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phenology (version 10.1)

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 syntax is :
Result <- fit_phenology(data=dataset, fitted.parameters=par, fixed.parameters=pfixed, trace=1, hessian=TRUE)
or if no parameter is fixed :
Result <- fit_phenology(data=dataset, fitted.parameters=par)
Add trace=1 [default] to have information on the fit progression or trace=0 to hide information on the fit progression.
hessian = FALSE does not estimate Hessian matrix and SE of parameters.
If the parameter Theta is fixed to +Inf, a Poissonian model of daily nest distribution is implemented.
Special section about cofactors:
cofactors must be a data.frame with a column Date and a column for each cofactor
add.cofactors are the names of the column of parameter cofactors to use as a cofactor;
The model is then: parameter[add.cofactors] * cofactor[, add.cofactors]
If the name of the parameter is paste0(add.cofactors, "multi"), then the model is:
parameter[paste0(add.cofactors, "multi")] * cofactor[, add.cofactors] * (number of nests without cofactor)
About parallel computing:
Set options mc.cores and forking to tell what sort of parallel computing
Example:
options(mc.cores = detectCores())
options(forking = FALSE)

Usage

fit_phenology(
  data = file.choose(),
  fitted.parameters = NULL,
  fixed.parameters = NULL,
  model_before = NULL,
  store.intermediate = FALSE,
  file.intermediate = "Intermediate.rda",
  hessian = FALSE,
  silent = FALSE,
  cofactors = NULL,
  add.cofactors = NULL,
  zero = 1e-09,
  lower = 0,
  upper = Inf,
  stop.fit = FALSE,
  method_Snbinom = "saddlepoint",
  control = list(trace = 1, REPORT = 1, maxit = 1000),
  method = c("Nelder-Mead", "L-BFGS-B")
)

Value

Return a list of with data and result

Arguments

data

A dataset generated by add_format

fitted.parameters

Set of parameters to be fitted

fixed.parameters

Set of fixed parameters

model_before

The change of parameters before to estimate daily counts.

store.intermediate

TRUE or FALSE to save the intermediates

file.intermediate

Name of the file where to save the intermediates as a list

hessian

If FALSE does not estimate se of parameters

silent

If TRUE does not show any message

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

zero

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

lower

Lower bound for each parameter

upper

Upper bound for each parameter

stop.fit

If TRUE, will stop search for parameters even if not ML

method_Snbinom

Can be Furman, exact, or saddlepoint.

control

List for control parameters for optim

method

Method used by optim. Several can be setup.

Author

Marc Girondot marc.girondot@gmail.com

Details

fit_phenology fits parameters to timeseries.

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(), likelihood_phenology(), logLik.phenology(), map_Gratiot, map_phenology(), par_init(), phenology(), phenology2fitRMU(), phenology_MHmcmc(), phenology_MHmcmc_p(), plot.phenology(), plot.phenologymap(), plot_delta(), plot_phi(), print.phenology(), print.phenologymap(), print.phenologyout(), remove_site(), result_Gratiot, result_Gratiot1, result_Gratiot2, result_Gratiot_Flat, result_Gratiot_mcmc, summary.phenology(), summary.phenologymap(), summary.phenologyout()