plt.2d.surf.with.batch: Visualize 2D emulator + stopping region + batch amounts

In mludkov/mlOSP: Machine Learning and Regression Monte Carlo Algorithms for Optimal Stopping

Visualize 2D emulator + stopping region + batch amounts

Description

two-dimensional image+contour plot with replication counts for an osp.seq.batch.design fit

Usage

plt.2d.surf.with.batch(
  fit,
  batch_size,
  x = seq(25, 50, len = 201),
  y = seq(25, 50, len = 201),
  contour.col = "red",
  rep.limits = c(20, 100)
)

Arguments

fit	An emulator object. Can be any of the types supported by forward.sim.policy
batch_size	array of replication counts for each input generated by osp.seq.batch.design
x, y	locations to use for the predict() functions. Default is a 200x200 fine grid. Passed to expand.grid
contour.col	(default is "red") – color of the zero contour
rep.limits	(default is c(20,100)) – range of the legend for the replication counts

Author(s)

Xiong Lyu

Examples

sob30 <- randtoolbox::sobol(55, d=2)  # construct a space-filling initial design
sob30 <- sob30[ which( sob30[,1] + sob30[,2] <= 1) ,]  
sob30 <- 25+30*sob30 
model2d <- list(x0 = rep(40,2),K=40,sigma=rep(0.2,2),r=0.06,
 div=0,T=1,dt=0.04,dim=2,sim.func=sim.gbm, 
 payoff.func=put.payoff, look.ahead=1, pilot.nsims=1000,
 cand.len=1000,max.lengthscale=c(40,40),min.lengthscale=c(3,3),
 seq.design.size=50,batch.nrep=25,total.budget=1000,init.size=30,
 init.grid=sob30, kernel.family="gauss",update.freq=5,
 r.cand=c(20, 30,40,50,60, 80, 120, 160))
set.seed(11)
require(tgp)
require(DiceKriging)
require(laGP)
require(ks)
require(RColorBrewer)
require(scales)
model2d$batch.heuristic <- 'adsa'
model2d$ei.func <- 'amcu'
oos.obj.adsa <- osp.seq.batch.design(model2d,method="trainkm")
plt.2d.surf.with.batch(oos.obj.adsa$fit[[15]], 
                     oos.obj.adsa$batches[1:oos.obj.adsa$ndesigns[15] - 1, 15])

mludkov/mlOSP documentation built on April 29, 2023, 7:56 p.m.