## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(fig.width = 6, fig.height = 6, fig.align = "center") ## ----------------------------------------------------------------------------- library(aphylo) # Parameter estimates psi <- c(.05, .025) mu_d <- c(.2, .1) mu_s <- c(.1, .05) Pi <- .5 ## ----data-sim----------------------------------------------------------------- set.seed(223) x <- raphylo(n = 200, psi = psi, mu_d = mu_d, mu_s = mu_s, Pi = Pi) plot(x) ## ----eval=FALSE--------------------------------------------------------------- # # Edgelist describing parent->offspring relations # write.csv(x$tree, file = "tree.tree", row.names = FALSE) # # # Tip annotations # ann <- with(x, rbind(tip.annotation, node.annotation)) # write.csv(ann, file = "annotations.csv", row.names = FALSE) # # # Event types # events <- with(x, cbind(c(tip.type*NA, node.type))) # rownames(events) <- 1:nrow(events) # write.csv(events, file = "events.csv", row.names = FALSE) ## ----inference, cache=TRUE---------------------------------------------------- ans <- aphylo_mcmc(x ~ psi + mu_d + mu_s + Pi) ans ## ----plot-predict------------------------------------------------------------- plot(ans) ## ----plot-loglike------------------------------------------------------------- plot_logLik(ans) ## ----predict-score------------------------------------------------------------ ps <- prediction_score(ans) ps # Printing plot(ps) # and plotting