Type: Package
Package: remstimate
Title: Optimization Frameworks for Tie-Oriented and Actor-Oriented
        Relational Event Models
Version: 3.1.0
Date: 2026-07-16
Authors@R: 
    c(person(given = "Giuseppe",
             family = "Arena",
             role = c("aut", "cre"),
             email = "g.arena@uva.nl",
             comment = c(ORCID = "0000-0001-5204-3326")),
      person(given = "Joris",
             family = "Mulder",
             role = "aut",
             email = "j.mulder3@tilburguniversity.edu"),
      person(given = "Rumana",
             family = "Lakdawala",
             role = "aut"),
      person(given = "Fabio",
             family = "Generoso Vieira",
             role = "aut"),
      person(given = "Marlyne",
             family = "Meijerink-Bosman",
             role = "ctb"),
      person(given = "Diana",
             family = "Karimova",
             role = "ctb"),
      person(given = "Mahdi",
             family = "Shafiee Kamalabad",
             role = "ctb"),
      person(given = "Roger",
             family = "Leenders",
             role = "ctb",
             email = "r.t.a.j.leenders@tilburguniversity.edu"))
Maintainer: Giuseppe Arena <g.arena@uva.nl>
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,
        <doi:10.1111/j.1467-9531.2008.00203.x>) and an actor-oriented
        modeling framework (Stadtfeld et al., 2017,
        <doi:10.15195/v4.a14>), 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 & Wit 2024,
        <doi:10.1007/s11336-024-09952-x>; Mulder & Hoff, 2024,
        <doi:10.1214/24-AOAS1885>), finite mixture and dyadic latent
        class models for unobserved dyadic heterogeneity (Lakdawala et
        al., 2026, <doi:10.1016/j.socnet.2026.06.006>), penalized
        estimation via the lasso, ridge, and elastic net (Tibshirani,
        R., 1996, <doi:10.1111/j.2517-6161.1996.tb02080.x>; Karimova et
        al., 2023, <doi:10.1016/j.socnet.2023.02.006>), and approximate
        Bayesian regularization (Karimova et al., 2025,
        <doi:10.1016/j.jmp.2025.102925>). Modeling of events with a
        duration is also supported (Lakdawala et al., 2026,
        <doi:10.48550/arXiv.2602.21000>) and moving window relational
        event models (Mulder & Leenders, 2019,
        <doi:10.1016/j.chaos.2018.11.027>; Meijerink et al., 2023,
        <doi:10.1371/journal.pone.0272309>).
License: MIT + file LICENSE
URL: https://tilburgnetworkgroup.github.io/remstimate/
BugReports: https://github.com/TilburgNetworkGroup/remstimate/issues
Depends: R (>= 4.0.0), remify (>= 4.1.0), remstats (>= 4.1.0)
Imports: Rcpp, trust, mvnfast
Suggests: knitr, rmarkdown, tinytest, survival, coxme, glmnet, lme4,
        glmmTMB, flexmix, shrinkem (>= 0.4.0), MASS, nnet, remdata (>=
        0.2.1)
LinkingTo: Rcpp, RcppArmadillo, remify (>= 4.1.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
LazyDataCompression: gzip
Config/pak/sysreqs: libglpk-dev libxml2-dev
Repository: https://tilburgnetworkgroup.r-universe.dev
Date/Publication: 2026-07-18 18:07:23 UTC
RemoteUrl: https://github.com/tilburgnetworkgroup/remstimate
RemoteRef: HEAD
RemoteSha: b95aae02ff11fcf3d7ff934806592d43d111fc2f
NeedsCompilation: yes
Packaged: 2026-07-18 18:42:17 UTC; root
Author: Giuseppe Arena [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-5204-3326>),
  Joris Mulder [aut],
  Rumana Lakdawala [aut],
  Fabio Generoso Vieira [aut],
  Marlyne Meijerink-Bosman [ctb],
  Diana Karimova [ctb],
  Mahdi Shafiee Kamalabad [ctb],
  Roger Leenders [ctb]