Estimates statistically significant fluorescent marker combination values within
which one immunologically distinctive group (i.e., disease case) is more associated than
another group (i.e., healthy control), successively, using various combinations (i.e.,
"gates") of fluorescent markers to examine features of cells that may be different between
groups. For a two-group comparison, the 'gateR' package uses the spatial relative risk
function that is estimated using the 'sparr' package. Details about the 'sparr' package
methods can be found in the tutorial: Davies et al. (2018) <doi:10.1002/sim.7577>. Details
about kernel density estimation can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>.
More information about relative risk functions using kernel density estimation can be
found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.
fields, graphics, grDevices, maptools, pgirmess, raster, sp,
sparr, spatstat, stats, tibble, utils
flowWorkspaceData, knitr, ncdfFlow, R.rsp, spelling, testthat

fields, graphics, grDevices, lifecycle, raster, sparr,
SpatialPack, spatstat.geom, stats, tibble, utils

fields, graphics, grDevices, lifecycle, raster, sparr,
SpatialPack, stats, tibble, utils

fields, graphics, grDevices, lifecycle, raster, rlang, sparr,
SpatialPack, stats, tibble, utils

Easily Gate or Select Points on a Scatter Plot
Allows user to choose/gate a region on the plot and returns points
within it.

Lotka-Volterra Models for Gause's 'Struggle for Existence'
c(person("Adam", "Clark", role = c("aut", "cre"),
email = c("adam.tclark@gmail.com"),
comment = c(ORCID = "0000-0002-8843-3278")),
person("Lina", "Mühlbauer", role = c("aut")),
person("Maximilienne", "Schulze", role = c("aut")))
A collection of tools and data for analyzing the Gause microcosm experiments, and for fitting Lotka-Volterra models to time series data. Includes methods for fitting single-species logistic growth, and multi-species interaction models, e.g. of competition, predator/prey relationships, or mutualism. See documentation for individual functions for examples. In general, see the lv_optim() function for examples of how to fit parameter values in multi-species systems. Note that the general methods applied here, as well as the form of the differential equations that we use, are described in detail in the Quantitative Ecology textbook by Lehman et al., available at <http://hdl.handle.net/11299/204551>, and in Lina K. Mühlbauer, Maximilienne Schulze, W. Stanley Harpole, and Adam T. Clark. 'gauseR': Simple methods for fitting Lotka-Volterra models describing Gause's 'Struggle for Existence' in the journal Ecology and Evolution.
Adam Clark [aut, cre] (<https://orcid.org/0000-0002-8843-3278>),
Lina Mühlbauer [aut],
Maximilienne Schulze [aut]