| plot_delta {phenology} | R Documentation |
Plot a likelihood lineplot obtained after map_phenology.
Description
This function plots a likelihood lineplot obtained after map_phenology.
Usage
plot_delta(map = NULL, Phi = NULL, ...)
Arguments
map |
A map generated with map_phenology |
Phi |
Phi value or NULL |
... |
Parameters for plot |
Details
plot_delta plots the likelihood delta for fixed Phi value.
Value
Return None
Author(s)
Marc Girondot
See Also
Other Phenology model:
AutoFitPhenology(),
BE_to_LBLE(),
Gratiot,
LBLE_to_BE(),
LBLE_to_L(),
L_to_LBLE(),
MarineTurtles_2002,
MinBMinE_to_Min(),
adapt_parameters(),
add_SE(),
add_phenology(),
extract_result(),
fit_phenology(),
likelihood_phenology(),
logLik.phenology(),
map_Gratiot,
map_phenology(),
par_init(),
phenology2fitRMU(),
phenology_MHmcmc_p(),
phenology_MHmcmc(),
phenology(),
plot.phenologymap(),
plot.phenology(),
plot_phi(),
print.phenologymap(),
print.phenologyout(),
print.phenology(),
remove_site(),
result_Gratiot1,
result_Gratiot2,
result_Gratiot_Flat,
result_Gratiot_mcmc,
result_Gratiot,
summary.phenologymap(),
summary.phenologyout(),
summary.phenology()
Examples
## Not run:
library("phenology")
# Read a file with data
data(Gratiot)
# Generate a formatted list nammed data_Gratiot
data_Gratiot<-add_phenology(Gratiot, name="Complete",
reference=as.Date("2001-01-01"), format="%d/%m/%Y")
# Generate initial points for the optimisation
parg<-par_init(data_Gratiot, fixed.parameters=NULL)
# Run the optimisation
result_Gratiot<-fit_phenology(data=data_Gratiot,
fitted.parameters=parg, fixed.parameters=NULL)
data(result_Gratiot)
# Extract the fitted parameters
parg1<-extract_result(result_Gratiot)
# Add constant Alpha and Tau values
# [day d amplitude=(Alpha+Nd*Beta)^Tau with Nd being the number of counts for day d]
pfixed<-c(parg1, Alpha=0, Tau=1)
pfixed<-pfixed[-which(names(pfixed)=="Theta")]
# The only fitted parameter will be Beta
parg2<-c(Beta=0.5, parg1["Theta"])
# Generate a likelihood map
# [default Phi=seq(from=0.1, to=20, length.out=100) but it is very long]
# Take care, it takes 20 hours ! The data map_Gratiot has the result
map_Gratiot<-map_phenology(data=data_Gratiot,
Phi=seq(from=0.1, to=20, length.out=100),
fitted.parameters=parg2, fixed.parameters=pfixed)
data(map_Gratiot)
# Plot the min(-Ln L) for Delta varying with Phi equal to the value for maximum likelihood
plot_delta(map=map_Gratiot)
# Plot the min(-Ln L) for Delta varying with Phi the nearest to 15
plot_delta(map=map_Gratiot, Phi=15)
## End(Not run)