config, data.table, DBI (>= 1.1.0), Hmisc, psych, rapportools,
RJDBC, RJSONIO, RPostgres, shiny, shinyjs, xml2

c(person(given = "Jonathan M.",
family = "Mang",
role = c("aut", "cre"),
email = "jonathan.mang@uk-erlangen.de",
comment = c(ORCID = "0000-0003-0518-4710")),
person(given = "Lorenz A.",
family = "Kapsner",
role = "aut",
comment = c(ORCID = "0000-0003-1866-860X")),
person(given = "MIRACUM - Medical Informatics in Research and Care in University Medicine",
role = "fnd"),
person(given = "Universitätsklinikum Erlangen, Germany",
role = "cph"))

Finding Patterns of Monotonicity and Convexity in Data
Paul Schneider [aut, ths], Liudmila Karagyaur [aut]
Given  an initial set of points, this package minimizes the number of elements to discard from this set such that there exists at least one monotonic and convex mapping within pre-specified upper and lower bounds.

c(person("Rafael", "de Andrade Moral", role = c("aut", "cre"), email = "rafael.deandrademoral@mu.ie"), person("John", "Connolly", role = "aut"), person("Caroline", "Brophy", role = "aut"))
Rafael de Andrade Moral [aut, cre],
John Connolly [aut],
Caroline Brophy [aut]
Rafael de Andrade Moral <rafael.deandrademoral@mu.ie>
methods, graphics, stats, utils, hnp, rootSolve
The 'DImodels' package is suitable for analysing data from biodiversity and ecosystem function studies using the Diversity-Interactions (DI) modelling approach introduced by Kirwan et al. (2009) <doi:10.1890/08-1684.1>. Suitable data will contain proportions for each species and a community-level response variable, and may also include additional factors, such as blocks or treatments. The package can perform data manipulation tasks, such as computing pairwise interactions (the DI_data_prepare() function), can perform an automated model selection process (the autoDI() function) and has the flexibility to fit a wide range of user-defined DI models (the DI() function).

The 'DImodels' package is suitable for analysing data from biodiversity and ecosystem function studies using the Diversity-Interactions (DI) modelling approach introduced by Kirwan et al. (2009) <doi:10.1890/08-1684.1>. Suitable data will contain proportions for each species and a community-level response variable, and may also include additional factors, such as blocks or treatments. The package can perform data manipulation tasks, such as computing pairwise interactions (the DI_data() function), can perform an automated model selection process (the autoDI() function) and has the flexibility to fit a wide range of user-defined DI models (the DI() function).