R-bloggers

You can read the original post in its original format on Rtask website by ThinkR here: Beyond Functions: How to Enrich an R Package with Data As package developers, we often focus on custom functions, their documentation, and unit testing. To provide a more complete user experience, it can be ...

Adding a suffix to column names in R is a common task that can help in organizing and managing data frames, especially when dealing with multiple datasets. This guide will walk you through the process using base R functions, making it accessible...

Gradient boosting with any regression algorithm in Python package mlsauce. Part2, R version

As package developers, we often focus on custom functions, their documentation, and unit testing. To provide a more complete user experience, it can be helpful to include data within the package. Here’s everything you need to know! Short on tim...

Methods for comparing spatial patterns in raster data This is the first part of a blog post series on comparing spatial patterns in raster data. Comparison of spatial patterns in raster data is a part of many types of spatial analysi...

When looking for a copula I could simulate from (rather than the Gaussian copula), I found an algorithm for the Ali–Mikhail–Haq copula that was proposed by Kumar (2010) as reproduced above. But the method seriously fails in that the range of (U,V) resulting from the simulation does not ...

Last week, we had an “mid-term” exam, for our introduction to statistical learning course.  The question is simple: consider three points, , here Consider here some linear models, estimated using least square techniques, what would be the leave-one-out cross-validation MSE ? I like this exercise since we can compute everything easily, by ...

The tidymodels framework provides a cohesive set of packages for modeling and machine learning in R, following tidyverse principles. In this post, we’ll build a realistic credit scoring model using tidymodels. Credit scoring models are used by fi...

If you’re a biostatistician or clinical software developer, you’ve probably felt the weight of trying to meet GxP standards while navigating the FDA/EMA submission process. It’s not just about getting the software right—it’s about ensuring safety, quality, and compliance, all under tight timelines. It ...

Linux is a powerful operating system that offers a wide range of tools for managing files and processes. One of the most essential concepts in Linux is I/O redirection, which allows users to control the flow of data between commands and files. T...

Summary Why? How? Examples [view raw Rmd] Summary This post introduces the POLYGON FULL geometry, new in sf 1.0-18 which appeared on CRAN Today. Why? Polygons delineate a two-dimensional bound area. The OGC simple feature access standard...

Hey there, ready to get your R code under control? Whether you’re working on your own or in a small team, managing your code can sometimes feel like juggling too many things at once. But don’t worry — there’s an easy way to stay on top of everything. ...

I have been asked recently by a colleague of mine how to extract the variance from a model estimated using adam() function from the smooth package in R. The problem was that that person started reading the source code of the forecast.adam() and got lost between the lines (this ...

Are you confident in your data analysis?  Shapiro-Wilk test in R is essential to ensuring your data fits a normal distribution, but how well do you understand its mechanisms and implications? Can you enhance the reliability of your research findings an...

Introduction Combining data frames is a fundamental task in data analysis, especially when dealing with datasets that have different structures. In R, there are several ways to achieve this, using base R functions, the dplyr package, and the da...