Package: LPmerge
Title: Merging linkage maps by linear programming
Version: 1.6
Author: Jeffrey Endelman
Maintainer: Jeffrey Endelman <endelman@wisc.edu>
Description: LPmerge creates a consensus genetic map by merging linkage maps from different populations. The software uses linear programming (LP) to efficiently minimize the mean absolute error between the consensus map and the linkage maps. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts.
Depends: Rglpk, Matrix
License: GPL-3
URL: http://potatobreeding.cals.wisc.edu/software
Packaged: 2014-08-16 21:03:44 UTC; endelman
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-08-17 01:14:04
Package: designmatch
Type: Package
Title: Construction of Optimally Matched Samples for Randomized
Experiments and Observational Studies that are Balanced by
Design
Version: 0.1.1
Date: 2016-02-14
Author: Jose R. Zubizarreta <zubizarreta@columbia.edu>, Cinar Kilcioglu <ckilcioglu16@gsb.columbia.edu>
Maintainer: Jose R. Zubizarreta <zubizarreta@columbia.edu>
Depends: R (>= 3.2), lattice, MASS, slam, Rglpk
Suggests: gurobi, Rcplex, Rsymphony
SystemRequirements: GLPK library package (e.g., libglpk-dev on
Debian/Ubuntu)
License: GPL-2 | GPL-3
Description: Includes functions for the construction of matched samples that are balanced by design. Among others, these functions can be used for matching in observational studies with treated and control units, with cases and controls, in related settings with instrumental variables, and in discontinuity designs. Also, they can be used for the design of randomized experiments, for example, for matching before randomization. By default, 'designmatch' uses the 'GLPK' optimization solver, but its performance is greatly enhanced by the 'Gurobi' optimization solver and its associated R interface. For their installation, please follow the instructions at http://user.gurobi.com/download/gurobi-optimizer and http://www.gurobi.com/documentation/6.5/refman/r_api_overview.html. We have also included directions in the gurobi_installation file in the inst folder.
NeedsCompilation: no
Packaged: 2016-02-15 20:55:07 UTC; jrz
Repository: CRAN
Date/Publication: 2016-02-15 23:40:25
Package: cosso
Version: 2.1-1
Date: 2013-03-10
Title: Fit Regularized Nonparametric Regression Models Using COSSO
Penalty.
Author: Hao Helen Zhang <hzhang@math.arizona.edu> and Chen-Yen Lin
<clin5@ncsu.edu>
Maintainer: Chen-Yen Lin <clin5@ncsu.edu>
Description: COSSO is a new regularization method that automatically
estimates and selects important function components by a
soft-thresholding penalty in the context of smoothing spline
ANOVA models. Implemented models include mean regression,
quantile regression, logistic regression and the Cox regression
models.
License: GPL (>= 2)
Depends: quadprog, Rglpk, parallel, glmnet
URL: http://www4.stat.ncsu.edu/~hzhang/cosso.html
Packaged: 2013-03-11 01:37:06 UTC; ChenYen
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-03-11 07:44:02
Package: sdcTable
Version: 0.21.5
Date: 2016-05-20
Title: Methods for Statistical Disclosure Control in Tabular Data
Description: Methods for statistical disclosure control in
tabular data such as primary and secondary cell suppression are covered in
this package.
Author: Bernhard Meindl
Maintainer: Bernhard Meindl <bernhard.meindl@statistik.gv.at>
URL: http://www.statistik.at
BugReports: https://github.com/bernhard-da/sdcTable/issues
Depends: stringr, methods, Rcpp (>= 0.11.0), Rglpk, lpSolveAPI
Imports: data.table
Suggests: testthat (>= 0.3)
LazyLoad: yes
LinkingTo: Rcpp
License: GPL (>= 2)
SystemRequirements: GLPK library, including -dev or -devel part
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-05-20 07:23:52 UTC; meindl
Repository: CRAN
Date/Publication: 2016-05-20 11:55:36
providing 
.