Documentation of difference between `dHN` and `dHN_V`

[ChloeRN]

Hi @scrogster and thanks a lot already for making this package.
I'm looking to use your half-normal detection function in a larger, integrated model and noticed that there are two version, dHN and dHN_V. You seem to use the latter in the example of your vignette, but it's not quite clear to the potential user what the difference between the two is. The difference is visible in the code, but probably not very enlightening to most.

Outlining the difference between the two versions would make a great addition to the function documentation!

[scrogster]

Thanks for the suggestion @ChloeRN, and thanks also for the fix to the documentation in your earlier pull request. I'll make some changes to the documentation and vignette along the lines you have suggested soon. As you've probably worked out from the code, dHN_V (and it's friend dHR_V) calculate the likelihood for a vector of distances with a common distance-detection function. The likelihood for the vector of distances is calculated in one step which can result in faster MCMC sampling. Conversely, dHN and dHR take only a single distance at a time so are better suited to situations where distances have parameters which are functions of covariates.