The penalized calibration technique in survey sampling combines usual calibration and soft calibration by introducing a penalty term. Certain relevant estimates in survey sampling can be considered as penalized calibration estimates obtained as particular cases from an optimization problem with...

Based on the use of calibration techniques as a way of handling nonresponse, case-deletion diagnostics for calibration estimators are proposed. A deleted case is dealt with as it were a nonresponse case. Two types of diagnostics are proposed: one compares the calibration weights and the other...

The consequences of model misspecification for multinomial data when using minimum [phi]-divergence or minimum disparity estimators to estimate the model parameters are considered. These estimators are shown to converge to a well-defined limit. Two applications of the results obtained are...

Using expansions based on orthogonal polynomials, we study the properties (such as attainability) of a system of lower bounds for the variance of any unbiased estimator in certain distributions whose range depends on an unknown parameter. We also study the bound of the first order, and compare...

Suppose we have observed only the number of records in a random sample of unknown size n from a continuous distribution. Based on this data, we propose an unbiased estimator of n and derive expressions for its maximum likelihood estimator and an estimator based on the method of moments.