Ranked Set Sampling 65 Years Improving the Accuracy in Data Gathering
Auteurs : Bouza-Herrera Carlos N., Falah Al-Omari Amer Ibrahim
Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a good representation of the population and minimizes the costs associated with obtaining them. The main focus of many agricultural, ecological and environmental studies is the development of well designed, cost-effective and efficient sampling designs, giving RSS techniques a particular place in resolving the disciplinary problems of economists in application contexts, particularly experimental economics. This book seeks to place RSS at the heart of economic study designs.
Principally graduate students and 1st year PhD students of economics, econometrics, and statistics interested in the development of survey sampling. The book will be of interest for practitioners in areas diverse as biology, economy, environment, medical, psychology quality control and sociology problems.
Professor Amer Al-Omari is a Professor of Statistics at the Department of Mathematics, and Vice-Dean of Academic Research at Al al-Bayt University, Mafraq, Jordan. He is interested in ranked set sampling, entropy, missing data, order statistics, acceptance sampling plans, and statistical inference. He has published over 100 articles.
- Focuses on how researchers should manipulate RSS techniques for specific applications
- Discusses RSS performs in popular statistical models, such as regression and hypothesis testing
- Includes a discussion of open theoretical research problems
- Provides mathematical proofs, enabling researchers to develop new models
Date de parution : 10-2018
Ouvrage de 314 p.
19x23.3 cm
Thèmes de Ranked Set Sampling :
Mots-clés :
Accuracy; Answer bias; Attribute; Auxiliary information; Auxiliary variate; Average run length; Best linear unbiased estimator; Bias; Bootstrap method; Complex sampling; Concomitants of order statistics; Distribution; Distribution function; Efficiency; Estimation of mean; Estimator; Estimators; Expected model variance; Extreme ranked set sampling; Extropy estimation; FQRR model; Fisher information number; Horvitz-Thompson estimator; Imperfect ranking; MSE; Maximum likelihood estimators; Mean square error; Mean squared error; Median ranked set sampling; Minimum mean squared error estimator; Modified method of moment; Moving extreme ranked set sampling; Order statistics; Partially ordered judgment subset sampling; Perfect and imperfect rankings; Power; Prediction interval; Product estimator; Proportion; Randomized response technique; Randomized responses; Rank set sampling; Ranked set sample; Ranked set sample mean; Ranked set sampling; Ratio estimator; Relative efficiency; Relative precision; Repetitive sampling; Sampling design; Sampling without replacement; Scrambling; Sensitive variables; Shewhart control chart; Shrinkage estimator; Simple random sampling; Skew distributions; Small sample size; Statistical test; Strata boundaries; Stratified sample; Study variate; Super population model; Two-stage sampling; Unbalanced multistage ranked set sampling; Unbalanced single-stage ranked set sampling; Unbalanced steady-state ranked set sampling; Unbiased estimator; Unbiasedness; Unequal samples; Upper ranked set sampling; Variance