How do I find out about the standards for writing regression packages in R?

Question

As part of my job, I need to fit a bunch of 'generalised logistic' (GL)* regression models (with some special restrictions that are not pertinent to this question). There is no package that currently allows me to do this so I have written my own function which just optimises the likelihood. It is messy, and not that general at the moment as it is tailored towards the specific job I need it to do.

I was thinking about turning it into a more general package, it would be the first I had written.

My questions are:

1) Am I missing a trick, and is it possible to just bolt on my own link function to GLM rather than writing it from scratch?

2) Is their information somewhere on the standards expected for a regression package, e.g., expected "summary" output, standardised names for output, standard formula input, etc?

3) Are there any good "how to write a package in R" resources that you could recommend?

I'm happy to be more specific if needed. Many thanks for any replies.

Best.

• https://en.wikipedia.org/wiki/Generalised_logistic_function

Answer 1

It should be possible to create your own GLM link function. You can do the following:

my_link_function <- function(mu) 
{
  # Body of your link function
}

my_inverse_link_function <- function(eta) 
{
  # Body of your inverse link function
}

my_derivative_function <- function(eta)
{
  # function describing dmu / delta
}

my_valid_eta_function <- function(eta)
{
  # return TRUE if eta is in domain of inverse_link_function, otherwise FALSE
}

my_link <- list(linkfun  = my_link_function,
                linkinv  = my_inverse_link_function,
                mu.eta   = my_derivative_function,
                valideta = my_valid_eta_function,,
                name     = "my_link")
class(my_link) <- "link-glm"

Now you can do this:

glm(my_var1 ~ my_var2, family = binomial(my_link))