This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linear assumption of many standard models and allow analysts to uncover structure in the data that might otherwise have been missed. While McCullagh and Nelder's Generalized Linear Models shows how to extend the usual linear methodology to cover analysis of a range of data types, Generalized Additive Models enhances this methodology even further by incorporating the flexibility of nonparametric regression. Clear prose, exercises in each chapter, and case studies enhance this popular text.
Rethink Everything You Know about Managing Talent in Today’s Disruptive Landscape A Vice Chairman at Korn Ferry (KF)—the world’s largest talent advisory and executive search firm—RJ Heckman has helped many of today’s most successful companies develop talent-management strategies that ensure corporate success through good times and bad. Now, he shares his breakthrough methods with you. The Talent Manifesto reveals proven talent strategies and innovative recruiting and retainment methods gleaned from nearly three decades of consulting with the world's leading organizations. Heckman identifies the most common pitfalls in HR today and delivers an actionable program for avoiding them. He shows how to generate reliable data and use it to make the best decisions. He reveals all the game-changing HR strategies at your disposal and how to use them to drive superior business performance. As organizations across industries experience faster cycles of disruptive change, one factor looms above all others as a portent of their future success: whether they can recruit, develop, and retain top talent better and faster than their competitors. With The Talent Manifesto, you have everything you need to redesign your HR strategies, reshape perception of talent management, and measurably contribute to your organization’s ability to compete—now and in the future.
Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software. The 2003 book is suitable as a textbook for students with little background in regression as well as a reference book for statistically oriented scientists such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models. Even experts on semiparametric regression should find something new here.
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.