embryogrowth (version 9.5)

likelihoodR: Estimate the likelihood of a set of parameters for nest incubation data

Description

Estimate the likelihood of a set of parameters for nest incubation data

Usage

likelihoodR(
  result = NULL,
  parameters = NULL,
  fixed.parameters = NULL,
  temperatures = NULL,
  integral = NULL,
  derivate = NULL,
  hatchling.metric = NULL,
  M0 = NULL,
  hessian = FALSE,
  weight = NULL,
  parallel = TRUE,
  echo = TRUE
)

Value

A result object

Arguments

result

A object obtained after searchR or likelihoodR

parameters

A set of parameters

fixed.parameters

A set of parameters that will not be changed

temperatures

Timeseries of temperatures

integral

Function used to fit embryo growth: integral.Gompertz, integral.exponential or integral.linear

derivate

Function used to fit embryo growth: dydt.Gompertz, dydt.exponential or dydt.linear. It will replace the one in NestsResult.

hatchling.metric

Mean and SD of size of hatchlings

M0

Measure of hatchling size or mass proxi at laying date

hessian

If TRUE, the hessian matrix is estimated and the SE of parameters estimated.

weight

A named vector of the weight for each nest for likelihood estimation

parallel

If true, try to use several cores using parallel computing.

echo

If FALSE, does not display the result.

Author

Marc Girondot

Details

likelihoodR estimates the likelihood of a set of parameters for nest incubation data

Examples

if (FALSE) {
library(embryogrowth)
data(nest)
formated <- FormatNests(nest)
# The initial parameters value can be:
# "T12H", "DHA",  "DHH", "Rho25"
# Or
# "T12L", "DT", "DHA",  "DHH", "DHL", "Rho25"
# K for Gompertz must be set as fixed parameter or being a constant K  
# or relative to the hatchling size rK
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 integral.linear or integral.exponential
LresultNest_4p <- likelihoodR(parameters=x, fixed.parameters=pfixed,  
	temperatures=formated, integral=integral.Gompertz, M0=1.7,  
	hatchling.metric=c(Mean=39.33, SD=1.92))
data(resultNest_4p_SSM)
LresultNest_4p <- likelihoodR(result=resultNest_4p_SSM)
}