plgp: Particle Learning of Gaussian Processes

Sequential Monte Carlo inference for fully Bayesian Gaussian process (GP) regression and classification models by particle learning (PL). The sequential nature of inference and the active learning (AL) hooks provided facilitate thrifty sequential design (by entropy) and optimization (by improvement) for classification and regression models, respectively. This package essentially provides a generic PL interface, and functions (arguments to the interface) which implement the GP models and AL heuristics. Functions for a special, linked, regression/classification GP model and an integrated expected conditional improvement (IECI) statistic is provides for optimization in the presence of unknown constraints. Separable and isotropic Gaussian, and single-index correlation functions are supported. See the examples section of ?plgp and demo(package="plgp") for an index of demos

Install the latest version of this package by entering the following in R:
install.packages("plgp")
AuthorRobert B. Gramacy <rbgramacy@chicagobooth.edu>
Date of publication2014-12-02 00:14:32
MaintainerRobert B. Gramacy <rbgramacy@chicagobooth.edu>
LicenseLGPL
Version1.1-7
http://faculty.chicagobooth.edu/robert.gramacy/plgp.html

View on CRAN

Functions

addpall.CGP Man page
addpall.ConstGP Man page
addpall.GP Man page
alc.adapt Man page
alc.const.adapt Man page
alc.ConstGP Man page
alc.GP Man page
calc2.ktKik.x Man page
calc.alcs Man page
calc.ecis Man page
calc.eis Man page
calc.ents Man page
calc.ieci Man page
calc.iecis Man page
calc.ktKik.x Man page
calc.vars Man page
covar Man page
covar.sep Man page
covar.sim Man page
cv.folds Man page
data.CGP Man page
data.CGP.adapt Man page
data.ConstGP Man page
data.ConstGP.improv Man page
data.GP Man page
data.GP.improv Man page
dist2covar.symm Man page
distance Man page
draw.CGP Man page
draw.ConstGP Man page
draw.GP Man page
EI Man page
ei.adapt Man page
entropy Man page
entropy.adapt Man page
entropy.bvsb Man page
exp2d.C Man page
findmin.ConstGP Man page
findmin.GP Man page
getmap.CGP Man page
getmap.GP Man page
hist.particle.params Man page
ieci.adapt Man page
ieci.const.adapt Man page
ieci.ConstGP Man page
ieci.GP Man page
init.CGP Man page
init.ConstGP Man page
init.GP Man page
latents.CGP Man page
lpost.GP Man page
lpredprob.CGP Man page
lpredprob.ConstGP Man page
lpredprob.GP Man page
mindist.adapt Man page
mvnorm.propose.rw Man page
papply Man page
params.CGP Man page
params.ConstGP Man page
params.GP Man page
phist Man page
PL Man page
PL.clear Man page
PL.env Man page
plgp Man page
plgp-package Man page
pred.CGP Man page
pred.ConstGP Man page
pred.GP Man page
pred.mean.GP Man page
prior.CGP Man page
prior.ConstGP Man page
prior.GP Man page
propagate.CGP Man page
propagate.ConstGP Man page
propagate.GP Man page
rectscale Man page
rectunscale Man page
renorm.lweights Man page
renorm.weights Man page
resample Man page
tquants Man page
unif.propose.pos Man page
updat.GP Man page
util.GP Man page
var.adapt Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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