[R] glm: modelling zeros as binary and non-zeroes as coming from a continuous distribution

Hello, I'd like to implement a regression model for extremely zero-inflated continuous data using a conditional approach, whereby zeroes are modelled as coming from a binary distribution, while non-zero values are modelled as log-normal. So far, I've come across two solutions for this: one, in R,

[R] Convert SAS NLMIXED code for zero-inflated gamma regression to R

I'm trying to run a zero-inflated regression for a continuous response variable in R. I'm aware of a gamlss implementation, but I'd really like to try out this algorithm by Dale McLerran that is conceptually a bit more straightforward. Unfortunately, the code is in SAS and I'm not sure how to re-wr