NEWS

hIRT 0.5.0 (2026-10-28)

The computational core is now written in C++ (Rcpp/RcppArmadillo): the E-step, the item-level M-step (a Newton solver for the weighted cumulative logit model, replacing rms::lrm.fit() and glm.fit() inside the EM loop), the level-II variance regression, and the scores used for standard errors. Estimates, standard errors, and log-likelihoods agree with version 0.4.0 to numerical precision, and fits are roughly 10 to 100 times faster.
The E-step is computed on the log scale, so it no longer underflows when a respondent answers many items.
hgrmDIF() pools respondents who share the same DIF covariate pattern in the M-step, which makes it much faster when x0 is categorical.

Removed dependency on the archived package pryr; function composition is now done in base R.
Added hgrmDIF() for differential item functioning in the graded response model.