library(ConnMatTools) ps <- c(0.7,0.5) # Fraction of eggs "marked" at each source site ks <- c(4,5) # Number of marked settlers among sample from each source site n.sample <- 20 # Total sample size. Must be >= sum(ks) phis0 = runif(3,min=0.05) phis0 = phis0 / sum(phis0) phis0 = phis0[1:2] # Don't include relative connectivity of unknown sites nbatch=1e4 library(mcmc) ans = metrop(d.rel.conn.multinomial.unnorm, initial=phis0,nbatch=nbatch,scale=0.1, log=TRUE,ps=ps,ks=ks,n.sample=n.sample) # A more serious test would adjust blen and scale to improve results, and would repeat # multiple times to get results from multiple MCMC chains. # Plot marginal distribution of relative connectivity from first site h=hist(ans$batch[,1],xlab="Rel. Conn., Site 1", main="Relative Connectivity for Source Site 1") # For comparison, add on curve that would correspond to single site calculation phi = seq(0,1,length.out=40) d1 = d.rel.conn.beta.prior(phi,ps,ks,n.sample) lines(phi,d1*nbatch*diff(h$breaks),col="red",lwd=5) # Image plot of bivariate probability density t=table(cut(ans$batch[,1],phi),cut(ans$batch[,2],phi)) image(t,col=heat.colors(12)[12:1],xlab="Rel. Conn., Site 1",ylab="Rel. Conn., Site 2") # Add line indicate region above which one can never find results as that would # lead to a total connectivity great than 1 abline(1,-1,col="black",lty="dashed",lwd=3)
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