Trudy Silverheels, Native American author of the novels Dusky Nightshade and the Little Heathens, Nuevo Biloxi, and The Chosen Profession of Jade Stonecalf, gave the world her own fascinating history in Baring All. My Sister Bootsy might well be considered a sequel or companion volume to that autobiographical work, for herein Trudy's closest confidant, her elder sibling, continues her story, covering the eventful two years that followed publication of Baring All and then filling in further details from Trudy's childhood and early career.
In Brave Girl Boots: A Forty-Day Journey to Brave, you'll discover that with God, you are capable of more than you ever thought possible. There isn't a battle you are facing that cannot be conquered with the help of the Lord. Regardless of wherever life has you at this very moment, God has a plan of bravery for you.
During these forty days, women from all walks of life share their stories at Tami Walker's table. They will share stories of enduring some of the hardest hits life has to offer; they may have stumbled but they didn't succumb.
Finding their strength in an extended hand of grace that whispers, "Come on, get up ... you can do this!" You are invited every morning to join them on this journey!
A comprehensive introduction to bootstrap methods in the R programming environment
Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout is on the use of bootstrap methods as an exploratory tool, including its value in variable selection and other modeling environments.
The authors begin with a description of bootstrap methods and its relationship to other resampling methods, along with an overview of the wide variety of applications of the approach. Subsequent chapters offer coverage of improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems, including pharmaceutical, genomics, and economics. To inform readers on the limitations of the method, the book also exhibits counterexamples to the consistency of bootstrap methods.
An introduction to R programming provides the needed preparation to work with the numerous exercises and applications presented throughout the book. A related website houses the book's R subroutines, and an extensive listing of references provides resources for further study.
Discussing the topic at a remarkably practical and accessible level, An Introduction to Bootstrap Methods with Applications to R is an excellent book for introductory courses on bootstrap and resampling methods at the upper-undergraduate and graduate levels. It also serves as an insightful reference for practitioners working with data in engineering, medicine, and the social sciences who would like to acquire a basic understanding of bootstrap methods.
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