person("Jaime", "Mosquera", email = "jmosquerag@unal.edu.co", role = c("aut", "cre"),
person("Freddy", "Hernandez", , "fhernanb@unal.edu.co", role = c("aut"),
estimated with 'numDeriv' Gilbert (2011) <http://CRAN.R-project.org/package=numDeriv>
or the option 'Hessian = TRUE' of 'optim' function.
Author: Jaime Mosquera [aut, cre] (<https://orcid.org/0000-0002-1684-4756>),

Depends: R (>= 3.3.0), DEoptim, boot, numDeriv, BBmisc
Suggests: gamlss.dist, survival, knitr, rmarkdown

Depends: R (>= 3.0.0), DEoptim, survival, stringr, BBmisc
Imports: Rdpack, utils, stats, numDeriv, boot, RCurl, foreign
Suggests: gamlss.dist, knitr, rmarkdown, AdequacyModel
Description: Routines for parameter estimation for any probability density or
mass function implemented in R via maximum likelihood (ML) given a data set.
The main routines 'maxlogL' and 'maxlogLreg' are  wrapper functions specifically
developed for ML estimation. There are included optimization procedures such as
'nlminb' and 'optim' from base package, and 'DEoptim' Mullen (2011)
<doi: 10.18637/jss.v040.i06>. Standard errors are estimated with 'numDeriv'

person("Freddy", "Hernandez", , "fhernanb@unal.edu.co", role = c("ctb"),
Imports: Rdpack, utils, stats, numDeriv, boot, matrixStats, autoimage,
Suggests: gamlss.dist, knitr, rmarkdown, AdequacyModel, readr, covr,

Title: Ethnicity Annotation from Whole Exome Sequencing Data
Description: Reliable and rapid ethnicity annotation from whole exome sequencing data.
Imports: graphics, utils, parallel, grDevices, rgeos (>= 0.3-20),

Imports: graphics, utils, parallel, grDevices, MASS (>= 7.3-47),
geometry (>= 0.3-6), data.table (>= 1.10.0), SNPRelate (>=

Authors@R: c(person("Alessandro", "Romanel", email = "alessandro.romanel@unitn.it",

Title: Ethnicity Annotation from Whole-Exome and Targeted Sequencing
Description: Reliable and rapid ethnicity annotation from whole exome and targeted sequencing data.

Maintainer: Elisa Frutos Bernal <efb@usal.es>
Description: Euclidean maps are graphical representations of the rows
and columns of the matrix Y, by row and column points points
based on the estimated parameters of the multiplicative
interaction model (MI). These graphs represent the Euclidean
space structure of the rows and columns as points of Rp and Rq,
and thus allow diagnosis of the model that best fits the data.