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A New Concept for Tuning Design Weights in Survey Sampling

A New Concept for Tuning Design Weights in Survey Sampling
  • Author : Sarjinder Singh
  • Publsiher : Academic Press
  • Release : 17 November 2015
  • ISBN : 0081005954
  • Pages : 316 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKA New Concept for Tuning Design Weights in Survey Sampling

Summary:
A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice introduces the new concept of tuning design weights in survey sampling by presenting three concepts: calibration, jackknifing, and imputing where needed. This new methodology allows survey statisticians to develop statistical software for analyzing data in a more precisely and friendly way than with existing techniques. Explains how to calibrate design weights in survey sampling Discusses how Jackknifing is needed in design weights in survey sampling Describes how design weights are imputed in survey sampling


A New Concept for Tuning Design Weights in Survey Sampling

A New Concept for Tuning Design Weights in Survey Sampling
  • Author : Sarjinder Singh,Stephen A. Sedory,Maria Del Mar Rueda,Antonio Arcos,Raghunath Arnab
  • Publisher : Academic Press
  • Release : 17 November 2015
GET THIS BOOKA New Concept for Tuning Design Weights in Survey Sampling

A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice introduces the new concept of tuning design weights in survey sampling by presenting three concepts: calibration, jackknifing, and imputing where needed. This new methodology allows survey statisticians to develop statistical software for analyzing data in a more precisely and friendly way than with existing techniques. Explains how to calibrate design weights in survey sampling Discusses how Jackknifing is needed in design weights in survey sampling

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Survey Sampling Theory and Applications

Survey Sampling Theory and Applications
  • Author : Raghunath Arnab
  • Publisher : Academic Press
  • Release : 08 March 2017
GET THIS BOOKSurvey Sampling Theory and Applications

Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling. The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying

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Impact Analysis of Total Productive Maintenance

Impact Analysis of Total Productive Maintenance
  • Author : José Roberto Díaz-Reza,Jorge Luis García-Alcaraz,Valeria Martínez-Loya
  • Publisher : Springer
  • Release : 01 October 2018
GET THIS BOOKImpact Analysis of Total Productive Maintenance

This book present the state of the art in Total Productive Maintainance (TPM) and its benefits. The authors present a survey applied to 368 manufacturing industries in order to determine their level of execution of TPM. Then a series of causal models are presented. For each model, the authors present a measure of the dependency between the critical success factors and the benefits obtained, allowing industry managers to differentiate between essential and non-essential activities. The content also allows students and academics

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Complex Surveys

Complex Surveys
  • Author : Thomas Lumley
  • Publisher : John Wiley & Sons
  • Release : 20 September 2011
GET THIS BOOKComplex Surveys

A complete guide to carrying out complex survey analysis usingR As survey analysis continues to serve as a core component ofsociological research, researchers are increasingly relying upondata gathered from complex surveys to carry out traditionalanalyses. Complex Surveys is a practical guide to theanalysis of this kind of data using R, the freely available anddownloadable statistical programming language. As creator of thespecific survey package for R, the author provides the ultimatepresentation of how to successfully use the software for analyzingdata from

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Federal Statistics, Multiple Data Sources, and Privacy Protection

Federal Statistics, Multiple Data Sources, and Privacy Protection
  • Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods
  • Publisher : National Academies Press
  • Release : 27 January 2018
GET THIS BOOKFederal Statistics, Multiple Data Sources, and Privacy Protection

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily

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Statistics and Probability for Engineering Applications

Statistics and Probability for Engineering Applications
  • Author : William DeCoursey
  • Publisher : Elsevier
  • Release : 14 May 2003
GET THIS BOOKStatistics and Probability for Engineering Applications

Statistics and Probability for Engineering Applications provides a complete discussion of all the major topics typically covered in a college engineering statistics course. This textbook minimizes the derivations and mathematical theory, focusing instead on the information and techniques most needed and used in engineering applications. It is filled with practical techniques directly applicable on the job. Written by an experienced industry engineer and statistics professor, this book makes learning statistical methods easier for today's student. This book can be read

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The Algorithmic Foundations of Differential Privacy

The Algorithmic Foundations of Differential Privacy
  • Author : Cynthia Dwork,Aaron Roth
  • Publisher : Anonim
  • Release : 26 June 2022
GET THIS BOOKThe Algorithmic Foundations of Differential Privacy

The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of

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Applied Text Analysis with Python

Applied Text Analysis with Python
  • Author : Benjamin Bengfort,Rebecca Bilbro,Tony Ojeda
  • Publisher : "O'Reilly Media, Inc."
  • Release : 11 June 2018
GET THIS BOOKApplied Text Analysis with Python

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine

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Introduction to Optimum Design

Introduction to Optimum Design
  • Author : Jasbir Arora
  • Publisher : Academic Press
  • Release : 12 August 2011
GET THIS BOOKIntroduction to Optimum Design

Introduction to Optimum Design, Third Edition describes an organized approach to engineering design optimization in a rigorous yet simplified manner. It illustrates various concepts and procedures with simple examples and demonstrates their applicability to engineering design problems. Formulation of a design problem as an optimization problem is emphasized and illustrated throughout the text. Excel and MATLAB® are featured as learning and teaching aids. Basic concepts of optimality conditions and numerical methods are described with simple and practical examples, making the

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Reinforcement Learning, second edition

Reinforcement Learning, second edition
  • Author : Richard S. Sutton,Andrew G. Barto
  • Publisher : MIT Press
  • Release : 13 November 2018
GET THIS BOOKReinforcement Learning, second edition

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's

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Practical Statistics for Data Scientists

Practical Statistics for Data Scientists
  • Author : Peter Bruce,Andrew Bruce
  • Publisher : "O'Reilly Media, Inc."
  • Release : 10 May 2017
GET THIS BOOKPractical Statistics for Data Scientists

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’

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Statistical Learning with Sparsity

Statistical Learning with Sparsity
  • Author : Trevor Hastie,Robert Tibshirani,Martin Wainwright
  • Publisher : CRC Press
  • Release : 07 May 2015
GET THIS BOOKStatistical Learning with Sparsity

Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm

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Data Gathering, Analysis and Protection of Privacy through Randomized Response Techniques: Qualitative and Quantitative Human Traits

Data Gathering, Analysis and Protection of Privacy through Randomized Response Techniques: Qualitative and Quantitative Human Traits tackles how to gather and analyze data relating to stigmatizing human traits. S.L. Warner invented RRT and published it in JASA, 1965. In the 50 years since, the subject has grown tremendously, with continued growth. This book comprehensively consolidates the literature to commemorate the inception of RR. Brings together all relevant aspects of randomized response and indirect questioning Tackles how to gather and analyze data

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