plgp (version 1.0)

addpall.GP: Add data to pall

Description

Add sufficient data common to all particles to the global pall variable, a mnemonic for particles-all, for Gaussian process (GP) regression, classification, or combined unknown constraint models

Usage

addpall.GP(Z)
addpall.CGP(Z)
addpall.ConstGP(Z)

Arguments

Z

new observation(s) (usually the next one in time) to add to the pall global variable

Value

• nothing is returned, but global variables are modified

Details

All three functions add new Z$x to pall$X; addpall.GP also adds Z$y to pall$Y, addpall.CGP also adds Z$c to pall$Y, and addpall.ConstGP does both

References

Gramacy, R. and Polson, N. (2010). Particle learning of Gaussian process models for sequential design and optimization. Tech. Rep. arXiv:0909.5262, University of Cambridge.

Gramacy, R. and Lee, H. (2010). Optimization under unknown constraints. Bayesian Statistics 9, J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West (Eds.); Oxford University Press

http://www.statslab.cam.ac.uk/~bobby/plgp.html

See Also

PL

Examples

## See the demos via demo(package="plgp") and the examples
## section of ?plgp