Title: Fast Spatial Ancestry via Flexible Allele Frequency Surfaces
Author: John Michael O Ranola, John Novembre, and Kenneth Lange
Description: Used primarily for estimates of allele frequency surfaces from point estimates.
It can also place individuals of unknown origin back onto the geographic map with great accuracy.
Additionally, it can place admixed individuals by estimating contributing fractions at each
location on a map. Lastly, it can rank SNPs by their ability to differentiate populations.
See "Fast Spatial Ancestry via Flexible Allele Frequency Surfaces" (John Michael Ranola, John
Novembre, Kenneth Lange) in Bioinformatics 2014 for more info.

Package: OriGen
Type: Package
Title: Fast Spatial Ancestry via Flexible Allele Frequency Surfaces
Version: 1.4.3
Author: John Michael O Ranola, John Novembre, and Kenneth Lange
Depends: maps, ggplot2
Maintainer: John Michael O. Ranola <ranolaj@uw.edu>
Description: Used primarily for estimates of allele frequency surfaces from point estimates.
It can also place individuals of unknown origin back onto the geographic map with great accuracy.
Additionally, it can place admixed individuals by estimating contributing fractions at each
location on a map. Lastly, it can rank SNPs by their ability to differentiate populations.
See "Fast Spatial Ancestry via Flexible Allele Frequency Surfaces" (John Michael Ranola, John
Novembre, Kenneth Lange) in Bioinformatics 2014 for more info.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2016-01-16 07:00:22 UTC; kamicz
Repository: CRAN
Date/Publication: 2016-01-16 09:10:00

Title: Dynamic Panel Models with Orthogonal Reparameterization of Fixed
Authors@R: c(person("Davor", "Cubranic", role = c("aut", "cre"),
person("Paul", "Gustafson", role = "aut",
person("Geoffrey", "Evans", role = "aut",
Description: Implements the orthogonal reparameterization
approach recommended by Lancaster (2002) to estimate dynamic panel
models with fixed effects (and optionally: panel specific
intercepts). The approach uses a likelihood-based estimator and
produces estimates that are asymptotically unbiased as N goes to