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The term "generalized linear model" is correct and usable in written English.
It can be used in statistics or data science contexts to describe a general class of models that link the expected mean of a response variable to a linear combination of predictor variables. An example sentence might be, "We used a generalized linear model to predict customer purchase behavior."
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Moreover, Sparse Generalized PLS extends Sparse PLS to the generalized linear model framework.
generalized linear model.
generalized linear model with stepwise feature selection.
Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM).
Pattern recognition utilized the generalized linear model, maximum likelihood fitting, for Poisson distributed uncertainties.
The analysis of variance was carried out using the generalized linear model (GLM) procedure in SAS.
A Generalized Linear Model was realized to predict the response of native ant species abundance.
The non-linear chopped model and the generalized linear model 4 appear to be equivalent.
A generalized linear model (glm) fit gave almost identical results (Figure 1).
Otherwise, the generalized linear model (GLM) will be preferred.
Generalized linear model using negative binomial family and log link.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com