Confidence Intervals in Generalized Regression Models PDF
323 Pages·2008·2.977 MB·English
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.
Preview Confidence Intervals in Generalized Regression Models
Description:
A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation—the generalized regression model (GRM)—of various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data and its statistical model. Provides a Large Collection of Models The book encompasses a number of different regression models, from very simple to more complex ones. It covers the general linear model (GLM), nonlinear regression model, generalized linear model (GLIM), logistic regression model, Poisson regression model, multinomial regression model, and Cox regression model. The author also explains methods of constructing confidence regions, profile likelihood-based confidence intervals, and likelihood ratio tests. Uses Statistical Inference Package to Make Inferences on Real-Valued Parameter Functions Offering software that helps with statistical analyses, this book focuses on producing statistical inferences for data modeled by GRMs. It contains numerical and graphical results while providing the code online.
See more
The list of books you might like
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.
