likelihoodR | R Documentation |
Estimate the likelihood of a set of parameters for nest incubation data
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
)
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. |
likelihoodR estimates the likelihood of a set of parameters for nest incubation data
A result object
Marc Girondot marc.girondot@gmail.com
## Not run:
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)
## End(Not run)
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