In this article we study the use of the sample distribution for the prediction of finite population totals under single-stage sampling. The proposed predictors condition on the sample values of the target outcome variable, the sampling weights of the sample units and possibly on known population...

We propose a simple but general bootstrap method for estimating the Prediction Mean Square Error (PMSE) of the state vector predictors when the unknown model parameters are estimated from the observed series. As is well known, substituting the model parameters by the sample estimates in the...

We consider a model-dependent approach for multi-level modelling that accounts for informative probability sampling of first- and lower-level population units. The proposed approach consists of first extracting the hierarchical model holding for the sample data given the selected sample, as a...

Regression models that account for main state effects and nested county effects are considered for the assessment of farmland values. Empirical predictors obtained by replacing the unknown variances in the formula of the optimal predictors by maximum likelihood estimates are presented. The...

This article describes a simple method of estimating the autocorrelations of survey errors for the case of routing-panel sampling designs. Such designs are in routine use, for example, in labor force surveys (LFS). The survey-error autocorrelations induce spurious trends that need to be...

We propose simple parametric and nonparametric bootstrap methods for estimating the prediction mean square error (PMSE) of state vector predictors that use estimated model parameters. As is well known, substituting the model parameters by their estimates in the theoretical PMSE expression that...