embryogrowth (version 6.2)

ChangeSSM: Generate set of parameters for Schoolfield-Sharpe-Magnuson model

Description

Generate a set of parameters for Schoolfield-Sharpe-Magnuson model

Usage

ChangeSSM(temperatures = (200:350)/10, parameters = stop("A set of parameters must be supplied"), initial.parameters = stop("A set of parameters for new model must be supplied"), ...)

Arguments

temperatures

A vector with incubation temperatures in degrees Celsius

parameters

A vector of parameters for model to be converted (4 or 6 parameters)

initial.parameters

A vector of parameters for initial model model to be fited (4 or 6 parameters)

...

A control list to be used with optim, see ?optim

Value

A vector with parameters

Details

ChangeSSM convert Schoolfield-Sharpe-Magnuson model from 4 to 6 parameters or reverse

Examples

## Not run: 
# data(resultNest_6p)
# x1 <- resultNest_6p$par
# data(resultNest_4p)
# x2 <- resultNest_4p$par
# temperaturesC <- (200:350)/10
# s <- ChangeSSM(temperatures=temperaturesC, parameters=x1, initial.parameters=x2)
# plotR(list(resultNest_6p, resultNest_4p, s), ylim=c(0,0.3), 
# col=list("black", "red", "green"), lty=list(1,1,1), 
# legend=list("R function to mimic", "Initial new R function", 
# "Fitted new R function"), show.box=FALSE)
# # Other example to fit anchored parameters
# data(resultNest_4p)
# x0 <- resultNest_4p$par
# t <- hist(resultNest_4p, plot=FALSE)
# x <- c(3.4, 3.6, 5.4, 5.6, 7.6, 7.5, 3.2)
# names(x) <- seq(from=range(t$temperatures)[1], to=range(t$temperatures)[2], 
#      length.out=7)
# newx <- ChangeSSM(temperatures = (200:350)/10, parameters = x0, 
#        initial.parameters = x, 
#        control=list(maxit=5000))
#  # Example on how to generate a set of SSM parameters from anchored parameters
#  xanchor <- GenerateAnchor(nests=resultNest_4p)
#  x <- resultNest_4p$par
#  xanchor["294"] <- 0
#  xanchor["308"] <- 2.3291035
#  xprime <- ChangeSSM(parameters = xanchor,
#                      initial.parameters = x, control=list(maxit=5000))
#  plotR(result=resultNest_4p, parameters=list(resultNest_4p$par, xprime$par), 
#        ylim=c(0,0.3), col=c("black", "red"), 
#        legend=list("Fitted parameters", "Constrainted parameters"))
# ## End(Not run)