sim.dpp.modal.seq {demu} | R Documentation |

## Draw sequential samples from the conditional DPP given previously sampled points already in the design.

### Description

`sim.dpp.modal.seq()`

is similar to `sim.dpp.modal`

but sequentially selects `n`

additional points to
add to the design given that the points in `curpts`

are alread in the design from previous sequential
iterations. It implements the DPP-based design emulator of Pratola et al. (2018) to draw a sequential
sample of `n`

-run additional optimal design points for a Gaussian process
regression model
with correlation function `r(x,x^\prime)`

, where the entries of `R`

are formed by evaluating
`r(x,x^\prime)`

over a grid of candidate locations. As is typical, `R`

is formed based on
*all* of the candidate grid points.

### Usage

```
sim.dpp.modal.seq(curpts, R, n)
```

### Arguments

`curpts` |
A vector of indices to the candidate points that already appear in the design. |

`R` |
A correlation matrix evaluated over a grid of candidate design sites. |

`n` |
Size of the design to sample. |

### Details

For more details on the method, see Pratola et al. (2018). Detailed examples demonstrating the method are available at http://www.matthewpratola.com/software.

### Value

A vector of indices to add to the existing design sites.

### References

Pratola, Matthew T., Lin, C. Devon, and Craigmile, Peter. (2018)
Optimal Design Emulators: A Point Process Approach.
*arXiv:1804.02089*.

### See Also

`demu-package`

`sim.dpp.modal`

`sim.dpp.modal.fast`

### Examples

```
library(demu)
n1=3
n2=3
n3=3
rho=rep(1e-10,2)
ngrid=10
x=seq(0,1,length=ngrid)
X=as.matrix(expand.grid(x,x))
l.d=makedistlist(X)
# Initial design
R=rhomat(l.d,rho)$R
pts.1=sim.dpp.modal(R,n1)
pts.1.proj=remove.projections(pts.1,X)
# Next sequential step, removing projections
pts.2=sim.dpp.modal.seq(pts.1.proj$allpts,R,n2)
design=c(pts.1,pts.2$pts.new)
pts.2.proj=remove.projections(design,X)
# Next sequential step, removing projections
pts.3=sim.dpp.modal.seq(pts.2.proj$allpts,R,n3)
design=c(design,pts.3$pts.new)
# Or, starting with the initial design, don't remove projections
pts.2=sim.dpp.modal.seq(pts.1,R,n2)
designB=c(pts.1,pts.2$pts.new)
pts.3=sim.dpp.modal.seq(designB,R,n3)
designB=c(designB,pts.3$pts.new)
# Plot the result:
#par(mfrow=c(1,3))
#plot(X,xlim=c(0,1),ylim=c(0,1),main="Initial Design")
#points(X[pts.1,],pch=20,cex=2)
#
#plot(X,xlim=c(0,1),ylim=c(0,1),main="+3x2 remove projections")
#points(X[design,],pch=20,cex=2)
#
#plot(X,xlim=c(0,1),ylim=c(0,1),main="+3x2 not removing projections")
#points(X[designB,],pch=20,cex=2)
```

*demu*version 0.3.0 Index]