mark padgham

yeah, the details are all pretty easy. The difficult and important thing was figuring out that the `get_columns` function should return a **list**. From that point on, it's all easy

@huanfachen Much of this has already been documented in previous issues. Inclusion of distance matrices is in #77, including all code which will eventually be merged, and the weights issue...

Even I've kinda gone off that these days in favour of `mapview` for the kinds of small-ish data sets used here. Sometimes, for better or worse, interactivity is soooo much...

Awesome package Nick! I'll be telling lotsa peeps about this. In the meantime, I've submitted [`geodist`](https://github.com/hypertidy/geodist) to CRAN, if that helps here. (It's currently still in perjury, but should appear...

Thanks a lot @jsta for these very useful comments. It would be great if you could transform them into direct edits and submit a pull request, especially as direct contributions...

Thanks for the responses @sevvandi, and no worries about no responding earlier. I didn't end up using {dobin} at the time i would have liked because of this scaling issue,...

Hi Anthony, thanks for asking. The manuscript for this package never ended up getting published, unfortunately. Most of the work can be understood by reading the main reference linked at...

Yeah, i do think a `k`-neighbours scheme would be useful here - all the distance data are `arma` matrices, so that's dead easy to just use `armadillo` to implement a...

The plan: Implement a `nbs` param with options of `"tri", "trin"` or numeric. The first is straight Delaunay; the second includes all neighbours with `d < max (dist (tri))`, and...

Thanks for your quick response Nick. I noticed your very independent C++ vs R structure, extending to stand-alone C++ test suite, which is actually really impressive. My approach is generally...