inst/examples/focal_examples_knit_.md

``` {r } require(wrightscape) require(ggplot2) require(reshape) data(labrids)


``` {r }
traits <- c("open", "kt")
regimes <- two_shifts 

``` {r } nboot <- 50 cpu <- 16



``` {r } 
require(snowfall)
sfInit(parallel=TRUE, cpu=cpu)
sfLibrary(wrightscape)
sfExportAll()

Fit all models, then actually perform the model choice analysis for the chosen model pairs

``` {r } fits <- lapply(traits, function(trait){ multi <- function(modelspec){ multiTypeOU(data = dat[[trait]], tree = tree, regimes = regimes, model_spec = modelspec, control = list(maxit=8000)) } bm <- multi(list(alpha = "fixed", sigma = "global", theta = "global")) ou <- multi(list(alpha = "global", sigma = "global", theta = "global")) bm2 <- multi(list(alpha = "fixed", sigma = "indep", theta = "global")) a2 <- multi(list(alpha = "indep", sigma = "global", theta = "global")) t2 <- multi(list(alpha = "global", sigma = "global", theta = "indep"))

mc <- montecarlotest(bm2,a2, cpu=cpu, nboot=nboot) bm2_a2 <- list(null=mc$null_dist, test=mc$test_dist, lr=-2(mc$null$loglik-mc$test$loglik)) mc <- montecarlotest(bm,ou, cpu=cpu, nboot=nboot) bm_ou <- list(null=mc$null_dist, test=mc$test_dist, lr=-2(mc$null$loglik-mc$test$loglik)) mc <- montecarlotest(bm,bm2, cpu=cpu, nboot=nboot) bm_bm2 <- list(null=mc$null_dist, test=mc$test_dist, lr=-2(mc$null$loglik-mc$test$loglik)) mc <- montecarlotest(ou,bm2, cpu=cpu, nboot=nboot) ou_bm2 <- list(null=mc$null_dist, test=mc$test_dist, lr=-2(mc$null$loglik-mc$test$loglik)) mc <- montecarlotest(t2,a2, cpu=cpu, nboot=nboot) t2_a2 <- list(null=mc$null_dist, test=mc$test_dist, lr=-2(mc$null$loglik-mc$test$loglik)) mc <- montecarlotest(bm2,t2, cpu=cpu, nboot=nboot) bm2_t2 <- list(null=mc$null_dist, test=mc$test_dist, lr=-2(mc$null$loglik-mc$test$loglik)) list(brownie_vs_alphas=bm2_a2, brownie_vs_thetas=bm2_t2, thetas_vs_alphas=t2_a2, bm_vs_brownie=bm_bm2, bm_vs_ou=bm_ou, ou_vs_brownie=ou_bm2) })



``` {r }
save(list=ls(), file="focal_examples.rda")

Clean up the data

``` {r } names(fits) <- traits dat <- melt(fits) names(dat) <- c("value", "type", "comparison", "trait")



``` {r }
r <- cast(dat, comparison ~ trait, function(x) quantile(x, c(.10,.90)))
subdat <- subset(dat, abs(value) < max(abs(as.matrix(r))))

``` {r } ggplot(subdat) + geom_boxplot(aes(type, value)) + facet_grid(trait ~ comparison, scales="free_y")


``` {r }
save(list=ls(), file="~/public_html/data/focal_examples.rda")


cboettig/wrightscape documentation built on May 13, 2019, 2:12 p.m.