Nothing
#' Result of the mcmc using the nest database
#' @title Result of the mcmc using the nest database
#' @author Marc Girondot \email{marc.girondot@@universite-paris-saclay.fr}
#' @docType data
#' @name resultNest_mcmc_4p_SSM
#' @encoding UTF-8
#' @description Fit using the nest database
#' @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
#' @keywords datasets
#' @usage resultNest_mcmc_4p_SSM
#' @examples
#' \dontrun{
#' library(embryogrowth)
#' data(nest)
#' formated <- FormatNests(nest)
#' # The initial parameters value can be:
#' # "T12H", "DHA", "DHH", "Rho25"
#' # Or
#' # "T12L", "DT", "DHA", "DHH", "DHL", "Rho25"
#' x <- structure(c(118.431040984352, 498.205702157603, 306.056280989839,
#' 118.189669472381), .Names = c("DHA", "DHH", "T12H", "Rho25"))
#' # pfixed <- c(K=82.33) or rK=82.33/39.33
#' pfixed <- c(rK=2.093313)
#' resultNest_4p_SSM <- searchR(parameters=x, fixed.parameters=pfixed,
#' temperatures=formated, integral=integral.Gompertz, M0=1.7,
#' test=c(Mean=39.33, SD=1.92))
#' data(resultNest_4p_SSM)
#' pMCMC <- TRN_MHmcmc_p(resultNest_4p_SSM, accept=TRUE)
#' # Take care, it can be very long, sometimes several days
#' resultNest_mcmc_4p_SSM <- GRTRN_MHmcmc(result=resultNest_4p_SSM,
#' adaptive = TRUE,
#' parametersMCMC=pMCMC, n.iter=10000, n.chains = 1, n.adapt = 0,
#' thin=1, trace=TRUE)
#' data(resultNest_mcmc_4p_SSM)
#' 1-rejectionRate(as.mcmc(resultNest_mcmc_4p_SSM))
#' as.parameters(resultNest_mcmc_4p_SSM)
#' layout(mat=matrix(1:4, nrow = 2))
#' plot(resultNest_mcmc_4p_SSM, parameters = "all", scale.prior = TRUE, las = 1)
#' layout(mat=1)
#' plotR(resultNest_4p_SSM, resultmcmc=resultNest_mcmc_4p_SSM, ylim=c(0,4),
#' main="Schoolfield, Sharpe & Magnuson 4-parameters", show.density=TRUE)
#' }
#' @format A list of class mcmcComposite with mcmc result for data(nest) with 4 parameters and Gompertz model of growth
NULL
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.