Title: Item Focussed Trees for the Identification of Items in
Depends: penalized, VGAM, grid, gridBase, plotrix
Description: Item focussed recursive partitioning for simultaneous selection of items and variables that induce Differential Item Functioning (DIF) in dichotomous or polytomous items.

Title: Determination of Intervals Using Georeferenced Survey Simulation
Authors@R: c(person("Mark","Hubbe", role = c("aut", "cre"),email = "hubbe.1@osu.edu"),
person("William", "Pestle", role = "aut"))
Description: Simulation tool to estimate the rate of success that surveys possessing user-specific characteristics have in identifying archaeological sites (or any groups of clouds of objects), given specific parameters of survey area, survey methods, and site properties. The survey approach used is largely based on the work of Kintigh (1988) <doi:10.2307/281113>.

Title: DIME (Differential Identification using Mixture Ensemble)
Author: Cenny Taslim <taslim.2@osu.edu>, with contributions from Dustin
Description: A robust differential identification method that considers
an ensemble of finite mixture models combined with a local
false discovery rate (fdr) to analyze ChIP-seq (high-throughput
genomic)data comparing two samples allowing for flexible

Potter, Abbasali Khalili and Shili Lin <shili@stat.osu.edu>.

Author: Cenny Taslim <taslim.2@osu.edu>, with contributions from  Dustin Potter, Abbasali Khalili and Shili Lin <shili@stat.osu.edu>.
Description: A robust differential identification method that considers an ensemble of finite mixture models combined with a local false discovery rate (fdr) to analyze ChIP-seq (high-throughput genomic)data comparing two samples allowing for flexible modeling of data.

Title: Differential Identification using Mixture Ensemble
Description: A robust identification of differential binding sites method for analyzing ChIP-seq (Chromatin Immunoprecipitation Sequencing)
comparing two samples that considers an ensemble of finite mixture models combined with a local false discovery rate (fdr)
allowing for flexible modeling of data. Methods for Differential Identification using Mixture Ensemble (DIME) is described in:
Taslim et al., (2011) <doi:10.1093/bioinformatics/btr165>.