Package: dream 2.1.3

Kevin A. Carson

dream: Dynamic Relational Event Analysis and Modeling

A set of tools for relational and event analysis, including two- and one-mode network brokerage and structural measures, and helper functions optimized for relational event analysis with large datasets, including creating relational risk sets, computing network statistics, estimating relational event models, and simulating relational event sequences. For more information on relational event models, see Butts (2008) <doi:10.1111/j.1467-9531.2008.00203.x>, Lerner and Lomi (2020) <doi:10.1017/nws.2019.57>, Bianchi et al. (2024) <doi:10.1146/annurev-statistics-040722-060248>, and Butts et al. (2023) <doi:10.1017/nws.2023.9>. In terms of the structural measures in this package, see Leal (2025) <doi:10.1177/00491241251322517>, Burchard and Cornwell (2018) <doi:10.1016/j.socnet.2018.04.001>, and Fujimoto et al. (2018) <doi:10.1017/nws.2018.11>. This package was developed with support from the National Science Foundation’s (NSF) Human Networks and Data Science Program (HNDS) under award number 2241536 (PI: Diego F. Leal). Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

Authors:Kevin A. Carson [aut, cre], Diego F. Leal [aut]

dream_2.1.3.tar.gz
dream_2.1.3.tar.gz(r-4.7-arm64)dream_2.1.3.tar.gz(r-4.7-x86_64)dream_2.1.3.tar.gz(r-4.6-arm64)dream_2.1.3.tar.gz(r-4.6-x86_64)
dream_2.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
dream/json (API)
NEWS

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

Bug tracker:https://github.com/kevincarson/dream/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

2.68 score 13 scripts 1.0k downloads 30 exports 11 dependencies

Last updated from:de6e0c7da9. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK195
linux-devel-x86_64OK191
source / vignettesOK218
linux-release-arm64OK195
linux-release-x86_64OK187
wasm-releaseOK167

Exports:create_resdream_sequencedreamstats_actordreamstats_actorfedreamstats_degreedreamstats_dyadcutdreamstats_dyadfedreamstats_dyadicdreamstats_eventdreamstats_fourcyclesdreamstats_persistencedreamstats_prefattachmentdreamstats_recencydreamstats_reciprocitydreamstats_repetitiondreamstats_triadsestimate_remgof_remnetstats_om_constraintnetstats_om_effectivenetstats_om_nwalksnetstats_om_pibnetstats_tm_constraintnetstats_tm_degreecentnetstats_tm_densitynetstats_tm_effectivenetstats_tm_egodistancenetstats_tm_homfourcyclesnetstats_tm_redundancysimulate_rem_seq

Dependencies:clicodetoolscollapsedata.tabledoParallelforeachiteratorslifecycleRcppRcppArmadillorlang

Readme and manuals

Help Manual

Help pageTopics
Coerce a 'dream_sequence' Object into a 'data.frame' Objectas.data.frame.dream_sequence
Extract the ML parameter estimates from Relational Event Model Fitscoef.dream_rem
Process One- and Two-Mode Relational Event Sequences and Create Post-Processing Relational Event Sequencescreate_res
dream: A Package for Dynamic Relational Event Analysis and Modelingdream_information
Helper Function to Create 'dream_sequence' Objectsdream_sequence
Add Actor-Level Statistics for Event Dyads in a Relational Event Sequencedreamstats_actor
Add Actor-Level Fixed Effects for Event Dyads in a Relational Event Sequencedreamstats_actorfe
Compute Degree Network Statistics for Event Senders and Receivers in a Post-Processing Relational Event Sequencedreamstats_degree
A Helper Function to Assist Researchers in Finding Dyadic Weight Cutoff Valuesdreamstats_dyadcut
Add Dyadic-Level Fixed Effects for Event Dyads in a Relational Event Sequencedreamstats_dyadfe
Add Dyadic-Level Statistics for Event Dyads in a Relational Event Sequencedreamstats_dyadic
Add Event-Level Statistics for a Relational Event Sequencedreamstats_event
Compute the Four-Cycles Network Statistic for Event Dyads in a Relational Event Sequencedreamstats_fourcycles
Compute Butts' (2008) Persistence Network Statistic for Event Dyads in a Relational Event Sequencedreamstats_persistence
Compute Butts' (2008) Preferential Attachment Network Statistic for Event Dyads in a Relational Event Sequencedreamstats_prefattachment
Compute Butts' (2008) Recency Network Statistic for Event Dyads in a Relational Event Sequencedreamstats_recency
Compute the Reciprocity Network Statistic for Event Dyads in a Relational Event Sequencedreamstats_reciprocity
Compute Butts' (2008) Repetition Network Statistic for Event Dyads in a Relational Event Sequencedreamstats_repetition
Compute Butts' (2008) Triadic Formation Statistics for Relational Event Sequencesdreamstats_triads
Fit a Maximum Likelihood Relational Event Model (REM) to A Processed Relational Event Sequenceestimate_rem
Estimate the proportion of dyads predicted by 'dream_rem' relational event model fitsgof_rem
Extract the model log-likelihood from Relational Event Model FitslogLik.dream_rem
Compute Burt's (1992) Constraint for Ego Networks from a Sociomatrixnetstats_om_constraint
Compute Burt's (1992) Effective Size for Ego Networks from a Sociomatrixnetstats_om_effective
Compute the Number of Walks of Length K in a One-Mode Networknetstats_om_nwalks
Compute Potential for Intercultural Brokerage (PIB) Based on Leal (2025)netstats_om_pib
Compute Burchard and Cornwell's (2018) Two-Mode Constraintnetstats_tm_constraint
Compute Degree Centrality Values for Two-Mode Networksnetstats_tm_degreecent
Compute Level-Specific Graph Density for Two-Mode Networksnetstats_tm_density
Compute Burchard and Cornwell's (2018) Two-Mode Effective Sizenetstats_tm_effective
Compute Fujimoto, Snijders, and Valente's (2018) Ego Homophily Distance for Two-Mode Networksnetstats_tm_egodistance
Compute Fujimoto, Snijders, and Valente's (2018) Homophilous Four-Cycles for Two-Mode Networksnetstats_tm_homfourcycles
Compute Burchard and Cornwell's (2018) Two-Mode Redundancynetstats_tm_redundancy
Plot method for 'dream_rem' Relational Event Model Fitsplot.dream_rem
Predict method for Relational Event Model Fitspredict.dream_rem
Print Method for dreamrem Modelprint.dream_rem
Print Method for 'dream' objectprint.dream_sequence
Print Method for dreamrem Modelprint.summary.dream_rem
Print Method for dream Modelprint.summary.dream_sequence
Model residuals for 'dream_rem' relational event model fitsresiduals.dream_rem
Simulate a Random One-Mode Relational Event Sequencesimulate_rem_seq
Davis Southern Women's Datasetsouthern.women
Summary Method for dreamrem Objectssummary.dream_rem
Summary Method for dream_sequence Objectssummary.dream_sequence
Extract variance-covariance matrix from Relational Event Model Fitsvcov.dream_rem
Wikipedia Edit Event Sequence 2018WikiEvent2018.first100k