Log-linear model

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A log-linear model is a mathematical model that takes the form of a function whose logarithm is a first-degree polynomial function of the parameters of the model, which makes it possible to apply (possibly multivariate) linear regression. That is, it has the general form

\exp \left(c + \sum_{i} w_i f_i(X) \right)\,,

in which the fi(X) are quantities that are functions of the variables X, in general a vector of values, while c and the wi stand for the model parameters.

The term may specifically be used for:

The specific applications of log-linear models are where the output quantity lies in the range 0 to ∞, for values of the independent variables X, or more immediately, the transformed quantities fi(X) in the range −∞ to +∞. This may be contrasted to logistic models, similar to the logistic function, for which the output quantity lies in the range 0 to 1. Thus the contexts where these models are useful or realistic often depends on the range of the values being modelled.

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