d <- read.csv("data/Volume.csv") d$time <- 30 d$host <- 1 # number of tadpoles in each container d$Number <- d$Cerc_Number # fit models ---------------------------- n_models <- length(models()) model_fits <- vector(mode = "list", length = n_models) names(model_fits) <- models() for (i in 1:n_models) { model_fits[[i]] <- fit_model(d, model = models()[i]) } # make aic table ------------------------------- header <- "Table 2a: varying parasite number (constant density)" aic_tab <- aic_table(model_fits, d) save_aic_table(aic_tab, header, filename = "tables/volume_table.md") (best_models <- rownames(subset(aic_tab, dAICc < 2))) # make parameter table ---------------------------------------------------- make_par_table(model_fits, name = "tables/parameter_estimates/volume.csv")