H1.toy {calibrator} | R Documentation |
Applies basis functions to rows of D1
and D2
H1.toy(D1)
H2.toy(D2)
D1 |
Matrix of code run points |
D2 |
Matrix of observation points |
Returns a matrix whose rows are the basis functions of the code run
points or observation points. Function H1.toy()
operates on
datasets like D1.toy
(latlong and parameters) and function
H2.toy()
operates on datasets like D2.toy
(latlong only)
See package goldstein for a less trivial example of h()
.
Robin K. S. Hankin
M. C. Kennedy and A. O'Hagan 2001. Bayesian calibration of computer models. Journal of the Royal Statistical Society B, 63(3) pp425-464
M. C. Kennedy and A. O'Hagan 2001. Supplementary details on Bayesian calibration of computer models, Internal report, University of Sheffield. Available at http://www.tonyohagan.co.uk/academic/ps/calsup.ps
R. K. S. Hankin 2005. Introducing BACCO, an R bundle for Bayesian analysis of computer code output, Journal of Statistical Software, 14(16)
data(toys)
jj <- extractor.toy(D1.toy)
x.star.toy <- jj$x.star
t.vec.toy <- jj$t.vec
H1.toy(D1=D1.toy)
H1.toy(D1.toy[1,,drop=FALSE])
H1.toy(D1.fun(x.star.toy , theta.toy)[1,,drop=FALSE])
H1.toy(D1.fun(x.star=x.toy,t.vec=theta.toy))
H1.toy(D1.fun(x.star=x.star.toy[1,],t.vec=t.vec.toy[1,]))
H1.toy(D1.fun(x.star=x.star.toy[1,],t.vec=t.vec.toy[1:2,]))
H2.toy(D2.toy)
H2.toy(t(x.toy))