An alternative to carrying out phenotypic adaptability and stability analyses, taking into account nonparametric statistics. Can be used as a robust approach, less sensitive to departures from common genotypic, environmental, and GxE effects data assumptions (e.g., normal distribution of errors).

Estimate Phenological Metrics using Presence-Only Data
c(person("Michael", "Belitz", email = "mbelitz@ufl.edu", role = c("aut", "cre")),
person("Caitlin", "Campbell", email = "caitjcampbell@gmail.com", role = "ctb"))
Generates Weibull-parameterized estimates of phenology for any percentile of
a distribution using the framework established in Cooke (1979)
<doi.org/10.1093/biomet/66.2.367>. Non-parametric bootstrapping can be used
to generate confidence intervals around those estimates.
Additionally, this package offers an easy way to perform non-parametric
bootstrapping to generate confidence intervals for quantile estimates or
mean estimates.
Michael Belitz [aut, cre],
Caitlin Campbell [ctb]

c(person("Michael", "Belitz", email = "mbelitz@ufl.edu", role = c("aut", "cre")),
person("Caitlin", "Campbell", email = "caitjcampbell@gmail.com", role = "ctb"),
person("Daijinag", "Li", email = "daijianglee@gmail.com", role = "ctb"))
Generates Weibull-parameterized estimates of phenology for any percentile of
a distribution using the framework established in Cooke (1979)
<doi:10.1093/biomet/66.2.367>.. Extensive testing against other
estimators suggest the weib_percentile() function is especially useful in
generating more accurate and less biased estimates of onset and offset.
Non-parametric bootstrapping can be used to generate confidence intervals
around those estimates. Additionally, this package offers an easy way to
perform non-parametric bootstrapping to generate confidence intervals for
quantile estimates, mean estimates, or any statistical function of interest.
Michael Belitz [aut, cre],
Caitlin Campbell [ctb],
Daijinag Li [ctb]

c(person("Michael", "Belitz", email = "mbelitz@ufl.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8162-5998")),
person("Caitlin", "Campbell", email = "caitjcampbell@gmail.com", role = "ctb", comment = c(ORCID = "0000-0002-8199-7775")),
person("Daijiang", "Li", email = "daijianglee@gmail.com", role = "ctb", comment = c(ORCID = "0000-0002-0925-3421")))
Generates Weibull-parameterized estimates of phenology for any percentile of
a distribution using the framework established in Cooke (1979)
<doi:10.1093/biomet/66.2.367>. Extensive testing against other
estimators suggest the weib_percentile() function is especially useful in
generating more accurate and less biased estimates of onset and offset
(Belitz et al. 2020 <doi.org:10.1111/2041-210X.13448>. Non-parametric
bootstrapping can be used to generate confidence intervals around those
estimates, although this is computationally expensive. Additionally, this
package offers an easy way to perform non-parametric bootstrapping to
generate confidence intervals for quantile estimates, mean estimates,
or any statistical function of interest.