This paper explores the robustness of minimum distance (GMM) estimators focusing particularly on the effect of intermediate covariance matrix estimation on final estimator performance. Asymptotic expansions to order <italic>O</italic>(<italic>n</italic>^−3/2) are employed to construct <italic>O</italic>(<italic>n</italic>⁻²) expansions for the variance of...

Motivated by sampling problems in forestry and related fields, we suggest a spatial sampling scheme for estimating intensity of a point process. The technique is related to the `wandering quarter' method. In applications where the cost of identifying random points is high relative to the cost of...

We consider model-based prediction of a finite population total when a monotone transformation of the survey variable makes it appropriate to assume additive, homoscedastic errors. As the transformation to achieve this does not necessarily simultaneously produce an easily parameterized mean...

Many popular methods of model selection involve minimizing a penalized function of the data (such as the maximized log-likelihood or the residual sum of squares) over a set of models. The penalty in the criterion function is controlled by a penalty multiplier λ which determines the properties...