Detection of edgepoints in images based on the difference
of two asymmetric M kernel estimators. Linear and circular
regression clustering based on redescending M estimators.
Detection of linear edges in images.

Detection of edge points in images based on the difference
of two asymmetric M-kernel estimators. Linear and circular
regression clustering based on redescending M-estimators.
Detection of linear edges in images.

Ecological Data Collection and Processing Package
person(given = "Ward",
family = "Fonteyn",
role = c("aut", "cre"),
email = "ward.fonteyn@kuleuven.be")
This is the course package for the exercise portion of the "Ecological Data Collection and Processing" course.

Get Evaporative Demand Drought Index Raster Data
person(given = "Max",
family = "Joseph",
role = c("aut", "cre"),
email = "maxwell.b.joseph@colorado.edu",
comment = c(ORCID = "0000-0002-7745-9990"))
Finds and downloads raw Evaporative Demand Drought
Index (EDDI) data, then reads the data into 'R' using the 'raster'
package. The EDDI product detects drought at multiple time scales,
from weekly "flash droughts" to long-term droughts. More information
about the EDDI data product can be found at
<https://www.esrl.noaa.gov/psd/eddi/>.
covr, knitr, rmarkdown, sf, sp, testthat

c(
person('Paul', 'Egeler', email = 'paulegeler@gmail.com', role = c('aut','cre')),
person('Tashi', 'Reigle', role = 'ctb'))
Compute a cyclist's Eddington number, including efficiently
computing cumulative E over a vector. A cyclist's Eddington number
<https://en.wikipedia.org/wiki/Arthur_Eddington#Eddington_number_for_cycling>
is the maximum number satisfying the condition such that a cyclist has
ridden E miles or greater in E days. The algorithm in this package is an
improvement over the conventional approach because both summary statistics
and cumulative statistics can be computed in linear time, since it does not
require initial sorting of the data. These functions may also be used for
computing h-indices for authors, a metric described by Hirsch (2005)
<doi:10.1073/pnas.0507655102>. Both are specific applications of computing
the side length of a Durfee square
<https://en.wikipedia.org/wiki/Durfee_square>.
Paul Egeler [aut, cre],
Tashi Reigle [ctb]