Depends: R (>= 3.5.0), spatstat.random (>= 2.1.0), spatstat.core (>=

Depends: R (>= 3.5.0), spatstat.random (>= 2.1.0), spatstat.explore (>=

Title: Objective functions for benchmarking the performance of global
Description: This package makes available 50 objective functions for benchmarking the performance of global optimization algorithms based on C functions described in M. Montaz Ali, Charoenchai Khompatraporn and Zelda B. Zabinsky, Journal of Global Optimization, 2005, vol. 31, 4, 635-672.

Description: This package makes available 50 objective functions for benchmarking the performance of global optimization algorithms

Title: Testing the additional predictive value of high-dimensional data
Depends: R (>= 2.8), mboost (>= 2.0-0), survival
Description: 'globalboosttest' implements a permutation-based testing
procedure to globally test the (additional) predictive value of
a large set of predictors given that a small set of predictors
is already available. Currently, 'globalboosttest' supports
binary outcomes (via logistic regression) and survival outcomes
(via Cox regression). It is based on boosting regression as

Title: Identify Global Objects in R Expressions
Description: Identifies global ("unknown" or "free") objects in R expressions
by code inspection using various strategies, e.g. conservative or liberal.
The objective of this package is to make it as simple as possible to
identify global objects for the purpose of exporting them in distributed

by code inspection using various strategies (ordered, liberal, or
conservative).  The objective of this package is to make it as simple as
possible to identify global objects for the purpose of exporting them in

Description: Identifies global ("unknown") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal.  The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.

Description: Identifies global ("unknown") objects in R expressions by code
inspection using various strategies, e.g. conservative or liberal. The objective
of this package is to make it as simple as possible to identify global objects
for the purpose of exporting them in distributed compute environments.