remstimate
Optimization Frameworks for Tie-Oriented and Actor-Oriented Relational Event Models
A comprehensive set of tools designed for optimizing likelihood within a tie-oriented (Butts, C., 2008, doi:10.1111/j.1467-9531.2008.00203.x) or an actor-oriented modelling framework (Stadtfeld, C., & Block, P., 2017, doi:10.15195/v4.a14) in relational event networks. The package accommodates both frequentist and Bayesian approaches. The frequentist approaches that the package incorporates are the Maximum Likelihood Optimization (MLE) and the Gradient-based Optimization (GDADAMAX). The Bayesian methodologies included in the package are the Bayesian Sampling Importance Resampling (BSIR) and the Hamiltonian Monte Carlo (HMC). The flexibility of choosing between frequentist and Bayesian optimization approaches allows researchers to select the estimation approach which aligns the most with their analytical preferences.
- Version2.3.11
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?Yes
- Last release05/16/2024
Documentation
Team
Giuseppe Arena
Joris Mulder
Show author detailsRolesContributorRoger Leenders
Show author detailsRolesContributorRumana Lakdawala
Show author detailsRolesAuthorMarlyne Meijerink-Bosman
Show author detailsRolesContributorDiana Karimova
Show author detailsRolesContributorFabio Generoso Vieira
Show author detailsRolesAuthorMahdi Shafiee Kamalabad
Show author detailsRolesContributor
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- Imports5 packages
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