Generalized Linear Models (GLM) is a general class of statistical models that includes many commonly used models as special cases. For example, the class of GLMs that includes linear regression, analysis of variance and analysis of covariance, is a special case of GLIMs. GLIMs also include log-lin
Generalized linear models. An applied approach
โ Scribed by Ulf Olsson
- Publisher
- Studentlitteratur
- Year
- 2002
- Tongue
- English
- Leaves
- 243
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
The assessment of risks posed by natural hazards such as floods, droughts, earthquakes, tsunamis or cyclones, may not reflect the full range or magnitude of events possible. As human populations grow, especially in hazard-prone areas, methods for accurately assessing natural hazard risks are becoming increasingly important. Jonathan Nott describes the many methods used to reconstruct such hazards from natural long-term records. He demonstrates how long-term records are essential in gaining a realistic understanding of the variability of natural hazards, and how short-term historical records can often misrepresent likely risks General linear models -- Generalized linear models -- Model diagnostics -- Models for continuous data -- Binary and binomial response variables -- Response variables as counts -- Ordinal response --Additional topics
๐ SIMILAR VOLUMES
Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview
Generalized Linear Models: A Unified Approach provides an introduction to and overview of GLMs, with each chapter carefully laying the groundwork for the next. Authors Jeff Gill and Michelle Torres provide examples using real data from multiple fields in the social sciences such as psychology, educa
This text aims to provide a clear and deep understanding of the general linear model using simple statistical ideas. Elegant geometric arguments are also invoked as needed and a review of vector spaces and matrices is provided to make the treatment self-contained. Complex, matrix-algebraic methods,
This text aims to provide a clear and deep understanding of the general linear model using simple statistical ideas. Elegant geometric arguments are also invoked as needed and a review of vector spaces and matrices is provided to make the treatment self-contained. Complex, matrix-algebraic methods,