Penalized Generalized Estimating Equations in High-Dimension
Gul Inan (Visiting scholar, University of Minnesota), Jianhui Zhou (Associate Professor, University of Virginia) and Lan Wang (Professor, University of Minnesota)
Fits penalized generalized estimating equations to longitudinal data with high-dimensional covariates.

Gul Inan (Lecturer, Middle East Technical University), Jianhui Zhou (Associate Professor, University of Virginia) and Lan Wang (Professor, University of Minnesota)

Shaojie Chen; Lei Huang; Huitong Qiu; Ani Eloyan; Brian Caffo; Ciprian Crainiceanu
A Group ICA Algorithm that can run in parallel on an SGE platform or multi-core PCs

Nested Resolvable Designs and their Associated Uniform Designs
Mohamed Laib, Abla Boudraa and Zebida Gheribi-Aoulmi
Construction method of nested resolvable designs from
a projective geometry defined on Galois field of order 2. The obtained
Resolvable designs are used to build uniform design. The presented results
are based on <https://eudml.org/doc/219563> and A. Boudraa et al. (See references).

Recursive method for construction of nested resolvable designs
and uniform designs associated
Mohamed LAIB, Abla BOUDRAA and Zoubida Gheribi-Aoulmi
Construction of balanced incomplete binary blocks designs (BIB) from a projective geometry defined on a Galois fields order 2, using to extract the RBIBD & the uniforms designs associated.

Discover Probable Duplicates in Plant Genetic Resources
Collections
c(
person(c("J.", "Aravind"),
email = "aravindj@nbpgr.ernet.in",
role = c("aut", "cre")),
person(c("J.", "Radhamani"),
email = "radhamani@nbpgr.ernet.in", role = "aut"),
person(c("Kalyani", "Srinivasan"),
email = "kalyani@nbpgr.ernet.in", role = "aut"),
person(c("B.", "Ananda", "Subhash"),
email = "anandasubhash@gmail.com", role = "aut"),
person(c("R.", "K.", "Tyagi"),
email = "rktyagi@nbpgr.ernet.in", role = "aut"))
Provides functions to aid the identification of probable/possible
duplicates in Plant Genetic Resources (PGR) collections using
'passport databases' comprising of information records of each constituent
sample. These include methods for cleaning the data, creation of a
searchable Key Word in Context (KWIC) index of keywords associated with
sample records and the identification of nearly identical records with
similar information by fuzzy, phonetic and semantic matching of keywords.
data.table (>= 1.9.3), igraph, stringdist (>= 0.5), stringi,
methods, utils, stats
J. Aravind [aut, cre],
J. Radhamani [aut],
Kalyani Srinivasan [aut],
B. Ananda Subhash [aut],
R. K. Tyagi [aut]