R-bloggers

Forecasting financial markets, such as the STOXX Europe 600 Index, presents a classic Machine Learning challenge: the data is inherently noisy, non-stationary, and highly susceptible to sudden market events. To tackle this, we turn to Automated Machine Learning (AutoML)—specifically the powerful, scalable framework provided by H2O.ai and integrated ...

K2 – CC BY-NC-ND by Marcelo Aguilar Day 1 of 30DayMapChallenge: « Points ». Mapping the peaks above 8000 m, also known as the eight-thousanders. Config library(httr) library(glue) library(dplyr) library(tidyr) library(purrr) library(tibble) library(stringr) library(sf) library(leaflet) Data Several non-trivial options for obtaining the data: english Wikipedia doesn’...

Last time we used a quirky dataset to get acquainted with Generalised Linear Models. If you recall, the dataset is a count of deaths by horse kick, where every year all the corps in the army had some non-negative integer number of deaths and we ...

Hi pharmaverse community, On behalf of the council we wanted to update you on 2 council members who are passing on the baton to new representatives from their respective companies. Firstly, Michael Rimler (who is one of our original co-founder...

Here we go again! I ran the Mainova Frankfurt Marathon 2025 and wanted to look at the race results. How can we do this using R? I couldn’t see an easy way to download the data, so I used R to scrape them. Note that these times are currently provisional, ...

If this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee. It shall be used to continue my Open Source efforts. You can send me questions for the blog using this form and subscribe to receive an email when there is a new ...

If this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee. It shall be used to continue my Open Source efforts. You can send me questions for the blog using this form and subscribe to receive an email when there is a new ...

Last time I quickly introduced my latest package, {rixpress}, but I think that to really understand what {rixpress} brings to the table, one needs to solve the same problem without it. And incidentally, I think that this exercise also show...

In today’s data-driven world, strong analytical and programming skills are essential for success. Whether you’re just starting your data journey or looking to expand your expertise, Jumping Rivers offers training that combines real-world experien...

If this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee. It shall be used to continue my Open Source efforts. You can send me questions for the blog using this form and subscribe to receive an email when there is a new ...

This post demonstrates the implementation of deterministic shift adjustments in an arbitrage-free pricing framework using R and the NMOF package. I generate synthetic yield curve data using Nelson-Siegel and Nelson-Siegel-Svensson models, estimate short rates using three different methods, simulate interest rate paths, compute unadjusted zero-coupon bond prices, apply deterministic shift ...

Computational Methods fastfocal v0.1.3: Provides a fast moving-window (“focal”) and buffer-based extraction for raster data using the terra package. Automatically selects between a C++ backend and a Fast Fourier Transform (FFT) backend depend...

If this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee. It shall be used to continue my Open Source efforts. You can send me questions for the blog using this form and subscribe to receive an email when there is a new ...

If this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee. It shall be used to continue my Open Source efforts. You can send me questions for the blog using this form and subscribe to receive an email when there is a new ...

Implementing three methods for constructing instantaneous short rates from historical yield curves, along with a deterministic shift adjustment to ensure arbitrage-free pricing of caps and swaptions.

This is a post about the famous double descent phenomenon in machine learning. I aim to constrct the simplest possible example of double descent and explain exactly how it arises and why it doesn’t contradict the bias-variance tradeoff. I was inspired...

Following a suggestion by Christian Hennig at JSM 2024, I started working with my PhD student Dana Naderi on a detailed assessment of the method we proposed in 2009 with Darren Wraith for evidence approximation. (The method was briefly mentioned in a Physical Review paper and also briefly illustrated in our 2010 San ...