Package: modehunt
Type: Package
Title: Multiscale Analysis for Density Functions
Version: 1.0.5
Date: 2010-08-30
Author: Kaspar Rufibach <kaspar.rufibach@ifspm.uzh.ch> and Guenther
Walther <gwalther@stanford.edu>
Maintainer: Kaspar Rufibach <kaspar.rufibach@ifspm.uzh.ch>
Description: Given independent and identically distributed observations
X(1), ..., X(n) from a density f, this package provides five
methods to perform a multiscale analysis about f as well as the
necessary critical values. The first method, introduced in
Duembgen and Walther (2008), provides simultaneous confidence
statements for the existence and location of local increases
(or decreases) of f, based on all intervals I(all) spanned by
any two observations X(j), X(k). The second method approximates
the latter approach by using only a subset of I(all) and is
therefore computationally much more efficient, but
asymptotically equivalent. Omitting the additive correction
term Gamma in either method offers another two approaches which
are more powerful on small scales and less powerful on large
scales, however, not asymptotically minimax optimal anymore.
Finally, the block procedure is a compromise between adding
Gamma or not, having intermediate power properties. The latter
is again asymptotically equivalent to the first and was
introduced in Rufibach and Walther (2010).
License: GPL (>= 2)
URL: http://www.biostat.uzh.ch/aboutus/people/rufibach.html,
http://www-stat.stanford.edu/~gwalther
Packaged: 2010-08-31 06:01:28 UTC; rufibach
Repository: CRAN
Date/Publication: 2010-08-31 08:14:45

Package: modehunt
Type: Package
Title: Multiscale Analysis for Density Functions
Version: 1.0.6
Date: 201-11-29
Author: Kaspar Rufibach <kaspar.rufibach@gmail.com> and Guenther Walther <gwalther@stanford.edu>
Maintainer: Kaspar Rufibach <kaspar.rufibach@gmail.com>
Description: Given independent and identically distributed observations X(1), ..., X(n) from a density f,
this package provides five methods to perform a multiscale analysis about f as well as the necessary critical
values. The first method, introduced in Duembgen and Walther (2008), provides simultaneous confidence statements
for the existence and location of local increases (or decreases) of f, based on all intervals I(all) spanned by
any two observations X(j), X(k). The second method approximates the latter approach by using only a subset of
I(all) and is therefore computationally much more efficient, but asymptotically equivalent. Omitting the additive
correction term Gamma in either method offers another two approaches which are more powerful on small scales and
less powerful on large scales, however, not asymptotically minimax optimal anymore. Finally, the block procedure is a
compromise between adding Gamma or not, having intermediate power properties. The latter is again asymptotically
equivalent to the first and was introduced in Rufibach and Walther (2010).
License: GPL (>= 2)
URL: http://www.kasparrufibach.ch,
http://www-stat.stanford.edu/~gwalther
Packaged: 2011-11-29 06:07:40 UTC; rufibach
Repository: CRAN
Date/Publication: 2011-11-29 07:02:10