Title: Interactive model exploration using GGobi
Description: Exploratory model analysis.  Fit and graphical explore ensembles of linear models.
Packaged: Wed Feb 25 07:12:21 2009; hadley

Depends: rggobi, ggplot, reshape, leaps, MASS
Packaged: Wed Feb 28 08:56:42 2007; hadley

Description: Exploratory model analysis.  Fit and graphical explore
Collate: 'ensemble.r' 'generate.r' 'ggobi.r' 'meifly.r' 'summarise.r'

Title: Interactive Model Exploration using 'GGobi'
Description: Exploratory model analysis with <http://ggobi.org>.
Fit and graphical explore ensembles of linear models.
Packaged: 2022-05-20 16:23:54 UTC; hadleywickham

Description: Exploratory model analysis.  Fit and graphical

Title: Variable Width Bar Charts: Bar Mekko
person("Eric", "Rynerson", email = "eric.rynerson@gmail.com", role = c("cre", "aut")),
person("Julius", "Vainora", role = "ctb"))
Description: Create variable width bar charts i.e.
"bar mekko" charts to include important quantitative context.
Closely related to mosaic, spine (or spinogram), matrix,
submarine, olympic, Mondrian or product plots and tree maps.

Package: melody
Version: 0.4.3
Date: 2012-12-29
Title: Statistical Methods for the Quantitative Analysis of Song
Spectrograms
Author: David M. Schruth <dschruth@u.washington.edu>
Maintainer: David M. Schruth <dschruth@u.washington.edu>
Depends: R (>= 1.8.0), caroline, network, sna, methods
Suggests: abind
Description: The melody package is a suite of computer vision tools for
processing vocal spectrograms.  In addition to temporal
partitioning, unit filtering, harmonic splitting, and
background noise removal functionality, the package provides a
collection of methods for assessing the higher order melodic
content of vocalization spectrograms. Both unit level (tone and
interval) as well as inter-unit measures (syllabic variation
and repetition clustering) are also currently available.
License: Artistic-2.0
LazyLoad: yes
Packaged: 2012-12-29 18:32:23 UTC; dave
Repository: CRAN
Date/Publication: 2012-12-29 20:14:39

Title: Multiple Empirical Likelihood Tests
Description: Multiple hypothesis testing via empirical likelihood in general
block designs. It provides asymptotic generalized family-wise
Authors@R: person("Eunseop", "Kim", email = "kim.7302@osu.edu", role = c("aut", "cre"))