Peter Ellis
Peter Ellis
I've started work on a separate package at https://github.com/ellisp/forecastxgb-r-package. Very early days yet but looks promising.
See also https://github.com/rstudio/rmarkdown/issues/609 which suggests the answer is to put rmarkdown in suggests:, but it already is.
Someone else with the same problem: http://cran.us.r-project.org/web/checks/check_results_dendextend.html
Thanks for pointing this out. I will remove that dependency. I think it is only needed for the nzcensus build (this repo builds two R packages) but will fix that...
This is somewhat resolved if we use the state space model, which is more rigorous and coherent in treating the whole thing at once.
Off-line I agreed so long as it mentions me, the URL, the blog title and Peter's Stats Stuff it is ok. I need to decide something and put it on...
Yes I think this would help and I'll import this when it's ready. I think moving holidays (Easter etc) is a must at some point, although of course people can...
Rob Hyndman [doesn't know of](http://robjhyndman.com/hyndsight/benchmarks) any data collections of the sort I'm looking for so I guess I will need to do simulations. They won't be great for real performance...
Does the "spirit level" stack up? See https://twitter.com/nicolas_sommet/status/1045315275825041409?s=19
Noting, old code I had like: `colourScale = JS('d3.scale.ordinal().range(["#7d3945","#e0677b", "#244457"])')` now works if it is changed to: `colourScale = JS('d3.scaleOrdinal().range(["#7d3945","#e0677b", "#244457"])')`