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Launched in the 1990s, reflecting the increasing importance of statistics in various fields of scientific research, the series aims to foster the application of statistical methodology in these disciplines. It is vital in the modern information era, with a prevalence of large and complex datasets, that researchers, practitioners and students from nearly all sciences have a solid understanding of statistical methods and their application.

The books in the series are necessarily very applied in nature, presenting overviews of statistical methodology with applications in fields as diverse as medical research, epidemiology, biology, genetics, ecology, actuarial science, social and behavioral science, and engineering. An emphasis is placed on describing the methods with sufficient rigor whilst assuming little in terms of the mathematical sophistication of the reader. The inclusion of detailed case studies and worked examples, preferably implemented using recognized statistical software, is therefore essential.

Please contact us if you have an idea for a book for the series.

Forthcoming

**Ernst Wit, Veronica Vinciotti, Vilda Purutcuoglu**

January 01, 2021

An introduction to a new paradigm in social, technological, and scientific discourse, this book presents an overview of statistical methods for describing, modeling, and inferring biological networks using genomic and other types of data. It covers a large variety of modern statistical techniques,...

Forthcoming

**Simon John Godsill, Peter Bunch**

January 01, 2021

The importance of Bayesian signal processing methods have grown over the past decade. A wealth of Bayesian tools are available for solving highly complex inference problems, including particle filters, Markov chain Monte Carlo, and variational Bayes. These methods can be utilized to solve some of...

Forthcoming

**Yulei He, Guangyu Zhang, Chiu-Hsieh Hsu, Nathaniel Schenker**

January 01, 2021

**Diana Cole**

May 18, 2020

Statistical and mathematical models are defined by parameters that describe different characteristics of those models. Ideally it would be possible to find parameter estimates for every parameter in that model, but, in some cases, this is not possible. For example, two parameters that only ever...

**Rex F. Galbraith**

March 04, 2020

Statistical analyses of the numbers, lengths, and orientations of fission tracks etched in minerals yield dating and thermal history information valuable in geological and geoscience applications, particularly in oil exploration. Fission tracks can be represented mathematically by a stochastic...

**Simon Washington, Matthew G. Karlaftis, Fred Mannering, Panagiotis Anastasopoulos**

February 12, 2020

The book's website (with databases and other support materials) can be accessed here. Praise for the Second Edition: The second edition introduces an especially broad set of statistical methods … As a lecturer in both transportation and marketing research, I find this book an excellent textbook for...

**Dankmar Bohning, Sasivimol Rattanasiri, Ronny Kuhnert**

October 21, 2019

Providing reliable information on an intervention effect, meta-analysis is a powerful statistical tool for analyzing and combining results from individual studies. Meta-Analysis of Binary Data Using Profile Likelihood focuses on the analysis and modeling of a meta-analysis with individually pooled...

**Rongling Wu, Min Lin**

October 18, 2019

Due to the tremendous accumulation of data for genetic markers, pharmacogenomics, the study of the functions and interactions of all genes in the overall variability of drug response, is one of the hottest areas of research in biomedical science. Statistical and Computational Pharmacogenomics...

**Subhash R. Lele, Joan T. Richtsmeier**

October 07, 2019

Natural scientists perceive and classify organisms primarily on the basis of their appearance and structure- their form , defined as that characteristic remaining invariant after translation, rotation, and possibly reflection of the object. The quantitative study of form and form change comprises...

**Peter J. Diggle, Emanuele Giorgi**

March 11, 2019

Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the public health problems that are the focus of this book, the...

**Kenneth G. Russell**

December 26, 2018

Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM, little information is available on how to collect the data that are to be...