Vignette d'image

Tillé, Yves

Nom
Tillé, Yves
Affiliation principale
Site web
Fonction
Professeur ordinaire
Email
yves.tille@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/541
_
0000-0003-0904-5523

Résultat de la recherche

Filtres

2
11
Réinitialiser les filtres

Paramètres

Voici les éléments 1 - 2 sur 2
  • Publication
    Métadonnées seulement
    Incorporating spatial and operational constraints in the sampling designs for forest inventories
    (2015-6-15)
    Vallée, Audrey-Anne 
    ;
    Ferland-Raymond, Bastien
    ;
    Rivest, Louis-Paul
    ;
    Tillé, Yves 
    In the province of Quebec, Canada, the forest is examined through regular inventories. Requirements for the spreading and the type of trees and for the cost are difficult to manage. We show that modern and advanced sampling techniques can be used to improve the planning of the forest inventories, even if there are many requirements. Our design includes balanced sampling, highly stratified balanced sampling and sample spreading through a two stage sample. The impact of these techniques on the satisfaction of the requirements and on the precision of survey estimates is investigated using field data from a Quebec inventory.
  • Publication
    Métadonnées seulement
    Systematic sampling is a minimal support design
    (2007-3-23)
    Pea, Johan 
    ;
    Qualité, Lionel 
    ;
    Tillé, Yves 
    In order to select a sample in a finite population of N units with given inclusion probabilities, it is possible to define asamplingdesign on at most N samples that have a positive probability of being selected. Designs defined on minimal sets of samples are called minimum supportdesigns. It is shown that, for any vector of inclusion probabilities, systematicsampling always provides a minimum supportdesign. This property makes it possible to extensively compute the samplingdesign and the joint inclusion probabilities. Random systematicsampling can be viewed as the random choice of a minimum supportdesign. However, even if the population is randomly sorted, a simple example shows that some joint inclusion probabilities can be equal to zero. Another way of randomly selecting a minimum supportdesign is proposed, in such a way that all the samples have a positive probability of being selected, and all the joint inclusion probabilities are positive.