Dynamic Relational Event Analysis and Modeling
Compute Burchard and Cornwell's (2018) Two-Mode Constraint
Compute Burchard and Cornwell's (2018) Two-Mode Effective Size
Compute Burchard and Cornwell's (2018) Two-Mode Redundancy
Compute Burt's (1992) Constraint for Ego Networks from a Sociomatrix
Compute Burt's (1992) Effective Size for Ego Networks from a Sociomatr...
Compute the Four-Cycles Network Statistic for Event Dyads in a Relatio...
Compute Fujimoto, Snijders, and Valente's (2018) Homophilous Four-Cycl...
Compute Butts' (2008) Incoming Shared Partners Network Statistic for E...
Compute Butts' (2008) Incoming Two Paths Network Statistic for Event D...
Compute Potential for Cultural Brokerage (PIB) Based on Leal (2025)
Compute the Number of Paths of Length K in a One-Mode Network
Compute Butts' (2008) Outgoing Shared Partners Network Statistic for E...
Compute Butts' (2008) Outgoing Two Paths Network Statistic for Event D...
Compute Butts' (2008) Persistence Network Statistic for Event Dyads in...
Compute Butts' (2008) Preferential Attachment Network Statistic for Ev...
Compute the Indegree Network Statistic for Event Receivers in a Relati...
Compute the Outdegree Network Statistic for Event Receivers in a Relat...
Compute Butts' (2008) Recency Network Statistic for Event Dyads in a R...
Compute the Reciprocity Network Statistic for Event Dyads in a Relatio...
A Helper Function to Assist Researchers in Finding Dyadic Weight Cutof...
Compute Butts' (2008) Repetition Network Statistic for Event Dyads in ...
Compute the Indegree Network Statistic for Event Senders in a Relation...
Compute the Outdegree Network Statistic for Event Senders in a Relatio...
Compute Degree Centrality Values for Two-Mode Networks
Compute Level-Specific Graph Density for Two-Mode Networks
Compute Fujimoto, Snijders, and Valente's (2018) Ego Homophily Distanc...
Compute the Triadic Closure Network Statistic for Event Dyads in a Rel...
dream: A Package for Dynamic Relational Event Analysis and Modeling
Fit a Relational Event Model (REM) to Event Sequence Data
Print Method for Summary of dream Model
Print Method for dream Model
Process and Create Risk Sets for a One-Mode Relational Event Sequence
Process and Create Risk Sets for a Two-Mode Relational Event Sequence
Helper Function to Compute Minimum Effective Time and Exponential Weig...
Simulate a Random One-Mode Relational Event Sequence
Summary Method for dream Objects
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.