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ACCURACIES IN THE THEORY OF THE LOGISTIC MODELS PRECISIONES EN LA TEORÍA DE LOS MODELOS LOGÍSTICOS
Revista Colombiana de Estadística, 2006 The logistic models are studied, as a kind of generalized lineal models. A theorem is showed about existence and uniqueness of ML-estimates of the estimation of the logistic regression coefficients and the method in order to calculate it. According to an
Llinás Humberto Jesús
doaj
Introducing COZIGAM: An R Package for Unconstrained and Constrained Zero-Inflated Generalized Additive Model Analysis [PDF]
Zero-inflation problem is very common in ecological studies as well as other areas. Nonparametric regression with zero-inflated data may be studied via the zero-inflated generalized additive model (ZIGAM), which assumes that the zero-inflated responses ...
Kung-Sik Chan, Hai Liu
core
Generalized bi-additive modelling for categorical data [PDF]
Generalized linear modelling (GLM) is a versatile technique, which may be viewed as a generalization of well-known techniques such as least squares regression, analysis of variance, loglinear modelling, and logistic regression.
Koning, A.J., Groenen, P.J.F.
core
Review of Generalized Estimating Equations by Hardin and Hilbe [PDF]
The new book by Hardin and Hilbe (2003) is reviewed.
Steven Stillman
core
An exact, unified distributional characterization of statistics used to test linear hypotheses in simple regression models [PDF]
The Wald, likelihood ratio and Lagrange multiplier test statistics are commonly used to test linear restrictions in regression models. It is shown that for testing these restrictions in the classical regression model, the exact densities of these test ...
Parker, Thomas
core
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Model Checks for Generalized Linear Models
Scandinavian Journal of Statistics, 2002In this paper we propose and study non‐parametric tests for the validity of (composite) Generalized Linear Models with a given parametric link structure, which are based on certain empirical processes marked by the residuals. When properly transformed to their innovation part the resulting test statistics are distribution‐free.
Lixing Zhu, Winfried Stute
exaly +3 more sources
Use generalized linear models or generalized partially linear models?
Statistics and Computing, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xinmin Li +3 more
openaire +3 more sources
2015
This article provides an introduction into the statistical analysis of neuroimaging data using the general linear model. The analysis allows a flexible use of various models offering a wide range of statistical tests for the analysis of typical neuroimaging experiments. A short introduction to the general linear model is provided using simple examples.
Kiebel, S. +1 more
openaire +2 more sources
This article provides an introduction into the statistical analysis of neuroimaging data using the general linear model. The analysis allows a flexible use of various models offering a wide range of statistical tests for the analysis of typical neuroimaging experiments. A short introduction to the general linear model is provided using simple examples.
Kiebel, S. +1 more
openaire +2 more sources