Stratified sampling design used in the study
STOCHASTIC OPTIMIZATION IN MULTIVARIATE STRATIFIED DOUBLE SAMPLING DESIGN
... This paper deals with optimum allocation of sample size in stratified double sampling when costs are considered as random in the objective function. When costs function are random, by applying modified E. ...
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Scalable Simple Random Sampling and Stratified Sampling
... Introduction Sampling is an important technique in statistical anal- ysis, which consists of selecting some part of a popu- lation in order to estimate or learn something from the population at low ...random ...
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On calibrated weights in stratified sampling
... in stratified sampling using the known mean and variance information from multi-auxiliary ...comparison study is also carried out using real and simulated data to evaluate the performance and the ...
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An Optimum Multivariate-Multiobjective Stratified Sampling Design: Fuzzy Programming Approach
... In stratified sampling design when the cost of measuring the units is not significant in each stratum, the estimation of population mean or total constructed from a selected sample according to ...
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Optimal Allocation of Stratified Sampling Design Using Gradient Projection Method
... in stratified sampling design to minimize the cost ...is used to solve the Non linear programming problem (NLPP), when a non integer solution is obtained after solving the NLPP then Branch and ...
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The Advantage and Disadvantage of Implicitly Stratified Sampling
... the design effect for each of the three stratified designs (ratio of sampling vari- ance under ESS or ISS to that under ...ESS(N/100) design demonstrates that tendency to suffer from arthritis ...
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Sampling Error Estimation in Stratified Surveys
... Keywords: Variance Estimation; Jackknife; Bootstrap; Stratified Sampling 1. Introduction Many of the operations carried out by official statistics institutions are based on surveys performed on a finite ...
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A Note on the Precision of Stratified Systematic Sampling
... systematic sampling and to ensure first, that the existing arrangement did not lead to inef- ficient estimates before using ...this study, since application of methods of strata construction requires that ...
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Replicated Stratified Sampling for Sensitivity Analysis
... used in the attribution analysis. As processing time is directly proportional to the number of attribution runs performed, producing validated model outputs for regulatory reporting using even the less complicated ...
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An Evaluation of Stratified Sampling of Microarchitecture Simulations
... Instead, by applying BBV phase detection in the context of stratified random sampling, we can obtain a confidence estimate with every experiment. By measuring at least 30 units from each stratum (BBV ...
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An Optimum Stratification For Stratified Cluster Sampling Design When Clusters Are Of Varying Sizes
... cluster sampling design considering unequal sizes of ...mean. sampling in each stratum being carried out independently by simple random sampling without replacement ...
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COMPARING THE OPTIMAL ALLOCATION IN STRATIFIED AND POST-STRATIFIED SAMPLING USING MULTI-ITEMS
... The study compared optimum allocation in stratified and post stratified sampling using multi-items and determined the variations of the components of the multi-items in the proposed ...the ...
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Optimized Sampling Strategy For Big Data Mining Through Stratified Sampling
... and sampling techniques give a platform for fast execution in the big data ...paper used data reduction techniques as sampling for fast execution and identifying which sampling technique is ...
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Stratified sampling design and loss to follow-up in survival models: evaluation of efficiency and bias
... the sampling strata in the model, even when ignoring the sample weights [6,7], considering that this, unfortunately insufficient, procedure will correct for the design ...usually used in exploratory ...
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Functional quantization-based stratified sampling methods
... in stratified sampling methods in both the finite and infinite dimensional ...a stratified sampling algorithm based on product functional quantization for path-dependent functionals of ...
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Stratified Two-Phase Ranked Set Sampling
... set sampling, relative efficiency, sampling with replacement, two-phase ...set sampling (RSS) introduced by McIntyre (1952), was used to estimate the mean pasture and forage ...
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IMPROVED EXPONENTIAL ESTIMATOR IN STRATIFIED RANDOM SAMPLING
... this study, under stratified random sampling without replacement scheme, we suggest two improved exponential estimators which are more efficient than estimators proposed by Singh et ...
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Adaptive Strategy for Stratified Monte Carlo Sampling
... • There are more and more applications in machine learning that are targeting the allocation and placement of various kinds of sensors (as e.g., pollution sensors, tem- perature sensors, cameras of various kinds, network ...
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Memory Type Ratio and Product Estimators in Stratified Sampling
... random sampling. In the current study, we made an attempt to improve the estimator of (Noor-ul-Amin, 2019) by using stratified sampling ...simulation study and the results are given in ...
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Three phase stratified sampling with ratio method of estimation
... Former Faculty Member, Department of Statistics, Utkal University, Bhubaneswar, Odisha, India 1. I NTRODUCTION Sometimes a survey sampler selects a large sample of units to collect information on certain variables and ...
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