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Generalized linear model

Known as: Link function, General linear modeling, Generalized linear models 
In statistics, the generalized linear model (GLM) is a flexible generalization of ordinary linear regression that allows for response variables that… 
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Related topics

Related topics

46 relations
Bias–variance tradeoffCount dataCrimeStatDiscriminative model

Papers overview

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Highly Cited
2010
Highly Cited
2010
Non-Life Insurance Pricing with Generalized Linear Models
Non-Life Insurance Pricing.- The Basics of Pricing with GLMs.- GLM Model Building.- Multi-Level Factors and Credibility Theory… 
Highly Cited
2010
Highly Cited
2010
Hyper-$g$ priors for generalized linear models
We develop an extension of the classical Zellner's g-prior to generalized linear models. The prior on the hyperparameter g is… 
Highly Cited
2006
Highly Cited
2006
Generalized linear array models with applications to multidimensional smoothing
Summary.  Data with an array structure are common in statistics, and the design or regression matrix for analysis of such data… 
Highly Cited
2002
Highly Cited
2002
Analysis of rainfall variability using generalized linear models: A case study from the west of Ireland
In the early 1990s a cluster of extreme flood events occurred in the south Galway region of western Ireland, and this led to… 
Highly Cited
2000
Highly Cited
2000
Generalized Linear Models: A Unified Approach
Introduction The Exponential Family Likelihood Theory and the Moments Linear Structure and the Link Function Estimation… 
Highly Cited
1995
Highly Cited
1995
A mixture likelihood approach for generalized linear models
A mixture model approach is developed that simultaneously estimates the posterior membership probabilities of observations to a… 
Highly Cited
1995
Highly Cited
1995
Local polynomial kernel regression for generalized linear models and quasi-likelihood functions
Abstract We investigate the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight… 
Highly Cited
1994
Highly Cited
1994
Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models
Introduction Generalized Linear Models and the Interpretation of Parameters Binary Logit and Probit Models Sequential Logit and… 
Highly Cited
1989
Highly Cited
1989
Collinearity in generalized linear models
This paper defines collinearity for generalized linear models (GLMs), investigates its consequences and proposes diagnostic… 
Highly Cited
1985
Highly Cited
1985
Dynamic Generalized Linear Models and Bayesian Forecasting
Abstract Dynamic Bayesian models are developed for application in nonlinear, non-normal time series and regression problems… 
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