Title: Heller-Heller-Gorfine Tests of Independence and Equality of
Author: Barak Brill & Shachar Kaufman, based in part on an earlier implementation by Ruth Heller and Yair Heller.
Description: Heller-Heller-Gorfine (HHG) tests are a set of powerful statistical tests of multivariate k-sample homogeneity and independence. For the univariate case, the package also offers implementations of the MinP DDP and MinP ADP tests, which are consistent against all continuous alternatives but are distribution-free, and are thus much faster to apply.

Author: Barak Brill & Shachar Kaufman, based in part on an earlier
implementation by Ruth Heller and Yair Heller.
Description: Heller-Heller-Gorfine ('HHG') tests are a set of powerful statistical
tests of multivariate k-sample homogeneity and independence. For the univariate
case, the package also offers implementations of the 'MinP DDP' and 'MinP ADP'
tests, which are consistent against all continuous alternatives but are
distribution-free, and are thus much faster to apply.

Description: Heller-Heller-Gorfine tests are a set of powerful statistical
tests of multivariate k-sample homogeneity and independence (Heller et. al., 2013, <doi:10.1093/biomet/ass070>). For the univariate
tests by Heller et. al. (2016), which are consistent against all continuous alternatives but are

Package: HI
Title: Simulation from distributions supported by nested hyperplanes
Version: 0.1-1
Date: 2005-04-29
Author: Giovanni Petris <GPetris@Uark.edu> and
Luca Tardella <luca.tardella@@uniroma1.it>; original C code
for ARMS by Wally Gilks.
Maintainer: ORPHANED
Depends: R (>= 1.7.0)
Description: Simulation from distributions supported by nested hyperplanes,
using the algorithm described in Petris & Tardella, "A geometric approach to
transdimensional Markov chain Monte Carlo", Canadian Journal of Statistics,
v.31, n.4, (2003).
Also random direction multivariate Adaptive Rejection Metropolis Sampling.
License: GPL version 2 or newer
Packaged: Fri Apr 29 16:07:43 2005; hornik

Package: HI
Title: Simulation from distributions supported by nested hyperplanes
Version: 0.2
Date: 2006-01-10
Author: Giovanni Petris <GPetris@Uark.edu> and
Luca Tardella <luca.tardella@@uniroma1.it>; original C code
for ARMS by Wally Gilks.
Maintainer: Giovanni Petris <GPetris@Uark.edu>
Depends: R (>= 1.7.0)
Description: Simulation from distributions supported by nested hyperplanes,
using the algorithm described in Petris & Tardella, "A geometric approach to
transdimensional Markov chain Monte Carlo", Canadian Journal of Statistics,
v.31, n.4, (2003).
Also random direction multivariate Adaptive Rejection Metropolis Sampling.
License: GPL version 2 or newer
Packaged: Tue Jan 10 11:11:49 2006; gpetris