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phenesse

phenesse: Estimate phenological metrics using presence-only data

The phenesse package provides tools in R to estimate phenological metrics using presence only data. The package includes a new Weibull-parameterized estimator described in Belitz et al. (2020) (https://doi.org/10.1111/2041-210X.13448). Additionally, the package provides a non-parametric bootstrap approach to estimating confidence intervals for this estimator as well as quantile and mean estimates.

Note that generating confidence intervals of a Weibull-parameterized estimate is very computationally expensive. We recommend exploring parallelization options when generating many CIs of Weibull-parameterized estimates. An example of parallelization can be found in the vignette.

Installation

CRAN

phenesse is available on CRAN. Install using install.packages("phenesse")

GitHub

The development version of phenesse is available on GitHub. To install without a vignette, use: devtools::install_github("mbelitz/phenessse")

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Install

install.packages('phenesse')

Monthly Downloads

205

Version

0.1.3

License

CC0

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Maintainer

Michael Belitz

Last Published

June 9th, 2025

Functions in phenesse (0.1.3)

estimate_ci

Calculate confidence intervals using bootstrap of any statistical function of interest.
weib_percentile

Calculating a percentile estimate of a seasonal abundance distribution from incidental observations.
inat_examples

Example iNaturalist-sourced data
quantile_ci

Calculating the confidence intervals (CIs) of a quantile estimate of a a vector of observations using non-parametric bootstrapping.
weib_percentile_ci

Calculating the CIs of a percentile estimate of a seasonal abundance distribution using the non-parametric bootstrapping.
mean_ci

Calculating the confidence intervals (CIs) of an arithmetic mean.