Learn R Programming

blackbox (version 1.1.54)

Black Box Optimization and Exploration of Parameter Space

Description

Performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. Includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (Rousset and Leblois, 2012 ; Leblois et al., 2014 ; and see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary Kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross-validation.

Copy Link

Version

Install

install.packages('blackbox')

Monthly Downloads

2,913

Version

1.1.54

License

CeCILL-2

Maintainer

Franois Rousset

Last Published

March 1st, 2026

Functions in blackbox (1.1.54)

sampleByResp

Sample predictor points according to predicted response
saveOldFile

Save a copy of an existing file.
maximizeOK

Find maximum of predicted response surface
options

blackbox options settings
islogscale

Test for parameter log scale
init_grid

Define starting points in parameter space.
calc1DCIs

Compute 1D confidence intervals
calcPredictorOK

Generate smoothing predictor given smoothing parameters
calcLRTs

Compute (profile) likelihood ratio tests
calcGCV

Estimate smoothing parameters by generalized cross-validation (GCV)
blackbox

Black box optimization and response surface exploration
buildFONKgpointls

Prepare data for smoothing
buildPointls

Read a data file
calc1Dprofiles

One and two-dimensional profiles, and surface plots
prepareData

Prepare data and controls for smoothing
preprocessbboptions

Set controls for most functiosn in the package
ordinary-internal

Internal ordinary Functions
writeFinalInfo

Pretty output, and management of output files
bboptim

Black-box function optimization