This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs.

Metal-Organic Frameworks for Environmental Applications examines this important topic, looking at potential materials and methods for the remediation of pressing pollution issues, such as heavy-metal contaminants in water streams, radioactive waste disposal, marine oil-spillage, the treatment of textile and dye industry effluents, the clean-up of trace amounts of explosives in land and water, and many other topics. This survey of the cutting-edge research and technology of MOFs is an invaluable resource for researchers working in inorganic chemistry and materials science, but it is also ideal for graduate students studying MOFs and their applications.

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs.