robust.boot {GeneTS} | R Documentation |

## Robust Error Resistant Bootstrap Algorithm

### Description

`robust.boot`

generates ordinary nonparametric bootstrap replicates. If an error occurs during the
function evaluation (e.g., due to numerical problems) the bootstrap draw is repeated.

`robust.boot`

offers only very limited bootstrap support, for much more advanced bootstrapping methods
use `boot`

.

### Usage

robust.boot(data, statistic, R)

### Arguments

`data` |
data matrix or data frame (each row is considered as one multivariate observation) |

`statistic` |
A function which when applied to data returns a vector
containing the statistic(s) of interest |

`R` |
number of bootstrap replicates |

### Details

`robust.boot`

is used in the functions `bagged.cov`

, `bagged.cov`

,
and `bagged.pcor`

.

### Value

A list with one component:

`t` |
a matrix with 'R' rows each of which is a bootstrap replicate of 'statistic'. |

### Author(s)

Korbinian Strimmer (http://www.stat.uni-muenchen.de/~strimmer/).

### See Also

`boot`

, `bagged.pcor`

.

### Examples

# load GeneTS library
library(GeneTS)
# small example data set
data(caulobacter)
dat <- caulobacter[,1:15]
dim(dat)
# test statistic: vector of means
test.fun <- function(data, i)
{
res <- apply(data[i,], 2, mean)
if (runif(1) < .01) stop("Error!") # in 1 percent of cases an error occurs ...
return(res)
}
# perform bootstrap
b.out <- robust.boot(dat, test.fun, 1000)
# despite the errors bootstrapping has finished
dim(b.out$t)
# bootstrap means
bag <- apply(b.out$t, 2, mean)
bag

[Package

*GeneTS* version 2.3

Index]