phenology (version 7.3)

likelihood_phenology: Estimate the likelihood of timeseries based on a set of parameters.

Description

This function is used to estimate the likelihood based on a set of parameters.

Usage

likelihood_phenology(data = NULL, fitted.parameters = NULL,
  fixed.parameters = NULL, zero_counts = NULL,
  method_incertitude = NULL, result = NULL, cofactors = NULL,
  add.cofactors = NULL, infinite = 200, zero = 1e-09)

Arguments

data

Dataset generated with add_format

fitted.parameters

Set of parameters to be fitted

fixed.parameters

Set of fixed parameters

zero_counts

example c(TRUE, TRUE, FALSE) indicates whether the zeros have been recorder for each of these timeseries. Defaut is TRUE for all.

method_incertitude

2 [default] is the correct one from a statistical point of view; 0 is an aproximate method more rapid; 1 is an alternative more rapid but biased.

result

An object obtained after fit_phenology()

cofactors

data.frame with a column Date and a column for each cofactor

add.cofactors

Names of the column of parameter cofactors to use as a cofactor

infinite

Number of iterations for dSnbinom() used for method_incertitude='sum'

zero

If the theoretical nest number is under this value, this value wll be used

Value

The likelihood of the data with the parameters

Details

likelihood_phenology estimate likelihood for a set of parameters.

Examples

# NOT RUN {
# Read a file with data
Gratiot<-read.delim("http://max2.ese.u-psud.fr/epc/conservation/BI/Complete.txt", header=FALSE)
data(Gratiot)
# Generate a formated 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)
# Estimate likelihood with this initial set of parameters
likelihood_phenology(data=data_Gratiot, fitted.parameters=parg, fixed.parameters=NULL)
# Or directly from a result object
likelihood_phenology(result=result_Gratiot)
# }