Collate: 'calculate.r' 'divide.r' 'labels.r' 'margin.r' 'parse.r'
'partition.r' 'plot.r' 'productplots.r' 'templates.r' 'utils.r'

Title: An Alternative Display Profiling Data as Tree Structure
Description: An alternative data structure for the profiling information

Title: Compute and Visualize Profile Extrema Functions
Authors@R: person("Dario","Azzimonti",role=c("aut","cre","cph"),email= "dario.azzimonti@gmail.com", comment = c(ORCID = "0000-0001-5080-3061"))
Description: Computes profile extrema functions for arbitrary functions. If the function is expensive-to-evaluate it computes profile extrema by emulating the function with a Gaussian process (using package 'DiceKriging'). In this case uncertainty quantification on the profile extrema can also be computed. The different plotting functions for profile extrema give the user a tool to better locate excursion sets.
Depends: R (>= 2.10), DiceKriging, KrigInv, pGPx
Imports: microbenchmark, quantreg, lhs, splines, methods, RColorBrewer,

Title: Implements profile analysis described in Davison & Davenport
Maintainer: Christopher David Desjardins <cddesjardins@gmail.com>
Description: Decomposes the level and pattern effects from a profile and implements the cross-validation technique described in Davison & Davenport (2002)

Description: Decomposes the level and pattern effects from a profile
and implements the cross-validation technique described in

Title: Profile Dirichlet Process Mixtures
Description: This package performs profile inference for models
utilizing the Dirichlet process (DP) and Dirichlet motivated
process (DMP) mixtures. This method is not based on Markov
chain Monte Carlo methods, as are most other mechanisms of
inference in DP and DMP mixtures. This method searches for the
maximum posterior (MAP) estimate for the cluster indicators in

Description: This package facilitates profile inference (inference at
the posterior mode) for a class of product partition models
(PPM). The Dirichlet process mixture is a specific case in this
class and is selected by default. These methods search for the
maximum posterior (MAP) estimate for the cluster partition in