For model calibration (esp via logistic regression), does anyone know of a statistical investigation of the properties of the resulting calibrated predictions?
IOW, if we use predictions from one model as inputs to another model, do we know the probability distribution of the final predictions?
Learn how to handle rows in R containing specific strings using base R's grep() and dplyr's filter() with str_detect(). Select or drop rows efficiently and enhance your data manipulation skills. Give it a try with your datasets for better data cleaning and organization.
It would enable the relatively easy creation of serious games and interactive exercises to learn R or statistics (or with the {rock} package, qualitative research); combining R with a simple game/adventure engine.
The April 2024 release of Posit Package Manager brings support for air-gapped PyPI repositories, more flexible curated CRAN repositories, performance improvements and more!
I just published a very basic introduction to using Boston's #Bluebikes bikeshare system data in #RStats. IMHO this is a great, underutilized dataset and is especially well-suited for student projects!
@streetsblogmass Not that I have time for this kind of stuff, but does the data link start and endpoints, to see where people are going? Or just volume at each station? (The transit nerd in me hopes the former; the privacy advocate hopes the latter)
@dcporter It includes start and end points, as well as start and end times, for every ride ever taken on Bluebikes. The tutorial I posted shows what else is in there.
I've always wanted to try to get axis text directly on my plots like I've seen in the New York Times and other places. Finally figured it out with the help of the {ggh4x} package. Code here: https://rfor.us/axistext#rstats