the constraint set (mismatched constraint) are considered. For bo...

In this paper, the statistical inference of the unknown parameters of a twoparameter inverse Weibull (IW) distribution based on the progressive Type-II censored sample has been considered. The maximum likelihood estimators cannot be obtained in explicit forms, hence the approximate maximum likelihood estimators are proposed, which are in explicit forms. The Bayes and generalized Bayes estimator...