# designUniformRandom: Uniform Design Generator In SPOT: Sequential Parameter Optimization Toolbox

 designUniformRandom R Documentation

## Uniform Design Generator

### Description

Create a simple experimental design based on uniform random sampling.

### Usage

```designUniformRandom(x = NULL, lower, upper, control = list())
```

### Arguments

 `x` optional data.frame x to be part of the design `lower` vector with lower boundary of the design variables (in case of categorical parameters, please map the respective factor to a set of contiguous integers, e.g., with lower = 1 and upper = number of levels) `upper` vector with upper boundary of the design variables (in case of categorical parameters, please map the respective factor to a set of contiguous integers, e.g., with lower = 1 and upper = number of levels) `control` list of controls: `size` number of design points `types` this specifies the data type for each design parameter, as a vector of either "numeric","integer","factor". (here, this only affects rounding) `replicates` integer for replications of each design point. E.g., if replications is two, every design point will occur twice in the resulting matrix.

### Value

matrix `design`
- `design` has `length(lower)` columns and `(size + nrow(x))*control\$replicates` rows. All values should be within `lower <= design <= upper`

### Examples

```set.seed(1) #set RNG seed to make examples reproducible
design <- designUniformRandom(,1,2) #simple, 1-D case
design
design <- designUniformRandom(,1,2,control=list(replicates=3)) #with replications
design
design <- designUniformRandom(,c(-1,-2,1,0),c(1,4,9,1),
control=list(size=5, types=c("numeric","integer","factor","factor")))
design
x <- designUniformRandom(,c(1,-10),c(2,10),control=list(size=5))
x2 <- designUniformRandom(x,c(1,-10),c(2,10),control=list(size=5))
plot(x2)
points(x, pch=19)
```

SPOT documentation built on June 26, 2022, 1:06 a.m.