Title: GEE Solver for Correlated Nominal or Ordinal Multinomial
Description: GEE solver for correlated nominal or ordinal multinomial
responses using a local odds ratios parameterization.

Description: GEE solver for correlated nominal or ordinal multinomial responses using a local odds ratios parameterization.

Description: GEE solver for correlated nominal or ordinal multinomial responses
using a local odds ratios parameterization.

Title: Multi Action Button for 'Shiny' Applications
person("Sergey", "Pimenov", role = "cph",
Description: Provides a multi action button for usage in 'shiny'

Title: Apply Functions to Multiple Multidimensional Arguments
person("Alasdair", "Hunter", , "alasdair.hunter@bsc.es", role = c("aut", "cre")),
person("Nicolau", "Manubens", , "nicolau.manubens@bsc.es", role = "aut"))
Description: The base apply function and its variants, as well as the related functions in the 'plyr' package, typically apply user-defined functions to a single argument (or a list of vectorized arguments in the case of mapply). The 'multiApply' package extends this paradigm to functions taking a list of multiple unidimensional or multidimensional arguments (or combinations thereof) as input, which can have different numbers of dimensions as well as different dimension lengths.
Imports: abind, plyr, doParallel, future, foreach

Imports: abind, doParallel, foreach, plyr

Title: Apply Functions to Multiple Multidimensional Arrays or Vectors
person("Nuria", "Perez", , "nuria.perez@bsc.es", role = "cre"))
Description: The base apply function and its variants, as well as the related
functions in the 'plyr' package, typically apply user-defined functions to a
single argument (or a list of vectorized arguments in the case of mapply). The
'multiApply' package extends this paradigm with its only function, Apply, which
efficiently applies functions taking one or a list of multiple unidimensional
or multidimensional numeric arrays (or combinations thereof) as input. The input
arrays can have different numbers of dimensions as well as different dimension
lengths, and the applied function can return one or a list of unidimensional or
multidimensional arrays as output. This saves development time by preventing the
R user from writing often error-prone and memory-inefficient loops dealing with
multiple complex arrays. Also, a remarkable feature of Apply is the transparent
use of multi-core through its parameter 'ncores'. In contrast to the base apply
function, this package suggests the use of 'target dimensions' as opposite
to the 'margins' for specifying the dimensions relevant to the function to be