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Ranked Set Sampling Models and Methods

When it comes to data collection and analysis, ranked set sampling (RSS) continues to increasingly be the focus of methodological research;

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Handling Missing Data in Ranked Set Sampling

traditional sampling. It is called Ranked Set Sampling (RSS). A random selection is made with the replacement of samples, which are ordered (ranked;

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Ranked Set Sampling

Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the;

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Applied Statistical Science II

Ranked Set Sample; Lower Bound to Mean Square Error of Estimator in Unequal Probability Sampling; Asymptomic Shrinkage Estimation: The Regression;

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Sampling Theory and Methods

Sampling Theory and Methods presents in detail several sampling schemes like simple random sampling, unequal probability sampling methods;

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Introduction to Ecological Sampling

An Easy-to-Understand Treatment of Ecological Sampling Methods and Data Analysis Including only the necessary mathematical derivations;

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Modern Sampling Methods

editions.Of both theoretical and practical use to statisticians and research workers using sampling techniques, this book describes five new multi;

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Survey Sampling Theory and Applications

covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling;

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New Developments in Applied Statistics

using random non-response in survey sampling; balanced groups ranked set samples for estimating the population median; Marshall-Olkin;

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Advanced Sampling Methods

cluster sampling, rank-set sampling and their applications in real life. Advance methods discussed in the book have tremendous applications;

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Advanced Sampling Methods

cluster sampling, rank-set sampling and their applications in real life. Advance methods discussed in the book have tremendous applications;

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Field Sampling

Written by a renowned professional with more than 30 years of experience in environmental sampling and analysis, this reference describes;

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Sampling of Populations

This set includes Sampling of Populations: Methods and Applications, 4th Edition and Sampling of Populations: Methods and Applications;

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Missing Data Methods

Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators;

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Missing Data Methods

Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators;

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Multivariate Statistics

papers on classification methods are included. Applications range from insurance mathematics to medical and industrial statistics and sampling;

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Bayesian Missing Data Problems

sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms. After introducing the missing data;

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Bayesian Missing Data Problems

sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms. After introducing the missing data;

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Recent Advances In Statistical Methods, Proceedings Of Statistics 2001 Canada

This volume consists of research papers dealing with computational and methodological issues of statistical methods on the cutting edge;

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Audit Guide: Sampling 2019

Updated as of December 1, 2019, this guide continues to be an indispensable resource packed with information on sampling requirements and;

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Hierarchical Modeling and Inference in Ecology

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods;

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Introdu To Statistical Computing

A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has;

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Methods of Statistical Model Estimation

maximum likelihood estimation, iteratively reweighted least squares regression, the EM algorithm, and MCMC sampling. Fully developed, working R;

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Methods of Statistical Model Estimation

maximum likelihood estimation, iteratively reweighted least squares regression, the EM algorithm, and MCMC sampling. Fully developed, working R;

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Bayesian Econometric Methods

have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based;

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Bayesian Econometric Methods

have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based;

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Audit Guide

Considered the industry-standard resource and updated as of March 1, 2014, the Audit Sampling Guide summarizes applicable requirements and;

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