Package: phenology 2026.2.28

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

Functions used to fit and test the phenology of species based on counts. Based on Girondot, M. (2010) <doi:10.3354/esr00292> for the phenology function, Girondot, M. (2017) <doi:10.1016/j.ecolind.2017.05.063> for the convolution of negative binomial, Girondot, M. and Rizzo, A. (2015) <doi:10.2993/etbi-35-02-337-353.1> for Bayesian estimate, Pfaller JB, ..., Girondot M (2019) <doi:10.1007/s00227-019-3545-x> for tag-loss estimate, Hancock J, ..., Girondot M (2019) <doi:10.1016/j.ecolmodel.2019.04.013> for nesting history, Laloe J-O, ..., Girondot M, Hays GC (2020) <doi:10.1007/s00227-020-03686-x> for aggregating several seasons.

Authors:Marc Girondot [aut, cre]

phenology_2026.2.28.tar.gz
phenology_2026.2.28.zip(r-4.7)phenology_2026.2.28.zip(r-4.6)phenology_2026.2.28.zip(r-4.5)
phenology_2026.2.28.tgz(r-4.6-any)phenology_2026.2.28.tgz(r-4.5-any)
phenology_2026.2.28.tar.gz(r-4.7-any)phenology_2026.2.28.tar.gz(r-4.6-any)
phenology_2026.2.28.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
phenology/json (API)
NEWS

# Install 'phenology' in R:
install.packages('phenology', repos = c('https://marc-girondot.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.78 score 1 stars 203 scripts 245 downloads 55 exports 26 dependencies

Last updated from:8c713ddb8b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK203
source / vignettesOK231
linux-release-x86_64OK200
macos-release-arm64OK115
macos-oldrel-arm64OK113
windows-develOK168
windows-releaseOK154
windows-oldrelOK123
wasm-releaseOK139

Exports:adapt_parametersadd_phenologyadd_SEAutoFitPhenologyBayesian.remigrationBE_to_LBLECI.RMUECFOCF_fECFOCF_fullExponentialRegressionextract_resultfit_phenologyfitCFfitCF_MHmcmcfitCF_MHmcmc_pfitRMUfitRMU_MHmcmcfitRMU_MHmcmc_pfixed.parameters0generateCFIPFitIPModelIPPredictL_to_LBLELBLE_to_BELBLE_to_Llikelihood_phenologylnLCFLnRI_normmap_phenologyMinBMinE_to_Minpar_initParameter_Global_Yearphenologyphenology_MHmcmcphenology_MHmcmc_pphenology2fitRMUplot_deltaplot_phiremove_siteRIRI2BPshift_sinusoidTableECFOCFTagloss_cumulTagloss_daymaxTagloss_fitTagloss_formatTagloss_LTagloss_LengthObsTagloss_mcmcTagloss_mcmc_pTagloss_modelTagloss_simulatetoggle_Min_PMin

