raster, gridBase, viridis, png, sp, geometry, reproj (>=
0.4.0), scales
datasets, knitr, rmarkdown, palr, rgl, testthat (>= 2.1.0),
ncdf4, covr, proj4

raster, gridBase, viridis, png, sp, geometry, reproj (>=
0.4.0), scales, palr

raster, gridBase, png, sp, geometry, reproj (>= 0.4.0),
scales, palr

S original by Berwin A. Turlach <berwin.turlach@anu.edu.au>
R port by Andreas Weingessel <Andreas.Weingessel@ci.tuwien.ac.at>
This package contains routines and documentation for
solving quadratic programming problems.

Functions to solve Quadratic Programming Problems.

S original by Berwin A. Turlach <berwin.turlach@anu.edu.au> R
port by Andreas Weingessel <Andreas.Weingessel@ci.tuwien.ac.at>

S original by Berwin A. Turlach <Berwin.Turlach@gmail.com> R
port by Andreas Weingessel <Andreas.Weingessel@ci.tuwien.ac.at>

Functions to Solve Quadratic Programming Problems

S original by Berwin A. Turlach <Berwin.Turlach@gmail.com>
R port by Andreas Weingessel <Andreas.Weingessel@ci.tuwien.ac.at>
Fortran contributions from Cleve Moler (dposl/LINPACK and
(a modified version of) dpodi/LINPACK)

Quadratic Programming with Absolute Value Constraints
person("Bob", "Harlow", email = "rharlow86@gmail.com",role = c("aut", "cre"))
Extends the quadprog package to solve quadratic programs with
absolute value constraints and absolute values in the objective function.

Visualizing the SD using a Quadratic Curve
Given a dataset, the user is invited to utilize the Empirical Cumulative Distribution Function (ECDF)
to guess interactively the mean and the mean deviation. Thereafter,
using the quadratic curve the user can guess the Root Mean Squared Deviation (RMSD)
and visualize the standard deviation (SD).
For details, see Sarkar and Rashid (2019)<doi:10.3126/njs.v3i0.25574>,
Have You Seen the Standard Deviaton?, Nepalese Journal of Statistics, Vol. 3, 1-10.

Sparsity by Worst-Case Quadratic Penalties
This package fits classical sparse regression models with
efficient active set algorithms by solving quadratic problems.
Also provides a few methods for model selection purpose
(cross-validation, stability selection).
Rcpp, RcppArmadillo, reshape2, scales, grid, parallel
'init.R' 'quadrupen-package.R' 'quadrupen-class.R'
'elastic_net.R' 'crossval-class.R' 'crossval.R'
'stability-class.R' 'stability.R'