Methods and Models in Statistics

Methods and Models in Statistics
Author: Niall M. Adams
Publisher: World Scientific
Total Pages: 261
Release: 2004
Genre: Mathematics
ISBN: 1860944639

John Nelder was one of the most influential statisticians of his generation, having made an impact on many parts of the discipline. This book contains reviews of some of those areas, written by top researchers. It is accessible to non-specialists, and is noteworthy for its breadth of coverage.

Methods And Models In Statistics: In Honour Of Professor John Nelder, Frs

Methods And Models In Statistics: In Honour Of Professor John Nelder, Frs
Author: David J Hand
Publisher: World Scientific
Total Pages: 261
Release: 2004-07-06
Genre: Mathematics
ISBN: 1783260696

John Nelder was one of the most influential statisticians of his generation, having made an impact on many parts of the discipline. This book contains reviews of some of those areas, written by top researchers. It is accessible to non-specialists, and is noteworthy for its breadth of coverage.

Nature

Nature
Author: Sir Norman Lockyer
Publisher:
Total Pages: 732
Release: 2007
Genre: Electronic journals
ISBN:

Library Journal

Library Journal
Author:
Publisher:
Total Pages: 1022
Release: 2004
Genre: Libraries
ISBN:

Includes, beginning Sept. 15, 1954 (and on the 15th of each month, Sept.-May) a special section: School library journal, ISSN 0000-0035, (called Junior libraries, 1954-May 1961). Also issued separately.

Data Analysis Using Hierarchical Generalized Linear Models with R

Data Analysis Using Hierarchical Generalized Linear Models with R
Author: Youngjo Lee
Publisher: CRC Press
Total Pages: 242
Release: 2017-07-06
Genre: Mathematics
ISBN: 135181155X

Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs, factor and structural equation models, robust modelling of random effects, models including penalty and variable selection and hypothesis testing. This example-driven book is aimed primarily at researchers and graduate students, who wish to perform data modelling beyond the frequentist framework, and especially for those searching for a bridge between Bayesian and frequentist statistics.

Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics

Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
Author: Daniel Sorensen
Publisher: Springer Science & Business Media
Total Pages: 745
Release: 2007-03-22
Genre: Science
ISBN: 0387954406

This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style and contain much more detail than necessary. Here, an effort has been made to relate biological to statistical parameters throughout, and the book includes extensive examples that illustrate the developing argument.

Bayesian Theory and Applications

Bayesian Theory and Applications
Author: Paul Damien
Publisher: Oxford University Press
Total Pages: 717
Release: 2013-01-24
Genre: Mathematics
ISBN: 0199695601

This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field.

Statistical Methods in Biology

Statistical Methods in Biology
Author: S.J. Welham
Publisher: CRC Press
Total Pages: 606
Release: 2014-08-22
Genre: Mathematics
ISBN: 1439808783

Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors’ experience. Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat® statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R. By the time you reach the end of the book (and online material) you will have gained: A clear appreciation of the importance of a statistical approach to the design of your experiments, A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables, Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly, An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working. The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.

Yeasts

Yeasts
Author: Alexandre Guilliermond
Publisher: Merchant Books
Total Pages: 452
Release: 2006-08-01
Genre: Science
ISBN: 9781933998237