embryogrowth (version 8.0)

result_mcmc_newp: Result of the mcmc using the nest database with anchored parameters

Description

Fit using the nest database with anchored parameters

Usage

result_mcmc_newp

Format

A list of class mcmcComposite with mcmc result for data(nest) with anchored parameters

Details

Result of the mcmc using the nest database with anchored parameters

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)
newp <- GenerateAnchor(nests=formated, number.anchors=7)
pfixed <- c(rK=2.093313)
resultNest_newp <- searchR(parameters=newp, fixed.parameters=pfixed, 
  temperatures=formated, derivate=dydt.Gompertz, M0=1.7, 
  test=c(Mean=39.33, SD=1.92))
data(resultNest_newp)
pMCMC <- TRN_MHmcmc_p(resultNest_newp, accept=TRUE)
# Take care, it can be very long, sometimes several days
result_mcmc_newp <- GRTRN_MHmcmc(result=resultNest_newp,  
  parametersMCMC=pMCMC, n.iter=10000, n.chains = 1, n.adapt = 0,  
	thin=1, trace=TRUE)
data(result_mcmc_newp)
data(resultNest_4p_SSM4p)
newp <- GenerateAnchor(nests=resultNest_4p_SSM4p, number.anchors=7)
# Here the confidence interval is built based on anchored parameters
plotR(resultNest_4p_SSM4p, parameters=newp, SE=result_mcmc_newp$SD, 
 ylim=c(0,4), ylimH=c(0,0.4), show.hist=TRUE, curves="ML quantiles")
# Here the confidence interval is built based on parametric SSM equation
data(resultNest_4p_SSM4p)
plotR(resultNest_4p_SSM4p, SE=resultNest_mcmc_4p_SSM4p$SD,
 ylim=c(0,4), ylimH=c(0,0.4), show.hist=TRUE, curves="ML quantiles")
plot(result_mcmc_newp, las=1, xlim=c(0,30), parameters="294", 
breaks=c(0, 1.00095, 2.0009, 3.00085, 4.0008, 5.00075, 6.0007, 7.00065, 8.0006, 9.00055, 
10.0005, 11.00045, 12.0004, 13.00035, 14.0003, 15.00025, 16.0002, 17.00015, 18.0001, 
19.00005, 20))
plot(result_mcmc_newp, las=1, xlim=c(0,30), parameters="296.333333333333")
plot(result_mcmc_newp, las=1, xlim=c(0,30), parameters=3)
# }