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Create a HGLM model object.
hglm_model( x, y, family = gaussian(), weights = NULL, frame = NULL, solver = "auto", approx = FALSE )
An object of class "hglm_model".
"hglm_model"
a numeric matrix giving the design matrix.
a vector giving the response variables.
a description of the error distribution and link function to be used in the model.
an optional vector of 'prior weights' to be used for the estimation.
an optional model frame object.
a character string giving the name of the solver to be used for the estimation.
a logical; if TRUE uses linear approximation of log-likelihood.
TRUE
No standardization prior to fitting the model takes place. If a x or y standardization is wanted, the user has to do this beforehand.
dat <- rhglm(100, c(1, 2, -3, 4, 5, -6)) x <- model.matrix(y ~ ., data = dat) hglm_model(x, y = dat[["y"]])
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