책 세부 정보
형식
페이퍼백
페이지
546
언어
영어
출판됨
Aug 23, 2010
출판사
Cambridge University Press
ISBN-10
0521145775
ISBN-13
9780521145770
설명
This collection celebrates the groundbreaking contributions of Sir John Kingman, a pivotal figure in the fields of probability and mathematical genetics. His innovative research has influenced countless scholars and has shaped the very foundations of these disciplines. The authors, N.H. Bingham and C.M. Goldie, present a curated selection of papers that explore various aspects of Kingman’s work, highlighting its relevance and applications in contemporary research.
The papers delve into advanced probability theories and their implications in genetic modeling, showcasing the intricate connections between these areas. Each contribution reflects the high standard of academic rigor and creativity that Kingman espoused throughout his career. Through this homage, researchers and students alike gain insight into the evolving landscape of mathematical genetics.
By gathering diverse perspectives from esteemed colleagues and contemporaries, the book serves as both a tribute and a resource for those interested in the intersection of probability theory and genetic research. It offers an opportunity to appreciate the legacy of Sir John Kingman and encourages future exploration within these dynamic fields.
The papers delve into advanced probability theories and their implications in genetic modeling, showcasing the intricate connections between these areas. Each contribution reflects the high standard of academic rigor and creativity that Kingman espoused throughout his career. Through this homage, researchers and students alike gain insight into the evolving landscape of mathematical genetics.
By gathering diverse perspectives from esteemed colleagues and contemporaries, the book serves as both a tribute and a resource for those interested in the intersection of probability theory and genetic research. It offers an opportunity to appreciate the legacy of Sir John Kingman and encourages future exploration within these dynamic fields.