Université de Neuchâtel

Doubly balanced spatial sampling with spreading and restitution of auxiliary totals

Grafström, Anton ; Tillé, Yves

In: Environmetrics, 2013, vol. 24, no. 2, p. 120-131

A new spatial sampling method is proposed in order to achieve a double property of balancing. The sample is spatially balanced or well spread so as to avoid selecting neighbouring units. Moreover, the method also enables to satisfy balancing equations on auxiliary variables available on all the sampling units because the Horvitz–Thompson estimator is almost equal to the population totals for...

Université de Neuchâtel

Measuring inequality in finite population sampling

Langel, Matti ; Tillé, Yves (Dir.)

Thèse de doctorat : Université de Neuchâtel, 2012 ; 2252.

This document focuses on the estimation of inequality measures for complex survey data. The proposed methodology takes into account both the complexity of these generally non-linear functions of interest and the complexity of the sampling strategy. The first chapter is dedicated to the presentation and definition of the main concepts used in both inequality and survey sampling theory. In the...

Université de Neuchâtel

New methods to handle nonresponse in surveys

Hasler, Caren ; Tillé, Yves (Dir.)

Thèse de doctorat : Université de Neuchâtel, 2015.

This document focuses on nonresponse in sample surveys. Mainly, methods to handle nonresponse in complex surveys are proposed. The first chapter of this document introduces concepts and notation of survey sampling and nonresponse. The second chapter proposes an algorithm for stratified balanced sampling for populations with large numbers of strata. The third chapter of this document presents a...

Université de Neuchâtel

Optimal allocation in balanced sampling

Tillé, Yves ; Favre, Anne-Catherine

In: Statistics & Probability Letters, 2005, vol. 74, no. 1, p. 31-37

The development of new sampling methods allows the selection of large balanced samples. In this paper we propose a method for computing optimal inclusion probabilities for balanced samples. Next, we show that the optimal Neyman allocation is a particular case of this method.