Search results for "Horvitz-Thompson estimator"

showing 7 items of 7 documents

Variance estimation and asymptotic confidence bands for the mean estimator of sampled functional data with high entropy unequal probability sampling …

2013

For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the H\'ajek formula. The interest of this asymptotic variance approximation is that it only involves the first order inclusion probabilities of the statistical units. We extend this variance formula when the variable under study is functional and we prove, under general conditions on the regularity of the individual trajectories and the sampling design, that we can get a uniformly convergent estimator of the variance function of the Horvitz-Thompson estimator of the mean function. Rates of convergence to the true variance function are given for the re…

Kullback-Leibler divergence[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]FOS: Mathematicscovariance functionrejective samplingMathematics - Statistics TheoryStatistics Theory (math.ST)finite populationHorvitz-Thompson estimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Hájek approximationunequal probability sampling without replacement[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]
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Variance Estimation for the Horvitz-Thompson Total Estimator in Unequal Probability Sampling Designs

unequal probability samplinghorvitz-thompson estimatorsurvey samplingvariance estimation
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Uniform convergence and asymptotic confidence bands for model-assisted estimators of the mean of sampled functional data

2013

When the study variable is functional and storage capacities are limited or transmission costs are high, selecting with survey sampling techniques a small fraction of the observations is an interesting alternative to signal compression techniques, particularly when the goal is the estimation of simple quantities such as means or totals. We extend, in this functional framework, model-assisted estimators with linear regression models that can take account of auxiliary variables whose totals over the population are known. We first show, under weak hypotheses on the sampling design and the regularity of the trajectories, that the estimator of the mean function as well as its variance estimator …

Statistics and ProbabilityMean squared errorMathematics - Statistics TheoryStatistics Theory (math.ST)Hájek estimator62D05; 62E20 62M9901 natural sciences010104 statistics & probabilityMinimum-variance unbiased estimatorBias of an estimator[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]60F050502 economics and businessStatisticsConsistent estimatorFOS: Mathematicscovariance functionHorvitz-Thompson estimator[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]62L200101 mathematicssurvey sampling050205 econometrics Variance functionMathematicsGREG05 social sciencesEstimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]calibration[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]linear interpolation.linear interpolationEfficient estimatorStatistics Probability and Uncertaintyfunctional linear modelInvariant estimator
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Estimating with kernel smoothers the mean of functional data in a finite population setting. A note on variance estimation in presence of partially o…

2014

In the near future, millions of load curves measuring the electricity consumption of French households in small time grids (probably half hours) will be available. All these collected load curves represent a huge amount of information which could be exploited using survey sampling techniques. In particular, the total consumption of a specific cus- tomer group (for example all the customers of an electricity supplier) could be estimated using unequal probability random sampling methods. Unfortunately, data collection may undergo technical problems resulting in missing values. In this paper we study a new estimation method for the mean curve in the presence of missing values which consists in…

FOS: Computer and information sciencesStatistics and ProbabilityPopulationRatio estimatorLinearizationRatio estimator01 natural sciencesSurvey sampling.Horvitz–Thompson estimatorMethodology (stat.ME)010104 statistics & probabilityH\'ajek estimator0502 economics and businessApplied mathematicsMissing valuesHorvitz-Thompson estimator0101 mathematicseducationStatistics - Methodology050205 econometrics MathematicsPointwiseeducation.field_of_study[STAT.ME] Statistics [stat]/Methodology [stat.ME]05 social sciencesNonparametric statisticsEstimator16. Peace & justiceMissing dataFunctional data[ STAT.ME ] Statistics [stat]/Methodology [stat.ME]Kernel (statistics)Statistics Probability and UncertaintyNonparametric estimation[STAT.ME]Statistics [stat]/Methodology [stat.ME]
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Properties of Design-Based Functional Principal Components Analysis.

2010

This work aims at performing Functional Principal Components Analysis (FPCA) with Horvitz-Thompson estimators when the observations are curves collected with survey sampling techniques. One important motivation for this study is that FPCA is a dimension reduction tool which is the first step to develop model assisted approaches that can take auxiliary information into account. FPCA relies on the estimation of the eigenelements of the covariance operator which can be seen as nonlinear functionals. Adapting to our functional context the linearization technique based on the influence function developed by Deville (1999), we prove that these estimators are asymptotically design unbiased and con…

Statistics and ProbabilityContext (language use)Mathematics - Statistics TheoryStatistics Theory (math.ST)Perturbation theory01 natural sciencesVariance estimationHorvitz–Thompson estimatorSurvey sampling010104 statistics & probabilityLinearization[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]0502 economics and businessStatisticsConsistent estimatorFOS: Mathematicsvon Mises expansionApplied mathematicsHorvitz-Thompson estimator[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsComputingMilieux_MISCELLANEOUS050205 econometrics MathematicsEigenfunctionsInfluence functionApplied Mathematics05 social sciencesMathematical statisticsEstimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Covariance operatorCovariance16. Peace & justice[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Delta methodModel-assisted estimationStatistics Probability and Uncertainty
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Penalization and data reduction of auxiliary variables in survey sampling

2012

Survey sampling techniques are quite useful in a way to estimate population parameterssuch as the population total when the large dimensional auxiliary data setis available. This thesis deals with the estimation of population total in presenceof ill-conditioned large data set.In the first chapter, we give some basic definitions that will be used in thelater chapters. The Horvitz-Thompson estimator is defined as an estimator whichdoes not use auxiliary variables. Along with, calibration technique is defined toincorporate the auxiliary variables for sake of improvement in the estimation ofpopulation totals for a fixed sample size.The second chapter is a part of a review article about ridge re…

Estimateur assisté par un modèleModel-assisted estimatorRégression ridge[ MATH.MATH-GM ] Mathematics [math]/General Mathematics [math.GM]Calage sur composantes principalesPenalized calibration[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]Estimateur basé sur un modèleSurvey sampling[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM]Ridge regressionCalage pénaliséModel-based estimatorColinéaritéEstimateur de Horvitz-ThompsonHorvitz-Thompson estimatorSondageMulticollinearityPrincipal component calibration
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Estimate the mean electricity consumption curve by survey and take auxiliary information into account

2012

In this thesis, we are interested in estimating the mean electricity consumption curve. Since the study variable is functional and storage capacities are limited or transmission cost are high survey sampling techniques are interesting alternatives to signal compression techniques. We extend, in this functional framework, estimation methods that take into account available auxiliary information and that can improve the accuracy of the Horvitz-Thompson estimator of the mean trajectory. The first approach uses the auxiliary information at the estimation stage, the mean curve is estimated using model-assisted estimators with functional linear regression models. The second method involves the au…

Model-assisted estimator[ MATH.MATH-GM ] Mathematics [math]/General Mathematics [math.GM]Unequal probability sampling without replacement[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]Functional linear modelCovariance functionFunctional central limit theoremConfidence bandFunctional dataBootstrapSurvey sampling[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM]Théorème central limite fonctionnelDonnées fonctionnellesHajek variance approximationFonction de covariancePlan à probabilités inégales sans remiseEstimateur de Horvitz-ThompsonModèle linéaire fonctionnelApproximation de HájekHorvitz-Thompson estimatorSondageBande de confianceEstimateur model-assisted
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