ERPM-package: ERPM: Exponential Random Partition Models

In ERPM: Exponential Random Partition Models

ERPM: Exponential Random Partition Models

Description

Simulates and estimates the Exponential Random Partition Model presented in the paper Hoffman, Block, and Snijders (2023) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/00811750221145166")}. It can also be used to estimate longitudinal partitions, following the model proposed in Hoffman and Chabot (2023) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.socnet.2023.04.002")}. The model is an exponential family distribution on the space of partitions (sets of non-overlapping groups) and is called in reference to the Exponential Random Graph Models (ERGM) for networks.

Author(s)

Maintainer: Marion Hoffman [e-mail] (ORCID) [copyright holder]

Authors:

• Alexandra Amani

• Nico Keiser

See Also

Useful links:

• https://github.com/stocnet/ERPM

• Report bugs at https://github.com/stocnet/ERPM/issues

ERPM documentation built on May 29, 2024, 10:05 a.m.