| jmstate |
Python package for joint multi-state models. Implements estimation and prediction methods combining longitudinal markers with multi-state survival processes. |
| pitcp |
Python package implementing PIT-based correction conformal prediction, mapping a base nonconformity scores through a learned conditional CDF, producing asymptotically exact conditional coverage. |
| uniformbands |
Python package deriving asymptotic uniform confidence bands for survival functions in large probability. |
| sbcluster |
Python package implementing Spectral Bridges, a scalable topological clustering algorithm. Partitions data via Voronoï regions then detects cluster boundaries and low-density zones through scale-invariant spectral methods. |
| fastkmeanspp |
Fast C++-backed k-means++ initialisation for Python. Accelerates the seeding step with a BLAS routine for probabilistic distance-based scheme, with potential speedups of \(\times 10\) compared to scikit-learn. |
| mimisbm |
Fast vectorized Python port of the corresponding R project, implementing a mixture of multilayer stochastic block models. See the CRAN for more information about the original project. |