As the size of data sets grows ever larger, the need for valid statistical tools is greater than ever. This book introduces super learning and the targeted maximum likelihood estimator, and discusses complex data structures and related applied topics.
In an extensively updated new edition, this book teaches stochastic programming, with new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods and more.
Now in its second, updated edition, this authoritative and coherent text contains a rich blend of theory and practice and covers all the essential concepts and algorithms from relevant fields such as data mining, machine learning, and text processing.
This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, …
Bayesian statistics are becoming the contemporary standard for treating ecological data. Introduction to Hierarchical Bayesian Modeling of Ecological Data is designed for readers who are interested in the quantitative analysis of environmental data yet reluctant to apply ready-m…
This textbook provides a guide for students using a computer package to analyse data from research projects and practical class work. The text takes a pragmatic approach to statistics with a strong focus on what is actually needed. There are chapters giving useful advice on the …
This book provides a practical guide for the use of modern statistical methods within agricultural and natural resources sciences. Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences is being released world-wide at an important time of …
The interaction between mathematicians and statisticians working in the actuarial and financial fields is producing numerous meaningful scientific results. This volume, comprising a series of four-page papers, gathers new ideas relating to mathematical and statistical methods in…
Section I: Food security policy analysis -- 1. Introduction to food security: concepts and measurement -- 2. Implications of technological change, post-harvest technology and technology adoption for improved food security - application of t- Statistic -- 3. Effects of commercial…
The concise yet authoritative presentation of key techniques for basic mixtures experiments Inspired by the author's bestselling advanced book on the topic, A Primer on Experiments with Mixtures provides an introductory presentation of the key principles behind experimenting wit…
Indirect questioning is a crucial topic in surveys of human populations. When the issue is about a stigmatizing characteristic (for example about illegal drug use), standard survey methodologies are destined to fail because, as expected, people are not willing to reveal incrimin…
Converting Data into Evidence: A Statistics Primer for the Medical Practitioner provides a thorough introduction to the key statistical techniques that medical practitioners encounter throughouttheir professional careers. These techniques play an important part in evidence-based…
This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, …
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted B…