r descr_models("linear_reg", "glm")
This engine has no tuning parameters but you can set the family
parameter (and/or link
) as an engine argument (see below).
linear_reg() %>% set_engine("glm") %>% translate()
To use a non-default family
and/or link
, pass in as an argument to set_engine()
:
linear_reg() %>% set_engine("glm", family = stats::poisson(link = "sqrt")) %>% translate()
However, the documentation in [stats::glm()] assumes that is specific type of case weights are being used:"Non-NULL weights can be used to indicate that different observations have different dispersions (with the values in weights being inversely proportional to the dispersions); or equivalently, when the elements of weights are positive integers w_i
, that each response y_i
is the mean of w_i
unit-weight observations. For a binomial GLM prior weights are used to give the number of trials when the response is the proportion of successes: they would rarely be used for a Poisson GLM."
The "Fitting and Predicting with parsnip" article contains examples for linear_reg()
with the "glm"
engine.
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.