We consider an estimation problem with observations from a Gaussian process. The problem arises from a stochastic process modeling of computer experiments proposed recently by Sacks, Schiller, and Welch. By establishing various representations and approximations to the corresponding...

The semiparametric accelerated failure time model relates the logarithm of the failure time linearly to the covariates while leaving the error distribution unspecified. The present paper describes simple and reliable inference procedures based on the least-squares principle for this model with...

We propose a unified estimation method for semiparametric linear transformation models under general biased sampling schemes. The new estimator is obtained from a set of counting process-based unbiased estimating equations, developed through introducing a general weighting scheme that offsets...

We develop a unified L₁-based analysis-of-variance-type method for testing linear hypotheses. Like the classical L₂-based analysis of variance, the method is coordinate-free in the sense that it is invariant under any linear transformation of the covariates or regression parameters. Moreover, it...

Empirical likelihood (EL) ratio tests are developed for testing for or against the hypothesis that k-population means [mu]1,[mu]2,...,[mu]k are isotonic with respect to some quasi-order [not precedes, equals] on {1,2,...,k}. The null asymptotic distributions are derived and are shown to be of...