Dependencies:clicodacpp11farverggplot2gluegtableHelpersMGisobandlabelinglatticelifecycleMASSMatrixnloptrnumDerivoptimxpracmaR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Tools to Manage a Parametric Function that Describes Phenology and Morephenology-package
Extract the parameters from a set of parameters to be used with another dataset.adapt_parameters
Create a new dataset or add a timeserie to a previous dataset.add_phenology
Add standard error for a fixed parameter.add_SE
Automatic fit for phenology and testsAutoFitPhenology
Return a posterior remigration interval.Bayesian.remigration
Transform a set of parameters from Begin End to LengthB LengthE.BE_to_LBLE
Calculate the confidence interval of the results of fitRMU()CI.RMU
Calculate a table of probabilities of ECF and OCF.ECFOCF_f
Calculate a table of probabilities of ECF and OCF.ECFOCF_full
Non-biased exponential regressionExponentialRegression
Extract the set of parameters from a result object.extract_result
Fit the phenology parameters to timeseries of counts.fit_phenology
Fit a model of Clutch Frequency for marine turtles.fitCF
Run the Metropolis-Hastings algorithm for ECFOCF datafitCF_MHmcmc
Generate set of parameters to be used with fitCF_MHmcmc()fitCF_MHmcmc_p
Adjust incomplete timeseries with various constraints.fitRMU
Run the Metropolis-Hastings algorithm for RMU.datafitRMU_MHmcmc
Generates set of parameters to be used with fitRMU_MHmcmc()fitRMU_MHmcmc_p
Generate a set of fixed parameters for series with only 0 countsfixed.parameters0
Generate a set of data to test Clutch Frequency for marine turtles.generateCF
Leatherback nest counts from Gratiot et al. (2006) Figure 1Gratiot
Fit a model of Internesting Period for marine turtles.IPFit
Estimates the pattern of internesting intervals for a set of parameters.IPModel
Predict the possible clutch number based on observed Internesting Period.IPPredict
Transform a set of parameters from Length format to LengthB LengthEL_to_LBLE
Transform a set of parameters from LengthB LengthE to Begin End.LBLE_to_BE
Transform a set of parameters from LengthB LengthE format to LengthLBLE_to_L
Estimate the likelihood of timeseries based on a set of parameters.likelihood_phenology
Calculate the -log likelihood of data within a model.lnLCF
Return a remigration interval.LnRI_norm
Return Log Likelihood of a fit done using fitCFlogLik.ECFOCF
Return Log Likelihood of a fit generated by fitRMUlogLik.fitRMU
Return Log Likelihood of a fit generated by fit_phenologylogLik.phenology
Return Log Likelihood of a fit generated by Tagloss_fitlogLik.Tagloss
Likelihood map of Leatherback nest countsmap_Gratiot
Generate a likelihood map varying Phi and Delta.map_phenology
Database of tagged marine turtles in 2002MarineTurtles_2002
Transform a set of parameters from MinB and MinE to MinMinBMinE_to_Min
Model of tagloss based on Rivalan datao_4p_p1p2
Database of leatherback CMR in French GuianaoutLR
Calculate initial set of parameters.par_init
Transform a set of parameters from Year to global effect, or reverseParameter_Global_Year
Run a shiny application for basic functions of phenology packagephenology
Run the Metropolis-Hastings algorithm for dataphenology_MHmcmc
Generates set of parameters to be used with phenology_MHmcmc()phenology_MHmcmc_p
Create the data to be used with fitRMU() for a summary(phenology).phenology2fitRMU
Plot a likelihood lineplot obtained after map_phenology.plot_delta
Plot the best likelihood for fixed Phi value.plot_phi
Plot a result of clutch frequency fit.plot.ECFOCF
Plot the synthesis of RMU fit.plot.fitRMU
Plot a result of Internesting Period fit or data.plot.IP
Plot the phenology from a result.plot.phenology
Plot a likelihood map with Delta and Phi varying.plot.phenologymap
Plot the remigration intervals.plot.Remigration
Plot a TableECFOCF dataset.plot.TableECFOCF
Plot the daily rate of tag loss.plot.Tagloss
Plot data used for tagloss analysis.plot.TaglossData
Print the result information from a result x.print.phenology
Print information on a phenologymap object.print.phenologymap
Print the information from a ouput x.print.phenologyout
Removes site information from a set of parameters.remove_site
Result of the fit of Leatherback nest countsresult_Gratiot
Result of the fit of Leatherback nest countsresult_Gratiot_Flat
Result of the fit of Leatherback nest countsresult_Gratiot1
Result of the fit of Leatherback nest countsresult_Gratiot2
Return an expected remigration interval.RI
Calculate Breeding Proportion from Remigration Interval.RI2BP
Shift sinusoid information.shift_sinusoid
Print the result information from a IP object.summary.IP
Print the result information from a result object.summary.phenology
Print information on a phenologymap object.summary.phenologymap
Print the summary information from a ouput object.summary.phenologyout
Format a CMR dataset into a file that fitCF can use.TableECFOCF
Return the cumulative rate of tag loss.Tagloss_cumul
Return the maximum number of days an individual has been observed in a dataset.Tagloss_daymax
fit a model of tag loss using a CMR database.Tagloss_fit
Format a CMR dataset into a file that Tagloss_L can use.Tagloss_format
Return the -log likelihood of a set of individuals under a model of tagloss.Tagloss_L
Return a list with the number of days for different kinds of individuals are seen.Tagloss_LengthObs
Bayesian model of tag loss using a CMR database.Tagloss_mcmc
Generates set of parameters to be used with Tagloss_mcmc()Tagloss_mcmc_p
Return the daily rate of tag loss.Tagloss_model
Return a list with the number of days different kinds of individuals are seen.Tagloss_simulate
Transform a set of parameters from Min, MinB or MinE to PMin, PminB or PminE, or reversetoggle_Min_PMin