## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 6, fig.height = 4 ) ## ----------------------------------------------------------------------------- library(amorem) ## ----------------------------------------------------------------------------- set.seed(2024) actors <- as.character(1:10) true_beta <- 0.6 cc <- simulate_relational_events( n_events = 1200, senders = actors, receivers = actors, baseline_rate = 1, allow_loops = FALSE, n_controls = 1, endogenous_stats = "reciprocity_count", endogenous_effects = true_beta ) head(cc) ## ----message=FALSE, warning=FALSE--------------------------------------------- library(mgcv) cases <- cc[cc$event == 1L, ] controls <- cc[cc$event == 0L, ] cases <- cases[order(cases$stratum), ] controls <- controls[order(controls$stratum), ] fit_df <- data.frame( one = 1, delta_r = cases$reciprocity_count - controls$reciprocity_count ) fit <- gam(one ~ delta_r - 1, family = "binomial", data = fit_df) unname(coef(fit)[1]) ## ----------------------------------------------------------------------------- set.seed(2024) gc <- data.frame( time_start = seq(0, 10, by = 1), weekday = rep(c(0, 1), length.out = 11) ) ev <- simulate_relational_events( n_events = 200, senders = letters[1:5], receivers = letters[1:5], baseline_rate = 0.3, horizon = 11, global_covariates = gc, global_effects = c(weekday = 3) ) share_weekday <- mean(ev$weekday == 1) share_weekday ## ----------------------------------------------------------------------------- set.seed(7) actors <- letters[1:5] gc <- data.frame(time_start = c(0, 2, 4, 6), weekday = c(1, 0, 1, 0)) ev <- simulate_relational_events( n_events = 60, senders = actors, receivers = actors, baseline_rate = 1, horizon = 7, endogenous_stats = "reciprocity_count", endogenous_effects = c(reciprocity_count = 0.4), global_covariates = gc, global_effects = c(weekday = 1.5) ) head(ev)