Rcpp (>= 0.12.4), randtoolbox, DiceDesign, MaxPro, doParallel,
doSNOW, gtools, nloptr, foreach, jpeg, gmp, conf.design, pdist,
DoE.base, FrF2, geometry

A binding to the minimist JavaScript library. This module implements
the guts of optimist's argument parser without all the fanciful decoration.

c(
person("Hannes", "M\u00fchleisen", role = c("aut", "cre"), email = "hannes@cwi.nl", comment = c(ORCID = "0000-0001-8552-0029")),
person("Google Inc.", role = "cph"),
person("Apache Software Foundation", role = "cph"),
person("Daniel", "Lemire", role = "cph"),
person("Chad", "Walters", role = "cph"))
Self-sufficient reader for a subset of Parquet files. Nested tables, compression besides Snappy and encryption are not supported.
Hannes Mühleisen [aut, cre] (<https://orcid.org/0000-0001-8552-0029>),
Google Inc. [cph],
Apache Software Foundation [cph],
Daniel Lemire [cph],
Chad Walters [cph]

R Interface to the Levenberg-Marquardt Nonlinear Least-Squares
Algorithm Found in MINPACK, Plus Support for Bounds
Timur V. Elzhov, Katharine M. Mullen, Andrej-Nikolai Spiess, Ben Bolker
The nls.lm function provides an R interface to lmder and lmdif from the MINPACK library, for solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support for lower and upper parameter bounds.  The implementation can be used via nls-like calls using the nlsLM function.

Derivative-free optimization algorithms by quadratic
approximation
Douglas Bates, Katharine M. Mullen, John C. Nash, Ravi Varadhan
Derivative-free optimization by quadratic approximation
based on an interface to Fortran implementations by M. J. D.
Powell

Katharine M. Mullen, John C. Nash, Ravi Varadhan

Derivative-free optimization by quadratic approximation
based on an interface to Fortran implementations by M. J. D.
Powell.

Derivative-Free Optimization Algorithms by Quadratic
Approximation

An R Package for Linear Mixed Model Analyses
This package offers three important components: (1) to construct a use-defined linear mixed model, (2) to employ one of linear mixed model approaches: minimum norm quadratic unbiased estimation (MINQUE) (Rao, 1971) for variance component estimation and random effect prediction; and (3) to employ a jackknife resampling technique to conduct various statistical tests. In addition, this package provides the function for model or data evaluations.This R package offers fast computations for large data sets analyses for various irregular data structures.