Bernstein-type exponential inequalities in survey sampling: Conditional Poisson sampling schemes

Bernoulli ◽  
2019 ◽  
Vol 25 (4B) ◽  
pp. 3527-3554
Author(s):  
Patrice Bertail ◽  
Stephan Clémençon
Keyword(s):  
Survey Sampling ◽  
Bernstein Type ◽  
Exponential Inequalities ◽  
Poisson Sampling ◽  
Sampling Schemes ◽  
Conditional Poisson Sampling ◽  
Conditional Poisson

Pareto Sampling versus Sampford and Conditional Poisson Sampling

2006 ◽  
Vol 33 (4) ◽  
pp. 699-720 ◽  
Author(s):  
LENNART BONDESSON ◽  
IMBI TRAAT ◽  
ANDERS LUNDQVIST
Keyword(s):  
Poisson Sampling ◽  
Conditional Poisson Sampling ◽  
Conditional Poisson

scholarly journals Bayesian Analysis of Finite Populations under Simple Random Sampling

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 318
Author(s):  
Manuel Mendoza ◽  
Alberto Contreras-Cristán ◽  
Eduardo Gutiérrez-Peña
Keyword(s):  
Bayesian Analysis ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Survey Sampling ◽  
Finite Populations ◽  
Population Means ◽  
Sampling Schemes ◽  
Nonparametric Approach ◽  
Conventional Procedure ◽  
Continuous And Discrete Variables

Statistical methods to produce inferences based on samples from finite populations have been available for at least 70 years. Topics such as Survey Sampling and Sampling Theory have become part of the mainstream of the statistical methodology. A wide variety of sampling schemes as well as estimators are now part of the statistical folklore. On the other hand, while the Bayesian approach is now a well-established paradigm with implications in almost every field of the statistical arena, there does not seem to exist a conventional procedure—able to deal with both continuous and discrete variables—that can be used as a kind of default for Bayesian survey sampling, even in the simple random sampling case. In this paper, the Bayesian analysis of samples from finite populations is discussed, its relationship with the notion of superpopulation is reviewed, and a nonparametric approach is proposed. Our proposal can produce inferences for population quantiles and similar quantities of interest in the same way as for population means and totals. Moreover, it can provide results relatively quickly, which may prove crucial in certain contexts such as the analysis of quick counts in electoral settings.

scholarly journals A metodologia de amostragem do Saeb

2019 ◽  
Vol 81 (197) ◽  
Author(s):  
Marcus M. Riether ◽  
Raíssa Rauter
Keyword(s):  
International Research ◽  
Target Population ◽  
Random Numbers ◽  
Sampling Methodology ◽  
Complex Samples ◽  
Poisson Sampling ◽  
Sampling Schemes ◽  
Data Analyses ◽  
Research Institutes

Apresenta, sob um enfoque simplificado, a metodologia de amostragem do Saeb, enfatizando particularidades relacionadas com o ciclo de 2001 e buscando esclarecer o leitor em relação a alguns dos pontos considerados mais importantes, tais como população de referência, estágios, esquemas de seleção de unidades amostrais e métodos de análise de dados de amostras complexas. Tópicos como precisão amostral, que envolvem discussões corriqueiras sobre a não-publicação de resultados individuais por escola ou a repetição de escolas que participaram do Saeb 1999, também são discutidos. Citam-se, ainda, casos de institutos de pesquisa sediados em outros países e que utilizam metodologias de amostragem semelhantes a do Saeb. Por fim, são apresentadas sugestões para o Saeb em suas futuras realizações. Palavras-chave: amostras complexas; coordenação de amostras; amostragem seqüencial de Poisson; números aleatórios permanentes. Abstract This paper presents a simplified version of the Saeb sampling methodology, emphasizing particularities of its cycle of 2001, and aiming at making clear to the reader some of its main points, such as target population, stages, sampling schemes and data analyses methods applied to complex samples. Topics like precision of estimates, that involve customary discussions about the avoidance in publishing schools' individual results or the sample overlap with the Saeb 1999 are also discussed. Cases of international research institutes that make use of sampling methodologies similar to that of Saeb are also mentioned. To finish, we present suggestions to Saeb in its future realizations. Keywords: complex samples; sample overlap; sequential Poisson sampling; permanent random numbers.

Empirical Processes in Survey Sampling with (Conditional) Poisson Designs

2016 ◽  
Vol 44 (1) ◽  
pp. 97-111 ◽  
Author(s):  
Patrice Bertail ◽  
Emilie Chautru ◽  
Stephan Clémençon
Keyword(s):  
Empirical Processes ◽  
Survey Sampling ◽  
Conditional Poisson

scholarly journals Coordination of Conditional Poisson Samples

2015 ◽  
Vol 31 (4) ◽  
pp. 649-672 ◽  
Author(s):  
Anton Grafström ◽  
Alina Matei
Keyword(s):  
Sampling Design ◽  
Random Numbers ◽  
Fixed Size ◽  
Poisson Sampling ◽  
New Methods ◽  
Inclusion Probabilities ◽  
Two Samples ◽  
Sequential Implementation ◽  
Coordination Degree ◽  
Conditional Poisson

Abstract Sample coordination seeks to maximize or to minimize the overlap of two or more samples. The former is known as positive coordination, and the latter as negative coordination. Positive coordination is mainly used for estimation purposes and to reduce data collection costs. Negative coordination is mainly performed to diminish the response burden of the sampled units. Poisson sampling design with permanent random numbers provides an optimum coordination degree of two or more samples. The size of a Poisson sample is, however, random. Conditional Poisson (CP) sampling is a modification of the classical Poisson sampling that produces a fixed-size πps sample. We introduce two methods to coordinate Conditional Poisson samples over time or simultaneously. The first one uses permanent random numbers and the list-sequential implementation of CP sampling. The second method uses a CP sample in the first selection and provides an approximate one in the second selection because the prescribed inclusion probabilities are not respected exactly. The methods are evaluated using the size of the expected sample overlap, and are compared with their competitors using Monte Carlo simulation. The new methods provide a good coordination degree of two samples, close to the performance of Poisson sampling with permanent random numbers.

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