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Everything about Poisson regression
Statistical model for count data
In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. A Poisson regression model is sometimes known as a log-linear model, especially when used to model contingency tables. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Poisson regressionA 5-minute orientation
- Skim a recent paper: Evolutionary support vector regression for monitoring Poisson profilesInfluential work since 2022
- Pick up a classic book: A First Look At Stochastic ProcessesThe most-reprinted book on the subject
- Read the landmark paper: A Modified Poisson Regression Approach to Prospective Studies with Binary DataCited 9,073 times
- Go sideways: Binomial regressionA closely related topic
- Go sideways: Vector generalized linear modelA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
A Modified Poisson Regression Approach to Prospective Studies with Binary Data
Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
Negative binomial and mixed Poisson regression
Generalized poisson regression model
Overdispersion and Poisson Regression
A Poisson ridge regression estimator
Regression Analysis of Poisson-Distributed Data
Restricted generalized poisson regression model
🆕 Influential since 2022
Evolutionary support vector regression for monitoring Poisson profiles
Efficient Posterior Sampling for Bayesian Poisson Regression
Ridge estimator in a mixed Poisson regression model
Optimal Poisson Subsampling for Softmax Regression
Choosing between modified Poisson and log-binomial regression: evidence for the superiority of modified Poisson regression under heterogeneous risk ratios
📚 Books worth reading
A First Look At Stochastic ProcessesJeffrey S. Rosenthal · 2019
Functional form and heterogeneity in models for count dataWilliam Greene · 2007
Statistical Analysis of Panel Count Data
Statistics for Biology and HealthJianguo Sun · 2013
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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