Stratified sampling strategy for quantitative phase
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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Adaptive Strategy for Stratified Monte Carlo Sampling
... with stratified sampling, that is, it targets an allocation which is proportional to the standard deviation (and not to the variance) of a stratum times its size, see the book of Rubinstein and Kroese ...
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Optimized Sampling Strategy For Big Data Mining Through Stratified Sampling
... OPTIMIZED SAMPLING STRATEGY FOR BIG DATA MINING Sampling is given solutions during some problem raised in the big data analysis, such as ―bag of little bootstraps‖ [23] and sampling ...
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Three phase stratified sampling with ratio method of estimation
... resulting sampling is termed as multiphase sampling, when the sample for the main survey is selected in more than two ...first phase to collect information on characteristics such as household size, ...
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Replication Variance Estimation for Two-Phase Stratified Sampling
... Kott (1990) derived a formula for variance estimation when the first phase is a stratified random sample and the second phase is a restratified simple random sample based on first-phase [r] ...
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Scalable Simple Random Sampling and Stratified Sampling
... map phase, for each input item we generate a random key and decide whether to accept, reject, or wait-list the ...sort phase, the items in the waiting list are sorted by their associated ...
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A census weighted, spatially stratified household sampling strategy for urban malaria epidemiology
... required sampling from widely dispersed geographic strata, increasing costs compared to those expected using a highly clustered sampling strategy, the use of pre-programmed handheld GPS units and ...
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Semi Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
... of stratified sampling originated from statistics theory to the selection of the initial seed set contributes most to the performance improvement in the bootstrapping ...the stratified ...
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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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Improve Intrusion Detection for Decision Tree with Stratified Sampling
... the phase, data preprocessing phase, fusion decision phase and data call back ...uses Stratified weighted sampling techniques to generate the samples from the original datasets and then ...
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Stratified Random Sampling from Streaming and Stored Data
... start sampling new elements according to the higher allocation to S i , then recent elements in the stream will be favored over the older ones, and the sample within stratum i is no longer uniformly ...same ...
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On calibrated weights in stratified sampling
... Abstract In this paper, we propose a calibration estimator of population mean in stratified sampling using the known mean and variance information from multi-auxiliary variables. The problem of determining ...
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The Advantage and Disadvantage of Implicitly Stratified Sampling
... The relative extent of the standard error reduction varies between the estimates, however. For example, for estimating mean number of children or the proportion of people in paid employment most of the gains to be had ...
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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
... Same view was expressed by Murthy (1967) [2], that a good arrangement of the population units may yield a better estimate while a bad arrangement may lead to inefficient estimate and therefore, warned that one had to be ...
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Replicated Stratified Sampling for Sensitivity Analysis
... environments. The advancement of technology and availability of computing power has propelled this development over the last few decades. However, most modeling and valuation actuaries are still challenged with providing ...
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COMPARING THE OPTIMAL ALLOCATION IN STRATIFIED AND POST-STRATIFIED SAMPLING USING MULTI-ITEMS
... in stratified and post stratified sampling using multi-items and determined the variations of the components of the multi-items in the proposed ...the stratified variable subject to a fixed ...
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Functional quantization-based stratified sampling methods
... The article is organized as follows. Section 1 presents some necessary background on optimal quantization. The emphasis is on the functional quantization of Gaussian processes. Section 2 briefly covers the first ...
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Bayesian Stratified Sampling to Assess Corpus Utility
... If the strata are well constructed, the re- suiting estimate about the corpus will have a much smaller credibility interval (the Bayesian version of a confidence in[r] ...
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IMPROVED EXPONENTIAL ESTIMATOR IN STRATIFIED RANDOM SAMPLING
... the stratified random sampling using the information of an auxiliary variable x which is correlated with y and suggested improved exponential ratio estimators in the stratified random ...
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