summary.phenology {phenology}R Documentation

Print the result information from a result object.

Description

The function summary.phenology shows result and estimates confidence interval.
If several years are analyzed, the sum_synthesis result can be obtained only if there is not a mix of bisextile and non-bisextile years.

Usage

## S3 method for class 'phenology'
summary(
  object,
  resultmcmc = NULL,
  chain = 1,
  series = "all",
  replicate.CI.mcmc = "all",
  replicate.CI = 10000,
  level = 0.95,
  print = TRUE,
  ...
)

Arguments

object

A result file generated by fit_phenology

resultmcmc

A mcmc object

chain

The number of chain to be used in resultmcmc

series

Names of the series to be analyzed or "all"

replicate.CI.mcmc

Number of iterations to be used or "all"

replicate.CI

Number of replicates for ML resampling

level

Level to estimate confidence interval or credibility interval

print

Should information be shown

...

Not used

Details

summary.phenology prints the information from a result object.

Value

A list with five objects: synthesis is a data.frame with global estimate of nesting.
details_MCMC, details_ML, details_mean are lists with day by day information for each series, and sum_synthesis is the synthesis of the sum of all analyzed time-series.

Author(s)

Marc Girondot marc.girondot@gmail.com

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_delta(), 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()

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)
# Display information from the result
s <- summary(result_Gratiot)
# Using mcmc
s <- summary(object=result_Gratiot, resultmcmc=result_Gratiot_mcmc)

## End(Not run)

[Package phenology version 9.1 Index]