summary.phenology: Print the result information from a result object.

In phenology: Tools to Manage a Parametric Function that Describes Phenology and More

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.
If save.all is true, it will return a object $save.all as an array with dimensions:
c("without_obs_ML", "with_obs_ML", "without_obs_MCMC", "with_obs_MCMC"),
series,
replicates
The replicates dimension will be the max of replicate.CI.mcmc and replicate.CI. If they are not equal, NA will be present for the missing replicates. See examples.

Usage

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

Arguments

object	A result file generated by fit_phenology
resultmcmc	A mcmc object
season	The number of season to analyze
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
save.all	If TRUE, returns all the values for replicates
...	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 [e-mail]

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(), 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, 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)
sa <- summary(object=result_Gratiot, resultmcmc=result_Gratiot_mcmc, save.all = TRUE)
hist(sa$save.all["with_obs_MCMC", "Complete", ])

## End(Not run)

phenology documentation built on June 17, 2025, 9:08 a.m.