Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods.
"Applied Probability" uniquely combines theory and applications, focusing on mathematical modeling and computational techniques, particularly in biological sciences. It's suitable for graduate students in various fields and covers essential topics like stochastic processes, combinatorics, and optimization. The second edition includes new chapters and expanded exercises, making it a valuable reference for mathematical scientists.
Lange is a Springer author of other successful books. This is the first book that emphasizes the applications of optimization to statistics. The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics.
During the past decade, geneticists have constructed detailed maps of the human genome and cloned scores of Mendelian disease genes. These insights into human disease and evolution which have transformed medicine and agriculture depend on the contributions of applied mathematicians, statisticians, and computer scientists. This work is written to help readers understand and model the epidemiological and experimental data encountered in genetics research.
This tutorial presents a brief survey of semidifferentials in the familiar context of finite-dimensional Euclidean space. The main focus is on Hadamard semidifferentials. The Hadamard semidifferential is more general than the Fréchet differential, which is now dominant in undergraduate mathematics education.