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Generalized Linear Modeling with H2O Tomas NykodymAriel Roam Wang Tom Kraljevichttp://h2o.gitbooks.io/glmwithh2o/ August 2015: Third EditionGeneralized Linear Modeling with H2O by Tomas Anybody, Ariel
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Generalized linear modeling is a statistical approach that extends linear regression to allow for different types of dependent variables and error distributions.
Researchers, statisticians, and data analysts who are analyzing data with non-normal and non-continuous dependent variables may use generalized linear modeling.
Generalized linear modeling is typically filled out using statistical software such as R, SAS, or SPSS.
The purpose of generalized linear modeling is to model relationships between dependent and independent variables when the assumptions of traditional linear regression are not met.
The variables used in the model, the model coefficients, the error distribution assumption, and the goodness-of-fit statistics must be reported.
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