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remstimate  

Optimization Frameworks for Tie-Oriented and Actor-Oriented Relational Event Models
View on CRAN: Click here


Download and install remstimate package within the R console
Install from CRAN:
install.packages("remstimate")

Install from Github:
library("remotes")
install_github("cran/remstimate")

Install by package version:
library("remotes")
install_version("remstimate", "2.3.14")



Attach the package and use:
library("remstimate")
Maintained by
Giuseppe Arena
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-12-20
Latest Update: 2025-01-29
Description:
A comprehensive set of tools designed for optimizing likelihood within a tie-oriented (Butts, C., 2008, ) or an actor-oriented modelling framework (Stadtfeld, C., & Block, P., 2017, ) 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.
How to cite:
Giuseppe Arena (2023). remstimate: Optimization Frameworks for Tie-Oriented and Actor-Oriented Relational Event Models. R package version 2.3.14, https://cran.r-project.org/web/packages/remstimate. Accessed 04 Jun. 2026.
Previous versions and publish date:
2.3.8 (2023-12-20 16:50), 2.3.9 (2024-05-13 18:10), 2.3.11 (2024-05-16 17:00), 2.3.13 (2025-01-29 14:20), 2.3.14 (2025-09-26 10:30)
Other packages that cited remstimate R package
View remstimate citation profile
Other R packages that remstimate depends, imports, suggests or enhances
Complete documentation for remstimate
Functions, R codes and Examples using the remstimate R package
Some associated functions: aic . aicc . ao_data . bic . diagnostics . plot.remstimate . print.remstimate . remstimate-package . remstimate . summary.remstimate . tie_data . waic . 
Some associated R codes: RcppExports.R . data.R . remstimate-package.R . remstimate.R .  Full remstimate package functions and examples
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