Download or read book On Reduced Risk Estimation in Linear Models written by Erkki Liski and published by . This book was released on 1979 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Health Risks from Exposure to Low Levels of Ionizing Radiation written by Committee to Assess Health Risks from Exposure to Low Levels of Ionizing Radiation and published by National Academies Press. This book was released on 2006-03-23 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the seventh in a series of titles from the National Research Council that addresses the effects of exposure to low dose LET (Linear Energy Transfer) ionizing radiation and human health. Updating information previously presented in the 1990 publication, Health Effects of Exposure to Low Levels of Ionizing Radiation: BEIR V, this book draws upon new data in both epidemiologic and experimental research. Ionizing radiation arises from both natural and man-made sources and at very high doses can produce damaging effects in human tissue that can be evident within days after exposure. However, it is the low-dose exposures that are the focus of this book. So-called “late” effects, such as cancer, are produced many years after the initial exposure. This book is among the first of its kind to include detailed risk estimates for cancer incidence in addition to cancer mortality. BEIR VII offers a full review of the available biological, biophysical, and epidemiological literature since the last BEIR report on the subject and develops the most up-to-date and comprehensive risk estimates for cancer and other health effects from exposure to low-level ionizing radiation.
Download or read book Risk Management in Supply Chains written by Mohammad Heydari and published by Routledge. This book was released on 2019-09-19 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book examines a relatively unexplored issue in supply chain risk management, which is how long companies specifically take to respond to catastrophic events of low probability but high impact. The book also looks at why such supply chain disruptions are unavoidable, and consequently, all complex supply chains are inherently at risk. The book illustrates how companies can respond to supply chain disruptions with faster responses and in shorter lead-times to reduce impact. In reducing total response time, designing solutions, and deploying a recovery plan sooner after a disruption in anticipation of such events, companies reduce the impact of disruption risk. The book also explores the basics of multiple-criteria decision-making (MCDM) and analytic hierarchy process (AHP), and how they contribute to both the quality of the financial economic decision-making process and the quality of the resulting decisions. The book illustrates through cases in the construction sector how this industry has become more complex and riskier due to the diverse nature of activities among global companies.
Download or read book Reexamining the Scientific Basis for the Linear No threshold Model of Low dose Radiation written by United States. Congress. House. Committee on Science. Subcommittee on Energy and Environment and published by . This book was released on 2001 with total page 1436 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Lower Risk Reduced Form Estimation and Forecasting Based on Finite Observations and Uncertain Structural Specifications in a Linear Simultaneous Equation Model written by Jin-Ho Jeong and published by . This book was released on 1985 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Linear Models written by Calyampudi R. Rao and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the theory and applications of linear models, for use as a textbook in statistics at graduate level as well as an accompanying text for other courses in which linear models play a part. The authors present a unified theory of inference from linear models with minimal assumptions, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights include: - a special emphasis on sensitivity analysis and model selection; - a chapter devoted to the analysis of categorical data based on logic, loglinear, and logistic regression models; - a chapter devoted to incomplete data sets; - an extensive appendix on matrix theory; - a chapter devoted to the analysis of categorical data based on a unified presentation of generalized linear models including GEE-methods for correlated response; - a chapter devoted to incomplete data sets including regression diagnostics to identify Non-MCAR-processes The material covered is thus invaluable not only to graduates, but also to researchers and consultants in statistics.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Generalized Linear Models for Insurance Rating written by Mark Goldburd and published by . This book was released on 2016-06-08 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Generalized Linear Models written by Annette J. Dobson and published by CRC Press. This book was released on 2018-04-17 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection, and a Postface on good statistical practice. Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before focusing on methods for analyzing particular kinds of data. It covers Normal, Poisson, and Binomial distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian models, and Markov chain Monte Carlo (MCMC) methods. Introduces GLMs in a way that enables readers to understand the unifying structure that underpins them Discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, non-linear associations and longitudinal analysis Connects Bayesian analysis and MCMC methods to fit GLMs Contains numerous examples from business, medicine, engineering, and the social sciences Provides the example code for R, Stata, and WinBUGS to encourage implementation of the methods Offers the data sets and solutions to the exercises online Describes the components of good statistical practice to improve scientific validity and reproducibility of results. Using popular statistical software programs, this concise and accessible text illustrates practical approaches to estimation, model fitting, and model comparisons.
Download or read book Health Risks from Exposure to Low Levels of Ionizing Radiation written by National Research Council and published by National Academies Press. This book was released on 2006-04-23 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: BEIR VII develops the most up-to-date and comprehensive risk estimates for cancer and other health effects from exposure to low-level ionizing radiation. It is among the first reports of its kind to include detailed estimates for cancer incidence in addition to cancer mortality. In general, BEIR VII supports previously reported risk estimates for cancer and leukemia, but the availability of new and more extensive data have strengthened confidence in these estimates. A comprehensive review of available biological and biophysical data supports a "linear-no-threshold" (LNT) risk modelâ€"that the risk of cancer proceeds in a linear fashion at lower doses without a threshold and that the smallest dose has the potential to cause a small increase in risk to humans. The report is from the Board on Radiation Research Effects that is now part of the newly formed Nuclear and Radiation Studies Board.
Download or read book Responses to Comments for Final Rules written by and published by . This book was released on 1984 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimation in Linear Models written by Truman Orville Lewis and published by . This book was released on 1971 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Health Effects of Exposure to Low Levels of Ionizing Radiation written by National Research Council and published by National Academies. This book was released on 1990-02-01 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reevaluates the health risks of ionizing radiation in light of data that have become available since the 1980 report on this subject was published. The data include new, much more reliable dose estimates for the A-bomb survivors, the results of an additional 14 years of follow-up of the survivors for cancer mortality, recent results of follow-up studies of persons irradiated for medical purposes, and results of relevant experiments with laboratory animals and cultured cells. It analyzes the data in terms of risk estimates for specific organs in relation to dose and time after exposure, and compares radiation effects between Japanese and Western populations.
Download or read book A Primer on Linear Models written by John F. Monahan and published by CRC Press. This book was released on 2008-03-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods.
Download or read book Causal Inference in Statistics written by Judea Pearl and published by John Wiley & Sons. This book was released on 2016-01-25 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.
Download or read book Admissible Linear Estimators in Mixed Linear Models written by Czesław Stepniak and published by . This book was released on 1988 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Theory of Ridge Regression Estimation with Applications written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2019-01-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators. The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
