Add `intercept` option to canned forecasters, or maybe some convolutional model

[brookslogan]

I was hoping to make/approximate a convolution-based forecaster & get its kernel with arx_forecaster.

E.g. something like

fc <- cases_deaths_subset %>%
  arx_forecaster("death_rate_7d_av", "case_rate_7d_av", args_list = arx_args_list(intercept = FALSE))
fc$epi_workflow %>% extract_fit_engine()

but there's no such setting, and it's not clear how to even achieve this. I think I got this working for quantile regression in an epipredict test somewhere, and there is maybe this approach for linear_reg (and I guess also quantile_reg). But that seems like something that has to be done inside the canned forecaster itself.

[brookslogan]

Guess for my purpose, getting coefficients to use in some other example, I'll need to work around this to try to move forward. Might wait for others to say they have a use to up the priority.