Result of the mcmc using the nest database

Description

Fit using the nest database

Usage

result_mcmc_4p_weight

Format

A list of class mcmcComposite with mcmc result for data(nest) with 4 parameters and Gompertz model of growth weigted to maximized entropy

Details

Result of the mcmc using the nest database with weight

Author(s)

Marc Girondot marc.girondot@u-psud.fr

References

Girondot, M., & Kaska, Y. (2014). A model to predict the thermal reaction norm for the embryo growth rate from field data. Journal of Thermal Biology, 45, 96-102. doi: 10.1016/j.jtherbio.2014.08.005

Examples

## Not run: 
library(embryogrowth)
data(nest)
formated <- FormatNests(nest)
w <- weightmaxentropy(formated, control_plot=list(xlim=c(20,36)))
x <- structure(c(118.768297442004, 475.750095909406, 306.243694918151, 
116.055824800264), .Names = c("DHA", "DHH", "T12H", "Rho25"))
# pfixed <- c(K=82.33) or rK=82.33/39.33
pfixed <- c(rK=2.093313)
# K or rK are not used for dydt.linear or dydt.exponential
resultNest_4p_weight <- searchR(parameters=x,  
	fixed.parameters=pfixed, temperatures=formated,  
	derivate=dydt.Gompertz, M0=1.7, test=c(Mean=39.33, SD=1.92),  
	method = "BFGS", weight=w)
data(resultNest_4p_weight)
pMCMC <- TRN_MHmcmc_p(resultNest_4p_weight, accept=TRUE)
# Take care, it can be very long, sometimes several days
result_mcmc_4p_weight <- GRTRN_MHmcmc(result=resultNest_4p_weight,  
	parametersMCMC=pMCMC, n.iter=10000, n.chains = 1, n.adapt = 0,  
	thin=1, trace=TRUE)
data(result_mcmc_4p_weight)
plot(result_mcmc_4p_weight, parameter="T12H", main="", xlim=c(290, 320), bty="n")
plotR(resultNest_4p_weight, SE=result_mcmc_4p_weight$SD, 
 ylim=c(0,0.3), las=1)
data(resultNest_4p)
data(result_mcmc_4p)
par(xpd=TRUE)
plotR(list(resultNest_4p_weight, resultNest_4p), 
 SE=list(result_mcmc_4p_weight$SD, result_mcmc_4p$SD), 
 ylim=c(0,0.4), las=1, col=list("red", "black"), 
 legend=list("Maximum entropy weighted", "Not weighted"))

## End(Not run)

Results