Nothing
clus.vb.fit<-function(len=NULL,age=NULL,cluster=NULL,nboot=1000,sumtype=1,
control=list(maxiter=10000,
minFactor=1/1024,tol=1e-5)){
if(length(age)!=length(len)) stop ("Vectors of different lengths")
if(length(cluster)!=length(len)) stop ("Vectors of different lengths")
if(length(cluster)!=length(age)) stop ("Vectors of different lengths")
if(mode(cluster)!="numeric") stop ("cluster must be a numeric variable")
ins<-as.data.frame(cbind(len,age,cluster))
ins<-ins[!is.na(ins$len) & !is.na(ins$age) & !is.na(ins$cluster),]
ins<-ins[order(ins$cluster),]
nclus<-length(unique(ins$cluster))
listclus<-unique(ins$cluster)
parms<-data.frame(NULL)
samp <- sample(listclus, nclus, replace = TRUE)
datDT <- as.data.table(ins)
setkey(datDT, "cluster")
for(i in 1:nboot){
samp <- sample(listclus, nclus, replace = TRUE)
x <- datDT[list(samp), allow.cartesian = TRUE]
mbt<-NULL;mbxt<-NULL;g2<-NULL
g2<-aggregate(x$len,list(round(x$age,0)),mean)
mbt<-g2;mbt[,1]<-mbt[,1]-1
mbxt<-merge(g2,mbt,by.x=c("Group.1"),by.y=c("Group.1"))
outboth<-lm(mbxt[,3]~mbxt[,2])
Kboth<-abs(log(coef(outboth)[2]));Lboth<--coef(outboth)[1]/(coef(outboth)[2]-1)
dxb<-as.data.frame(cbind(Lboth-g2$x,g2[,1]));dxb<-dxb[dxb[,1]>0,]
t0b<-(coef(lm(log(dxb[,1])~dxb[,2]))[1]-log(Lboth))/Kboth
Linf1<-Lboth;K1<-Kboth;t01<-t0b
#fit model
vbmodel<-try(nls(len~Linf*(1-exp(-K*(age-t0))),data=x,
start=c(Linf=Linf1[[1]],K=K1[[1]],t0=t01[[1]]),
control=control),silent=TRUE)
vbtype<-class(vbmodel)
if(vbtype!="try-error"){
parms[i,1]<-coef(vbmodel)[1]
parms[i,2]<-coef(vbmodel)[2]
parms[i,3]<-coef(vbmodel)[3]
cor<-summary(vbmodel,correlation=TRUE)$correlation
parms[i,4]<-cor[1,2]
parms[i,5]<-cor[1,3]
parms[i,6]<-cor[2,3]
}
if(vbtype=="try-error"){
parms[i,1]<-NA
parms[i,2]<-NA
parms[i,3]<-NA
parms[i,4]<-NA
parms[i,5]<-NA
parms[i,6]<-NA
}
} # boot loop
#calculate statistics
if(sumtype==1) means<-c(mean(parms[,1],na.rm=TRUE),mean(parms[,2],na.rm=TRUE),mean(parms[,3],na.rm=TRUE),
mean(parms[,4],na.rm=TRUE),mean(parms[,5],na.rm=TRUE),mean(parms[,6],na.rm=TRUE))
if(sumtype==2) means<-c(median(parms[,1],na.rm=TRUE),median(parms[,2],na.rm=TRUE),median(parms[,3],na.rm=TRUE),
median(parms[,4],na.rm=TRUE),median(parms[,5],na.rm=TRUE),median(parms[,6],na.rm=TRUE))
sds<-apply(parms,2,sd,na.rm=TRUE)
qLinf<-quantile(parms[,1],c(0.025,0.975),na.rm=TRUE)
qK<-quantile(parms[,2],c(0.025,0.975),na.rm=TRUE)
qt0<-quantile(parms[,3],c(0.025,0.975),na.rm=TRUE)
# output
nfails<-length(parms[is.na(parms[,1]),1])
title<-c(paste("Parameter coefficients based on ",nboot-nfails," successful fits"))
ans<-NULL
ans$summary<-paste(title)
ans$results<-matrix(NA,3L,6L)
ans$results<-rbind(cbind(round(means[1],2),round(sds[1],3),round(qLinf[1],3),round(qLinf[2],3)),
cbind(round(means[2],3),round(sds[2],4),round(qK[1],4),round(qK[2],4)),
cbind(round(means[3],3),round(sds[3],4),round(qt0[1],4),round(qt0[2],4)))
dimnames(ans$results)<-list(cbind("Linf","K","t0"),c("Estimate","SE","95% LCI","95% UCI"))
ans$correlations<-matrix(NA,3L,3L)
ans$correlations<-rbind(cbind(1,round(means[4],3),round(means[5],3)),
cbind(round(means[4],3),1,round(means[6],3)),
cbind(round(means[5],3),round(means[6],3),1))
dimnames(ans$correlations)<-list(cbind("Linf","K","t0"),c("Linf","K","t0"))
return(ans)
}# function
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.