<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Optimization Frameworks for Tie-Oriented and Actor-Oriented
Relational Event Models</dc:title>
  <dc:title>R package remstimate version 3.1.0</dc:title>
  <dc:description>Tools for fitting, diagnosing, and analyzing tie-oriented and
    actor-oriented relational event models, under both frequentist and Bayesian
    approaches. The package supports tie-oriented modeling (Butts, 2008,
    &lt;doi:10.1111/j.1467-9531.2008.00203.x&gt;) and an actor-oriented modeling
    framework (Stadtfeld et al., 2017, &lt;doi:10.15195/v4.a14&gt;),
    with additional model diagnostics and goodness-of-fit tools. 
    Interfaces to estimation backends provide a range of extensions: random-effects (frailty)
    relational event models capturing sender, receiver, and dyadic heterogeneity
    (Juozaitiene &amp; Wit 2024, &lt;doi:10.1007/s11336-024-09952-x&gt;;
    Mulder &amp; Hoff, 2024, &lt;doi:10.1214/24-AOAS1885&gt;), finite mixture
    and dyadic latent class models for unobserved dyadic heterogeneity
    (Lakdawala et al., 2026, &lt;doi:10.1016/j.socnet.2026.06.006&gt;), penalized estimation via the lasso,
    ridge, and elastic net (Tibshirani, R., 1996,
    &lt;doi:10.1111/j.2517-6161.1996.tb02080.x&gt;; Karimova et al., 2023, &lt;doi:10.1016/j.socnet.2023.02.006&gt;),
    and approximate Bayesian regularization (Karimova et al., 2025, &lt;doi:10.1016/j.jmp.2025.102925&gt;). Modeling
    of events with a duration is also supported (Lakdawala et al., 2026, &lt;doi:10.48550/arXiv.2602.21000&gt;) and
    moving window relational event models (Mulder &amp; Leenders, 2019,
    &lt;doi:10.1016/j.chaos.2018.11.027&gt;; Meijerink et al., 2023, &lt;doi:10.1371/journal.pone.0272309&gt;).</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.0.0), remify (&gt;= 4.1.0), remstats (&gt;= 4.1.0)</dc:relation>
  <dc:relation>Imports: Rcpp, trust, mvnfast</dc:relation>
  <dc:relation>LinkingTo: Rcpp, RcppArmadillo, remify (&gt;= 4.1.0)</dc:relation>
  <dc:relation>Suggests: knitr, rmarkdown, tinytest, survival, coxme, glmnet, lme4,
glmmTMB, flexmix, shrinkem (&gt;= 0.4.0), MASS, nnet, remdata (&gt;=
0.2.1)</dc:relation>
  <dc:creator>Giuseppe Arena &lt;g.arena@uva.nl&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Giuseppe Arena [aut, cre] (ORCID:
    &lt;https://orcid.org/0000-0001-5204-3326&gt;),
  Joris Mulder [aut],
  Rumana Lakdawala [aut],
  Fabio Generoso Vieira [aut],
  Marlyne Meijerink-Bosman [ctb],
  Diana Karimova [ctb],
  Mahdi Shafiee Kamalabad [ctb],
  Roger Leenders [ctb]</dc:contributor>
  <dc:rights>MIT + file LICENSE (https://CRAN.R-project.org/package=remstimate/LICENSE)</dc:rights>
  <dc:date>2026-07-17</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=remstimate</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.remstimate</dc:identifier>
</oai_dc:dc>
