phenology (version 5.1)

fit_phenology: Fit the phenology parameters to timeseries of counts.

Description

Function of the package phenology to fit parameters to timeseries. To fit data, the syntaxe is : Result <- fit_phenology(data=dataset, parametersfit=par, parametersfixed=pfixed, trace=1, method_incertitude=2, zero_counts=TRUE, hessian=TRUE) or if no parameter is fixed : Result <- fit_phenology(data=dataset, parametersfit=par) Add trace=1 [default] to have information on the fit progression or trace=0 to hide information on the fit progression. zero_counts = c(TRUE, TRUE, FALSE) indicates whether the zeros have been recorded for each of these timeseries. Defaut is TRUE for all. hessian = FALSE does not estimate se of parameters.

Usage

fit_phenology(data = file.choose(), parametersfit = NULL, parametersfixed = NULL, trace = 1, maxit = 500, method_incertitude = "convolution", infinite = 200, zero_counts = TRUE, cofactors = NULL, add.cofactors = NULL, hessian = TRUE, silent = FALSE, growlnotify = TRUE, zero = 1e-09)

Arguments

data

A dataset generated by add_format

parametersfit

Set of parameters to be fitted

parametersfixed

Set of fixed parameters

trace

If 1, it shows the progression of fit; 0 is silent (don't be afraid if it is very long !)

maxit

Number of iterations for search before checking if it converges. If it does not converge, it will continue to search for. Default is 500.

method_incertitude

'combinatory' estimates likelihood of all combinations for nest numbers; 'convolution' [default] uses the exact likelihood of the sum of negative binomial distribution.

infinite

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

zero_counts

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

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

hessian

If FALSE does not estimate se of parameters

silent

If TRUE does not show any message

growlnotify

If FALSE, does not send growl notification (only in MacOSX)

zero

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

Value

Return a list of with data and result

Details

fit_phenology fits parameters to timeseries.

Examples

## Not run: 
# library(phenology)
# # 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 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, parametersfixed=NULL)
# # Run the optimisation
# result_Gratiot <- fit_phenology(data=data_Gratiot, 
# 		parametersfit=parg, parametersfixed=NULL, trace=1)
# data(result_Gratiot)
# # Plot the phenology and get some stats
# output <- plot(result_Gratiot)
# # Use fit with co-factor
# # First extract tide information for that place
# td <- tide.info(year=2001, latitude=4.9167, longitude=-52.3333, tz="America/Cayenne")
# td2 <- td[td$Tide=="High Tide", ]
# td3 <- cbind(td2, Date=as.Date(td2$Date.Time))
# td4 <- td3[(as.POSIXlt(td3$Date.Time)$hou<6) | (as.POSIXlt(td3$Date.Time)$hou>18), ]
# with(td4, plot(Date.Time, Level, type="l"))
# data_Gratiot$Complete$Date
# td5 <- merge(data_Gratiot$Complete, td4, by.x="Date", by.y="Date")
# td6 <- td5[, c("Date", "Level")]
# parg <- par_init(data_Gratiot, parametersfixed=NULL, add.cofactors="Level")
# result_Gratiot_CF <- fit_phenology(data=data_Gratiot, 
# 		parametersfit=parg, parametersfixed=NULL, trace=1, cofactors=td6, 
# 		add.cofactors="Level")
# compare_AIC(WithoutCF=result_Gratiot, WithCF=result_Gratiot_CF)
# plot(result_Gratiot_CF)
# ## End(Not run)