English
Related papers

Related papers: An Integer Programming Formulation Applied to Opti…

200 papers

The allocation problem for multivariate stratified random sampling as a problem of stochastic matrix integer mathematical programming is considered. With these aims the asymptotic normality of sample covariance matrices for each strata is…

Statistics Theory · Mathematics 2011-05-18 Jose A. Diaz-Garcia , Rogelio Ramos-Quiroga

This work considers the allocation problem for multivariate stratified random sampling as a problem of integer non-linear stochastic multiobjective mathematical programming. With this goal in mind the asymptotic distribution of the vector…

Methodology · Statistics 2011-06-07 Jose A. Diaz-Garcia , Rogelio Ramos-Quiroga

Allocation of samples in stratified and/or multistage sampling is one of the central issues of sampling theory. In a survey of a population often the constraints for precision of estimators of subpopulations parameters have to be taken care…

Statistics Theory · Mathematics 2015-03-31 Jacek Wesolowski , Robert Wieczorkowski

This paper studies a two-stage model of experimentation, where the researcher first samples representative units from an eligible pool, then assigns each sampled unit to treatment or control. To implement balanced sampling and assignment,…

Econometrics · Economics 2023-08-22 Max Cytrynbaum

The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata…

Methodology · Statistics 2024-03-27 Jacek Wesołowski , Robert Wieczorkowski , Wojciech Wójciak

In this paper, we propose a stratified sampling algorithm in which the random drawings made in the strata to compute the expectation of interest are also used to adaptively modify the proportion of further drawings in each stratum. These…

Methodology · Statistics 2007-12-04 Pierre Etore , Benjamin Jourdain

This paper investigates the use of stratified sampling as a variance reduction technique for approximating integrals over large dimensional spaces. The accuracy of this method critically depends on the choice of the space partition, the…

Probability · Mathematics 2009-09-15 Pierre Etoré , Gersende Fort , Benjamin Jourdain , Eric Moulines

We report a new optimal resolution for the statistical stratification problem under proportional sampling allocation among strata. Consider a finite population of N units, a random sample of n units selected from this population and a…

Machine Learning · Computer Science 2009-02-24 Jose Brito , Mauricio Lila , Flavio Montenegro , Nelson Maculan

We derive optimality conditions for the optimum sample allocation problem in stratified sampling, formulated as the determination of the fixed strata sample sizes that minimize the total cost of the survey, under the assumed level of…

Statistics Theory · Mathematics 2023-12-11 Wojciech Wójciak

Recent works have proposed optimal subsampling algorithms to improve computational efficiency in large datasets and to design validation studies in the presence of measurement error. Existing approaches generally fall into two categories:…

Methodology · Statistics 2025-12-25 Jasper B. Yang , Thomas Lumley , Bryan E. Shepherd , Pamela A. Shaw

In this paper, we aim to compute numerical approximation integral by using an adaptive Monte Carlo algorithm. We propose a stratified sampling algorithm based on an iterative method which splits the strata following some quantities called…

Numerical Analysis · Mathematics 2015-07-22 Toni Sayah

A modified Prekopa's approach is considered for the problem of optimum allocation in multivariate stratified random sampling. An example is solved by applying the proposed methodology.

Statistics Theory · Mathematics 2011-12-25 Jose A. Diaz-Garcia , Rogelio Raos-Quiroga

In classification problems, sampling bias between training data and testing data is critical to the ranking performance of classification scores. Such bias can be both unintentionally introduced by data collection and intentionally…

Methodology · Statistics 2017-11-02 Chandler Zuo

We consider the problem of adaptive stratified sampling for Monte Carlo integration of a noisy function, given a finite budget n of noisy evaluations to the function. We tackle in this paper the problem of adapting to the function at the…

Machine Learning · Statistics 2013-03-13 Alexandra Carpentier , Remi Munos

The problem of estimating a proportion of objects with particular attribute in a finite population is considered. This paper shows an example of the application of estimation fraction using new proposed sample allocation in a population…

Applications · Statistics 2019-03-19 Dominik Sieradzki , Wojciech Zieliński

Science and engineering problems subject to uncertainty are frequently both computationally expensive and feature nonsmooth parameter dependence, making standard Monte Carlo too slow, and excluding efficient use of accelerated uncertainty…

Numerical Analysis · Mathematics 2021-10-01 Per Pettersson , Sebastian Krumscheid

Predicting the cheapest sample size for the optimal stratification in multivariate survey design is a problem in cases where the population frame is large. A solution exists that iteratively searches for the minimum sample size necessary to…

Methodology · Statistics 2018-06-18 Mervyn O'Luing , Steven Prestwich , S. Armagan Tarim

In sampling theory, stratification corresponds to a technique used in surveys, which allows segmenting a population into homogeneous subpopulations (strata) to produce statistics with a higher level of precision. In particular, this article…

Methodology · Statistics 2022-11-22 José Brito , Gustavo Semaan , Leonardo de Lima , Augusto Fadel

The problem of estimation of the proportion of units with a given attribute in a~finite population is considered. From the population a sample is drawn due to the simple random sampling without replacement. There are limited funds for…

Statistics Theory · Mathematics 2019-03-26 Dominik Sieradzki , Wojciech Zieliński

In many randomized trials, outcomes such as essays or open-ended responses must be manually scored as a preliminary step to impact analysis, a process that is costly and limiting. Model-assisted estimation offers a way to combine surrogate…

Methodology · Statistics 2026-02-16 Reagan Mozer , Nicole E. Pashley , Luke Miratrix
‹ Prev 1 2 3 10 Next ›