# boot.samples

From InPosition v0.12.7.1
by Derek Beaton

##### Compute indicies for bootstrap resampling.

This function computes a set of indicies for bootstrap resampling. It can be unconstrained or bootstrap within a group design.

- Keywords
- Bootstrap

##### Usage

`boot.samples(DATA, DESIGN = NULL, constrained = FALSE)`

##### Arguments

- DATA
The original data matrix to be bootstrapped. Rows will be bootstrapped and are assumed to be observations.

- DESIGN
A design matrix (in disjunctive coding). Only used if

`constrained`

is TRUE.- constrained
a boolean. If TRUE, bootstrap resampling will occur within groups as designated by the

`DESIGN`

matrix.

##### Value

a set of indicies to be used to be used as the bootstrap resampled indices.

##### See Also

##### Examples

```
# NOT RUN {
data(ep.iris)
unconstrained.indices <- boot.samples(ep.iris$data)
#ep.iris$data[unconstrained.indices,]
constrained.indices <- boot.samples(ep.iris$data,DESIGN=ep.iris$design,constrained=TRUE)
#ep.iris$data[constrained.indices,]
# }
```

*Documentation reproduced from package InPosition, version 0.12.7.1, License: GPL-2*

### Community examples

Looks like there are no examples yet.