inst/examples/labrid_mc_knit_.md

In cboettig/wrightscape: wrightscape

• Author: Carl Boettiger [e-mail]
• License: BSD

``` {r } require(wrightscape) require(snowfall) require(ggplot2) require(reshape)

``` {r }
data(labrids)
traits <- c("bodymass", "close", "open", "kt", "gape.y",  "prot.y", "AM.y", "SH.y", "LP.y")

``` {r } regimes <- two_shifts

Just a few processors, for debugging locally.

``` {r }
sfInit(par=T, 4)    
sfLibrary(wrightscape)
sfExportAll()

The main parallel loop fitting each model

``` {r } fits <- sfLapply(traits, function(trait){ multi <- function(modelspec){ out <- multiTypeOU(data = dat[[trait]], tree = tree, regimes = regimes, model_spec = modelspec, control = list(maxit=8000)) n <- length(levels(out$regimes)) Xo <- rep(out$Xo,n) loglik <- rep(out$loglik, n) pars <- cbind(out$alpha, out$sigma, out$theta, Xo, loglik) rownames(pars) <- levels(out$regimes) colnames(pars) <- c("alpha", "sigma", "theta", "Xo", "loglik") if(out$convergence != 0) # only return values if successful pars[,] <- NA pars } 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")) list(bm=bm,brownie=bm2, ou=ou, ouch=t2, alphas=a2) })

Reformat and label data for plotting

``` {r }
names(fits) <- traits  # each fit is a different trait (so use it for a label)
data <- melt(fits)
names(data) <- c("regimes", "param", "value", "model", "trait")

model likelihood

``` {r fig.width=8} ggplot(subset(data, param=="loglik")) + geom_boxplot(aes(model, value)) + facet_wrap(~ trait, scales="free_y")

Parameter distributions of alpha parameter in model `alpha` (alphas vary) and `ou` (global).  

``` {r fig.width=8 }
ggplot(subset(data, param %in% c("alpha") 
       & model %in% c("alphas", "ou")),
       aes(model, value, fill=regimes)) +
  geom_bar(position="dodge") +  
  facet_wrap(~trait, scales="free_y")

Parameter distribution of the sigma parameter in the brownie and bm models

``` {r fig.width=8 } ggplot(subset(data, param %in% c("sigma") & model %in% c("bm", "brownie")), aes(model, value, fill=regimes)) + geom_bar(position="dodge") + facet_wrap(~trait, scales="free_y")

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

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