ICR

momi (short for MOran Models for Inference) is a Python package for computing the expected sample frequency spectrum (SFS) and using it to infer demographic history.

Within demestats package, all ICR related functions are implemented under demestats.icr.ICRCurve and meanfield approximations implemented under demestats.icr.ICRMeanFieldCurve.

The method for ICR is described in the following preprint:

Liang, J., & Terhorst, J. (2026, April 10). Computing coalescence rates for complex demographies and sampling configurations [Preprint]. bioRxiv. https://doi.org/10.64898/2026.04.09.717519

Content

  • ICR Tutorial introduces all of the core functions of ICR

  • Model Constraints shows how to modify model constraints

  • ICR Optimization demonstrates how to construct custom inference pipelines using scipy.minimize and the SFS

  • Special Examples shows examples of constructing complex models (e.g. exponential growth, admixture, bottleneck)