Given certain data, and we need to create models (xgboost, random forest, regression, etc). Each one of them has its constraints regarding data types. Errors are not clear, here's a new function to speed up model creation.

Technically speaking, there is no need to evaluate the variable importance and to perform the variable selection in the training of a GRNN. It’s also been a consensus that the neural network is a black-box model and it is not an easy task to assess the variable importance in ...

I was recently making some arrangements for the 2020 eclipse in South America, which of course got me thinking of the day we were lucky enough to have a path of totality come to us. We have a weather station that records local temperature every 5 minutes, so after the eclipse I ...

Introduction:On August 2, 2016 then Trump campaign manager, Paul Manafort, gave polling data to Konstantin Kalimnik a Russian widely assumed to be a spy. Before then Manafort ordered his protege, Rick Gates, to share polling data with Kilmnik. Gates periodically did so starting April or May. The Mueller Report stated it ...

Last week’s post just happened to use MCMCglmm as an example of an R package that can get confused by tibble-style data frames. To make that example, I simulated some pedigree and trait data. Just for fun, let’s look at the simulation code, and use MCMCglmm and AnimalINLA ...

Often data you’re working with has abstract column names, such as (x1, x2, x3…). Typically, the first step I take when renaming columns with r is...

After refactoring my programming so that it was only about 10 lines of code, using 12 functions I wrote an loaded in via the source command, I went through all the steps in Part 1 of this blog post and Part 2 of this blog post to set up the R package infrastructure using ...

A major advantage of General Regression Neural Networks (GRNN) over other types of neural networks is that there is only a single hyper-parameter, namely the sigma. In the previous post (https://statcompute.wordpress.com/2019/07/06/latin-hypercube-sampling-in-hyper-parameter-optimization), I’ve shown how to use the random search strategy to find a close-to-optimal value ...

In Part 1, I set up RStudio with usethis, and created my first Minimum Viable R Package (MVRP?) which was then pushed to Github to create a new repository. I added a README: Things were moving along just fine, until I got this unkind message (what do you mean NOT an ...

(What does this new package do? Find out here.) I have had package-o-phobia for years, and have skillfully resisted learning how to build a new R package. However, I do have a huge collection of scripts on my hard drive with functions in them, and I keep a bunch of ...

I have been recently confronted to the issue of finding similarities among time-series and though about using k-means to cluster them. To illustrate the method, I’ll be using data from the Penn World Tables, readily available in R (inside the {pwt9...

Intro I was playing around generating fractals in R when I realized the monochromatic green Barnsely Fern I had on my screen didn’t quite look like the leaves I could see outside my window. It was already Fall. In this post I describe a technique to generate a Barnsley ...

Package wyz.code.offensiveProgramming version 1.1.12 is available on CRAN. If you are interested in reducing time and efforts to implement and debug R code, to generate R documentation, to generate test code, then you may consider using this package...

Last week, we started a new course titled “Statistical Programming and Open Science Methods”. It is being offered under the research program of TRR 266 “Accounting for Transparency” and enables students to conduct data-based research so that...

Attribution modelling in R an example Here I am going into some examples in attribution modelling in R. It is a complex topic and much more can be said about it than I will be able to do here. I will here go hands on mostly into the markov model ...