Package: amorem 1.0.0

Francisco Richter

amorem: Augmented Modelling of Relational Events

Utilities for simulating and prototyping relational event models, including helpers to generate dynamic event sequences and covariate processes for sender and receiver sets. The endogenous-effect and case-control estimation machinery follows Juozaitiene and Wit (2024) <doi:10.1093/jrsssa/qnae132>.

Authors:Francisco Richter [aut, cre], Martina Boschi [aut], Ernst C. Wit [aut], Melania Lembo [aut]

amorem_1.0.0.tar.gz
amorem_1.0.0.tar.gz(r-4.7-arm64)amorem_1.0.0.tar.gz(r-4.7-x86_64)amorem_1.0.0.tar.gz(r-4.6-arm64)amorem_1.0.0.tar.gz(r-4.6-x86_64)
amorem_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
amorem/json (API)

# Install 'amorem' in R:
install.packages('amorem', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/franciscorichter/amorem/issues

Pkgdown/docs site:https://franciscorichter.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.48 score 12 scripts 31 exports 5 dependencies

Last updated from:ff20547ebf. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK224
linux-devel-x86_64OK237
source / vignettesOK241
linux-release-arm64OK233
linux-release-x86_64OK239
wasm-releaseOK158

Exports:as_dyadic_logas_hyperedge_logattach_static_covariatescompare_modelscompare_models_globalcompare_models_smoothcpp_supported_statsendogenous_featuresgof_auxiliarygof_globalgof_multivariategof_univariatehyperedge_activityhyperedge_featureshyperedge_loghyperedge_sizeshyperedge_subrepis_hyperedge_logmartingale_residualsnn_controlnn_uncertaintyremsample_non_eventssimulate_actor_covariatessimulate_directed_hyperedge_eventssimulate_directed_hyperevents_tvnlsimulate_hyperedge_eventssimulate_relational_eventsstandardize_event_logtransform_recencywiden_case_control

Dependencies:latticeMatrixRcppsurvivalwithr

Endogenous mechanisms and time-varying global covariates
Endogenous reciprocity | Time-varying global covariates | Composing endogenous and global | Caveat
Rendered fromendogenous-and-global.Rmdusingknitr::rmarkdown

Last update: 2026-06-29
Started: 2026-06-29

Exogenous dyadic covariates
US state distance matrix | Defining a non-linear effect | Simulating events with exogenous covariates | Recovering the effect with a GAM | Plotting estimated vs true effect
Rendered fromexogenous-covariates.Rmdusingknitr::rmarkdown

Last update: 2026-06-29
Started: 2026-06-29

Model comparison on a real REM dataset
1. Load a bundled REM dataset | 2. Build candidate specifications | 3. Compare by AIC | Multiple controls per case | 4. Inspect coefficients of a chosen specification | 5. Cross-implementation guarantee | References
Rendered frommodel-comparison.Rmdusingknitr::rmarkdown

Last update: 2026-06-29
Started: 2026-06-29

Simulating relational events
Simulating actor covariates | Simulating event sequences
Rendered fromsimulation-demo.Rmdusingknitr::rmarkdown

Last update: 2026-06-29
Started: 2026-06-29

Species invasions as a relational event process
Why model invasions as relational events? | A synthetic invasion process | Recovering the drivers | Where to go from here
Rendered fromspecies-invasion.Rmdusingknitr::rmarkdown

Last update: 2026-06-29
Started: 2026-06-29

Readme and manuals

Help Manual

Help pageTopics
Attach static covariates to an event logattach_static_covariates
Classroom actor attributes (McFarland 2001)classroom_actors
Classroom interaction events (McFarland 2001)classroom_events
CollegeMsg: private messages on a university online communitycollege_msg
Compare candidate endogenous specifications by AICcompare_models
Compare REM specifications with global covariate effectscompare_models_global
Compare candidate specifications with smooth (TV / NL / TVNL) effectscompare_models_smooth
Endogenous statistics with a compiled fast pathcpp_supported_stats
US state distance matrixdist_matrix
Email-Eu-Core temporal (single-department subset)email_eu_core
Compute endogenous event-network statisticsendogenous_features
GOF test for an auxiliary (unmodelled) statisticgof_auxiliary
Omnibus GOF test via Cauchy combinationgof_global
Multivariate GOF test for smooth or random-effect covariatesgof_multivariate
Goodness-of-fit test for a single FLE covariategof_univariate
Activity counter for hyperedge subsetshyperedge_activity
Endogenous features for a hyperedge event loghyperedge_features
Build / detect / convert hyperedge event logsas_dyadic_log as_hyperedge_log hyperedge_log is_hyperedge_log
Cardinality columns for a hyperedge event loghyperedge_sizes
Subset repetition statistic for a hyperedge event loghyperedge_subrep
Martingale residuals from a case-control partial-likelihood fitmartingale_residuals
Control parameters for the neural-network backend of rem()nn_control
Bootstrap uncertainty for the neural rem() backendnn_uncertainty
Plot partial-dependence uncertainty bandsplot.nn_uncertainty
Manufacturing-company email events (Michalski et al. 2014)radoslaw_email
Fit a relational (hyper)event model on preprocessed case-control datarem
Sample non-events for inferencesample_non_events
Simulate exogenous actor covariatessimulate_actor_covariates
Simulate directed two-mode hyperedge eventssimulate_directed_hyperedge_events
Simulate directed hyper-events with time-varying and non-linear effectssimulate_directed_hyperevents_tvnl
Simulate undirected hyperedge events (multi-actor meetings)simulate_hyperedge_events
Simulate relational event sequencessimulate_relational_events
Actor attributes for the Social Evolution studysocial_evolution_actors
Phone calls in the Social Evolution study (Madan et al. 2011)social_evolution_calls
Friendship-survey events for the Social Evolution studysocial_evolution_friendship
Standardize a relational event logstandardize_event_log
Recency transform of inter-event time gapstransform_recency
Convert a long case-control event log to wide case-1-control formatwiden_case_control