remstimate

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.

Last 30 days

This package has been downloaded 188 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 5,871 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Sep 11, 2024 with 70 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.