Title: An Interface for Face Recognition
Authors@R: person("Carsten", "Schwemmer", email = "c.schwem2er@gmail.com", comment = c(ORCID = "0000-0001-9084-946X"), role = c("aut", "cre"))
Description: Provides an interface to the 'Kairos' Face Recognition API <https://kairos.com/face-recognition-api>. The API detects faces in images and returns estimates for demographics like gender, ethnicity and age.
Author: Carsten Schwemmer [aut, cre] (<https://orcid.org/0000-0001-9084-946X>)

Title: A C++ Framework for Plant-Plant Interaction IBMs
Authors@R: c(person("Mali", "Salles", email = "marinacs@gmail.com", role = c("aut", "cre")),
Description: A tool for simulating a variety of spatial individual-based models of
plant-plant interactions. User-created models can include any number of species, each of
which can be structured in any number of life-stages, where each life-stage has specific
death, growth and reproduction rates, as well as specific interaction radius, dispersal
radius, and interaction effects over each other species/life-stage. Life stages were modeled
so as to be a stochastic, individual-based version of differential Matrix Population
Models (Caswell 2001, ISBN:0-87893-096-5). Interactions can be positive
(facilitation) or negative (competition) and can affect death rates, growth rates or
reproduction rates. Interactions from multiple numbers are additive, so as to best
approximate classic population dynamics models such as the logistic model and
Lotka-Volterra model (Britton 2004, ISBN:9781852335366). All models work in continuous time, implemented as an optimized version
of the Gillespie algorithm (Gillespie 1976 <doi:10.1016/0021-9991(76)90041-3>) for independent exponential times, and continuous space.
Imports: Rcpp (>= 0.12.14), Matrix, grid, animation

Description: The package contains methods using stochastic approximation
Depends: Matrix, graphics, plotrix, datasets, FactoMineR

Title: Data Mining Methods for Data Streams
Depends: R (>= 2.14.0), plotrix, FactoMineR, Matrix

Title: Instrumental Variables Estimation for 2^k Factorial Experiments
Description: Implements instrumental variable estimators for 2^K factorial experiments with noncompliance.
Suggests: tibble, dplyr, rmarkdown, knitr
Packaged: 2021-05-20 01:16:30 UTC; mblackwell
Author: Matthew Blackwell [aut, cre] (<https://orcid.org/0000-0002-3689-9527>),