Poisson Regression: A Regression Approach for Count Response Variable
Vaibhav Chittora
Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan, Himachal Pradesh (173 230), India
DOI: NIL
Keywords: Count data, Linear regression, Parameters estimation, Poisson Distribution
Abstract
In regression analysis when the response variable is not continuous in nature or it is in number or count data in that situation response variable will not follow the assumption if regression. When the response variable is in number or count in that situation Poisson regression will give the valid estimates of the regression parameters. The characteristics of the Poisson regression mean and variance must be the same and our response variable should follow the assumption of Poisson model. Poisson Regression models are best used for modeling events where the outcomes are counts. Poisson Regression helps us analyze both count data and rate data by allowing us to determine which explanatory variables (X values) have an effect on a given response variable Y.
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Reference
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