This work aims at proposing a new method for estimating variances of complex survey estimators based on the recent developments in quasi-Monte Carlo methods. It can be effectively used to create replication schemes in complex surveys where the mathematically elegant schemes such as balanced repeated replica-tions break down due to design complexities, while other methods such as the survey bootstrap carry wit
International audienceRandomized Quasi-Monte Carlo (RQMC) methods provide unbiased estimators whose ...
This paper presents a simple idea for the use of quasi-Monte Carlo sampling with empirical datasets,...
A discussion on the possibility of reducing the variance of quasi-Monte Carlo estimators in applicat...
In this article, I discuss the main approaches to resampling variance estimation in complex survey d...
In complex survey sampling every population unit is assigned a specific probability to be included ...
Complex survey samples are constructed with selection schemes that affect the usual random assumptio...
This article discusses some resampling techniques that have found widespread application in survey ...
Several features of sample surveys generally render inapplicable the st and ard explicit forms of va...
I present software for analysing complex survey samples in R. The sampling scheme can be explicitly ...
A variance estimator in a large survey based on jackknife or balanced repeated replication typically...
It is routine practice for survey organizations to provide replication weights as part of survey dat...
Many control problems are so complex that analytic techniques fail to solve them [2]. Furthermore, e...
Although most survey texts are concerned primarily with problems of estimating finite population par...
Large-scale surveys such as the Current Population Survey, the Panel Study of Income Dynamics, and t...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
International audienceRandomized Quasi-Monte Carlo (RQMC) methods provide unbiased estimators whose ...
This paper presents a simple idea for the use of quasi-Monte Carlo sampling with empirical datasets,...
A discussion on the possibility of reducing the variance of quasi-Monte Carlo estimators in applicat...
In this article, I discuss the main approaches to resampling variance estimation in complex survey d...
In complex survey sampling every population unit is assigned a specific probability to be included ...
Complex survey samples are constructed with selection schemes that affect the usual random assumptio...
This article discusses some resampling techniques that have found widespread application in survey ...
Several features of sample surveys generally render inapplicable the st and ard explicit forms of va...
I present software for analysing complex survey samples in R. The sampling scheme can be explicitly ...
A variance estimator in a large survey based on jackknife or balanced repeated replication typically...
It is routine practice for survey organizations to provide replication weights as part of survey dat...
Many control problems are so complex that analytic techniques fail to solve them [2]. Furthermore, e...
Although most survey texts are concerned primarily with problems of estimating finite population par...
Large-scale surveys such as the Current Population Survey, the Panel Study of Income Dynamics, and t...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
International audienceRandomized Quasi-Monte Carlo (RQMC) methods provide unbiased estimators whose ...
This paper presents a simple idea for the use of quasi-Monte Carlo sampling with empirical datasets,...
A discussion on the possibility of reducing the variance of quasi-Monte Carlo estimators in applicat...