R-bloggers

R-bloggers is a platform that leverages the content from various documents to provide concise summaries for its audience. The platform serves as a hub for information and insights related to a wide range of topics. By summarizing the content from diverse sources, R-bloggers aims to offer valuable and easily digestible information to its readers. The platform’s summaries are designed to provide a quick overview of the key points and insights covered in the original documents, making it a convenient resource for individuals interested in staying informed about the latest developments in various fields.

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Major Update for revss Package for R – v3.1.0

R-bloggers

The revss Package for R Receives Major Update to Version 3.1.0 This is a big one! The revss package for R, which provides robust estimation for small samples, received a major, breaking update. The en...

Getting to the bottom of TMLE: targeting in action

R-bloggers

In the previous post, I worked my way through some key elements of TMLE theory as I try to understand how it all works. At its essence, TMLE is focused on getting the efficient influence function (EIF...

Bio7 3.6 Released

R-bloggers

17.03.2026 A new release of Bio7 is available.The application Bio7 is a free and open-source integrated development environment for ecological modeling, scientific image analysis and statistical analy...

stats19 v4.0.0: 45 Years of UK Road Crash Data, Unified

R-bloggers

The stats19 R package has been updated to version 4.0.0. The main change is a unified column schema that lets you work with 45 years of UK road crash data (1979 to 2024) without running into mismatche...

Prompting large language models for quality ecological statistics

R-bloggers

Like it or not, everyone is using large languageden models to help do their statistics. There’s a lot of claims made about whether LLMs can or can’t do useful ecological statistics. In our new paper “...

Option pricing using time series models as market price of risk Pt.3

R-bloggers

Option pricing using time series models as market price of risk and bootstrap resampling Continue reading: Option pricing using time series models as market price of risk Pt.3

Can I use Skills with Posit Assistant for the RStudio IDE?

R-bloggers

I recently shared a blog post on Claude Skills for R Users, featuring excellent Skills developed by several community members. It brought me a lot of joy to share these impactful resources from the co...

Little useless-useful R functions – Date Palindrome

R-bloggers

It is a rare thing that a date can be a palindrome. But it happens. And the idea is the following, to cover all different date formats and for the given period And to do some useless extraction of the...

Exploring Piperacillin/Tazobactam Probability of Target Attainment (PTA) in Pseudomonas

R-bloggers

Exploring pip/tazo PTA for Pseudomonas using popPK simulation. Key finds: 30-min infusions fall short of 90% PTA at MIC 16; prolonged infusion helps, but neutropenic fever population sees the biggest ...

Text Analytics in R: Dense embeddings and RAG pipeline with ragnar and ellmer

R-bloggers

Required Packages install.packages(c("ragnar", "ellmer", "dplyr", "ggplot2", "tibble")) library(ragnar) library(ellmer) library(dplyr) library(ggplot2) library(tibble) Introduction This earlier post, ...

Bayesian Linear Regression in R: A Step-by-Step Tutorial

R-bloggers

Bayesian linear regression is one of the best ways to learn Bayesian modeling in R because it combines familiar regression ideas with a more realistic treatment of uncertainty. Instead of estimating a...

Three Posit Platform Features Worth Knowing About

R-bloggers

We recently ran a session on Posit platform updates, the kind of features that don’t always make it onto your radar but can make a real difference once you know they’re there. This post covers the thr...