Dynamic Relational Event Analysis and Modeling


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Documentation for package ‘dream’ version 2.1.1

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as.data.frame.dream_sequence Coerce a 'dream_sequence' Object into a 'data.frame' Object
coef.dream_rem Extract the ML parameter estimates from Relational Event Model Fits
create_res Process One- and Two-Mode Relational Event Sequences and Create Post-Processing Relational Event Sequences
dreamstats_actor Add Actor-Level Statistics for Event Dyads in a Relational Event Sequence
dreamstats_actorfe Add Actor-Level Fixed Effects for Event Dyads in a Relational Event Sequence
dreamstats_degree Compute Degree Network Statistics for Event Senders and Receivers in a Post-Processing Relational Event Sequence
dreamstats_dyadcut A Helper Function to Assist Researchers in Finding Dyadic Weight Cutoff Values
dreamstats_dyadfe Add Dyadic-Level Fixed Effects for Event Dyads in a Relational Event Sequence
dreamstats_dyadic Add Dyadic-Level Statistics for Event Dyads in a Relational Event Sequence
dreamstats_event Add Event-Level Statistics for a Relational Event Sequence
dreamstats_fourcycles Compute the Four-Cycles Network Statistic for Event Dyads in a Relational Event Sequence
dreamstats_persistence Compute Butts' (2008) Persistence Network Statistic for Event Dyads in a Relational Event Sequence
dreamstats_prefattachment Compute Butts' (2008) Preferential Attachment Network Statistic for Event Dyads in a Relational Event Sequence
dreamstats_recency Compute Butts' (2008) Recency Network Statistic for Event Dyads in a Relational Event Sequence
dreamstats_reciprocity Compute the Reciprocity Network Statistic for Event Dyads in a Relational Event Sequence
dreamstats_repetition Compute Butts' (2008) Repetition Network Statistic for Event Dyads in a Relational Event Sequence
dreamstats_triads Compute Butts' (2008) Triadic Formation Statistics for Relational Event Sequences
dream_information dream: A Package for Dynamic Relational Event Analysis and Modeling
dream_sequence Helper Function to Create 'dream_sequence' Objects
estimate_rem Fit a Maximum Likelihood Relational Event Model (REM) to A Processed Relational Event Sequence
logLik.dream_rem Extract the model log-likelihood from Relational Event Model Fits
netstats_om_constraint Compute Burt's (1992) Constraint for Ego Networks from a Sociomatrix
netstats_om_effective Compute Burt's (1992) Effective Size for Ego Networks from a Sociomatrix
netstats_om_nwalks Compute the Number of Walks of Length K in a One-Mode Network
netstats_om_pib Compute Potential for Intercultural Brokerage (PIB) Based on Leal (2025)
netstats_tm_constraint Compute Burchard and Cornwell's (2018) Two-Mode Constraint
netstats_tm_degreecent Compute Degree Centrality Values for Two-Mode Networks
netstats_tm_density Compute Level-Specific Graph Density for Two-Mode Networks
netstats_tm_effective Compute Burchard and Cornwell's (2018) Two-Mode Effective Size
netstats_tm_egodistance Compute Fujimoto, Snijders, and Valente's (2018) Ego Homophily Distance for Two-Mode Networks
netstats_tm_homfourcycles Compute Fujimoto, Snijders, and Valente's (2018) Homophilous Four-Cycles for Two-Mode Networks
netstats_tm_redundancy Compute Burchard and Cornwell's (2018) Two-Mode Redundancy
predict.dream_rem Predict method for Relational Event Model Fits
print.dream_rem Print Method for dreamrem Model
print.dream_sequence Print Method for 'dream' object
print.summary.dream_rem Print Method for dreamrem Model
print.summary.dream_sequence Print Method for dream Model
simulate_rem_seq Simulate a Random One-Mode Relational Event Sequence
southern.women Davis Southern Women's Dataset
summary.dream_rem Summary Method for dreamrem Objects
summary.dream_sequence Summary Method for dream_sequence Objects
vcov.dream_rem Extract variance-covariance matrix from Relational Event Model Fits
WikiEvent2018.first100k Wikipedia Edit Event Sequence 2018