Ali S. Hadi – författare

A straightforward, practical guide to extreme value modeling for today's world Measuring and interpreting data for extreme values presents a unique and important challenge that has far-reaching implications for all aspects of modern engineering and science. Extreme Value and Related Models with Applications in Engineering and Science reflects the latest information in this growing field. The book incorporates illuminating real-world examples from such areas as structural engineering, hydraulics, meteorology, materials science, highway traffic analysis, environmetrics, and climatology, and is designed to help engineers, mathematicians, statisticians, and scientists gain a clearer understanding of extreme value theory and then translate that knowledge into practical applications within their own fields of research.The book provides: A unique focus on modern topics including data analysis and inferenceSpecific data in such areas as wind, flood, chain strength, electrical insulation, fatigue, precipitation, and wave heightsUseful techniques for addressing extreme value problems, including discrete, continuous, univariate, and multivariate modelsCoverage of order statistics, return period, exceedances and shortfalls, along with detailed explanations on how to obtain exact distributions for these statisticsAn in-depth look at asymptotic models and the limit distributions of maxima, minima, and other order statisticsEnhanced with numerous graphs and exercises, plus an extensive bibliography for further study, this text is an important reference source for engineers designing structures that will withstand even the most extreme circumstances.

Treats linear regression diagnostics as a tool for application of linear regression models to real-life data. Presentation makes extensive use of examples to illustrate theory. Assesses the effect of measurement errors on the estimated coefficients, which is not accounted for in a standard least squares estimate but is important where regression coefficients are used to apportion effects due to different variables. Also assesses qualitatively and numerically the robustness of the regression fit.

Regression Analysis By Example Using RA STRAIGHTFORWARD AND CONCISE DISCUSSION OF THE ESSENTIALS OF REGRESSION ANALYSISIn the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides in-depth treatments of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression.The author clearly demonstrates effective methods of regression analysis with examples that contain the types of data irregularities commonly encountered in the real world. This newest edition also offers a brand-new, easy to read chapter on the freely available statistical software package R.Readers will also find: Reorganized, expanded, and upgraded exercises at the end of each chapter with an emphasis on data analysisUpdated data sets and examples throughout the bookComplimentary access to a companion website that provides data sets in xlsx, csv, and txt formatPerfect for upper-level undergraduate or beginning graduate students in statistics, mathematics, biostatistics, and computer science programs, Regression Analysis By Example Using R will also benefit readers who need a reference for quick updates on regression methods and applications.