Description
One of the most important contributions in the field of statistics in late twentieth century was, without any doubt, the introduction by J. Nelder and R. W. Wedderburn of the concept of the generalized linear model (GLM) in 1972. The GLM constitutes the natural generalization of classic linear models, and includes, as particular cases, linear regression, the analysis of variance, the analysis of covariance, Poisson regression, logistic regression, logit regression, log-lineal models, multinomial response models, as well as certain models of the analysis of survival and temporary series.nThe contents of this book are based on two large and intimately related pillars: "statistical modelling" as a general procedure and GLM, generalized linear model, as a conceptual framework for the inferential study of the relationship between the group of variables.nThe present volume should be understood as a natural continuation of the project that began with the book entitled Del Contraste de Hipótesis al Moldeado Estadístico (Losilla, J. M.; Navarro, J. B.; Palmer, A.; Rodrigo, M. F.; i Lligo, M., 2005), where the approximation of statistical modelling is presented from the linear regression model, subsuming the classic tests of bivariate hypothesis contrast. Throughout the chapters of this "second" volume the field of application of statistical modelling is extended to the main models, which alongside the linear regression model and sharing with it the same structure, certain properties and a common method for estimation, shapes GLM.n
