New version 0.2.2 of
đŠ distributions3 on #CRAN, together with @alexpghayes
#rstats
- Object-oriented computations on (vectors of) probability distributions
- More model-based probabilistic forecasts
- simulate() from fitted likelihood models
- Support in #tibble in addition to data.frame
Documentation at:
Tools to create and manipulate probability distributions using S3. Generics pdf(), cdf(), quantile(), and random() provide replacements for base R's d/p/q/r style functions. Functions and arguments have been named carefully to minimize confusion for students in intro stats courses. The documentation for each distribution contains detailed mathematical notes.
Recently ran into a disturbing #ChatGPT result: I asked it to translate a #python function written by Mathieu Daëron (https://github.com/mdaeron/D47crunch) to #R, using the #tidyverse and a #tibble. I had done this manually for my #rpackage https://github.com/isoverse/clumpedr/ and wanted to see how they would compare.
It returned my code literally, including TODO notes, comments, and #roxygen skeleton. But it did not say where it got the code from, even when pressed. My R package is on #github under #GPL 3. Thoughts?
Python library for processing and standardizing carbonate clumped-isotope analyses, from low-level data out of a dual-inlet mass spectrometer to final, âabsoluteâ Î47 and Î48 values with fully prop...
Every time I work with data.table I think what a great package. The speed alone is great. What I also like is the tibble-like behavior when displaying data.