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Everything about Generalized linear model
Class of statistical models
In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Generalized linear modelA 5-minute orientation
- Pick up a classic book: Parallel Programming with Co-ArraysThe most-reprinted book on the subject
- Read the landmark paper: Generalized Linear Array Models with Applications to Multidimensional SmoothingCited 147 times
- Go sideways: Binomial regressionA closely related topic
- Go sideways: Vector generalized linear modelA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
đź“š Books worth reading
Parallel Programming with Co-ArraysRobert W. Numrich, John Ker Reid · 2012
Data structures and algorithm analysis in CMark Allen Weiss · 1993
Data structures & algorithm analysis in JavaMark Allen Weiss · 1999
Parallel Programming in C with MPI and OpenMPMichael J. Quinn · 2003
Digital systems testing and testable designMiron Abramovici · 1990
Computer algorithmsEllis Horowitz · 1997
Programming Massively Parallel ProcessorsDavid Kirk, Wen-Mei W. Hwu · 2010
Data structures & algorithms in JavaRobert Lafore · 2003
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
- Binomial regression In statistics, binomial regression is a regression analysis technique in which the response (often referred to as Y) has a binomial distribution: it is…
- Vector generalized linear model In statistics, the class of vector generalized linear models (VGLMs) was proposed to enlarge the scope of models catered for by generalized linear models…
- Logistic regression In statistics, a logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent…
- Generalized functional linear model The generalized functional linear model (GFLM) is an extension of the generalized linear model (GLM) that allows one to regress univariate responses of…
- Binary regression In statistics, specifically regression analysis, a binary regression estimates a relationship between one or more explanatory variables and a single output…
- Variance function In statistics, the variance function is a smooth function that depicts the variance of a random quantity as a function of its mean. The variance function…
- Poisson regression In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression…
- Probit model In statistics, a probit model is a type of regression where the dependent variable can take only two values. The word is a portmanteau, coming from probability…