statistical analysis with missing data wiley series in probability and statistics

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Statistical Analysis With Missing Data

Author : Roderick J. A. Little
ISBN : UCSD:31822002419430
Genre : Mathematics
File Size : 84. 84 MB
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Missing data in experiments. Maximum likelihood for general patterns of missing data: introduction and theory with ignorable nonresponse. Maximum likelihood estimation for multivariate normal examples, ignoring the missing-data mechanism. Models for pertilliy classified contingency tables, ignoring the missing-data mechanism. Mixed normal and nonnormal data with missing values, ignoring-data mechanism. Nonignorable missing-data models. The model-based to survey nonresponse.

Statistical Analysis Techniques In Particle Physics

Author : Ilya Narsky
ISBN : 9783527677290
Genre : Science
File Size : 65. 61 MB
Format : PDF
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Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.

New Frontiers Of Biostatistics And Bioinformatics

Author : Yichuan Zhao
ISBN : 9783319993898
Genre : Mathematics
File Size : 90. 75 MB
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This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of biostatistics, bioinformatics, and interdisciplinary areas. Biostatistics and bioinformatics have been playing a key role in statistics and other scientific research fields in recent years. The goal of the 5th Workshop on Biostatistics and Bioinformatics was to stimulate research, foster interaction among researchers in field, and offer opportunities for learning and facilitating research collaborations in the era of big data. The resulting volume offers timely insights for researchers, students, and industry practitioners.

Multiple Imputation For Nonresponse In Surveys

Author : Donald B. Rubin
ISBN : 9780470317365
Genre : Mathematics
File Size : 79. 11 MB
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Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations. Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique for researchers who must analyze them. Also presents the background for Bayesian and frequentist theory. After establishing that only standard complete-data methods are needed to analyze a multiply-imputed set, the text evaluates procedures in general circumstances, outlining specific procedures for creating imputations in both the ignorable and nonignorable cases. Examples and exercises reinforce ideas, and the interplay of Bayesian and frequentist ideas presents a unified picture of modern statistics.

Advances In Intelligent Data Analysis Xii

Author : Allan Tucker
ISBN : 9783642413988
Genre : Computers
File Size : 42. 16 MB
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This book constitutes the refereed conference proceedings of the 12th International Conference on Intelligent Data Analysis, which was held in October 2013 in London, UK. The 36 revised full papers together with 3 invited papers were carefully reviewed and selected from 84 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.

Improved Forecast Accuracy In Airline Revenue Management By Unconstraining Demand Estimates From Censored Data

Author : Richard H. Zeni
ISBN : 1581121415
Genre : Business & Economics
File Size : 63. 85 MB
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Accurate forecasts are crucial to a revenue management system. Poor estimates of demand lead to inadequate inventory controls and sub-optimal revenue performance. Forecasting for airline revenue management systems is inherently difficult. Competitive actions, seasonal factors, the economic environment, and constant fare changes are a few of the hurdles that must be overcome. In addition, the fact that most of the historical demand data is censored further complicates the problem. This dissertation examines the challenge of forecasting for an airline revenue management system in the presence of censored demand data. This dissertation analyzed the improvement in forecast accuracy that results from estimating demand by unconstraining the censored data. Little research has been done on unconstraining censored data for revenue management systems. Airlines tend to either ignore the problem or use very simple ad hoc methods to deal with it. A literature review explores the current methods for unconstraining censored data. Also, practices borrowed from areas outside of revenue management are adapted to this application. For example, the Expectation-Maximization (EM) and other imputation methods were investigated. These methods are evaluated and tested using simulation and actual airline data. An extension to the EM algorithm that results in a 41% improvement in forecast accuracy is presented.

Applied Bayesian Modeling And Causal Inference From Incomplete Data Perspectives

Author : Andrew Gelman
ISBN : 9780470090442
Genre : Mathematics
File Size : 42. 55 MB
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This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area.

Applied Mixed Models In Medicine

Author : Helen Brown
ISBN : 9781118778258
Genre : Medical
File Size : 65. 59 MB
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Author : Siegfried Gabler
ISBN : 3830961537
Genre :
File Size : 49. 7 MB
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Mathematical Methods In Survival Analysis Reliability And Quality Of Life

Author : Catherine Huber
ISBN : 1848210108
Genre : Business & Economics
File Size : 88. 22 MB
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Reliability and survival analysis are important applications of stochastic mathematics (probability, statistics and stochastic processes) that are usually covered separately in spite of the similarity of the involved mathematical theory. This title aims to redress this situation: it includes 21 chapters divided into four parts: Survival analysis, Reliability, Quality of life, and Related topics. Many of these chapters were presented at the European Seminar on Mathematical Methods for Survival Analysis, Reliability and Quality of Life in 2006.

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