findSubsample {biotools} | R Documentation |

## Finding an Optimized Subsample

### Description

It allows one to find an optimized (minimized or maximized) numeric subsample according to a statistic of interest. For example, it might be of interest to determine a subsample whose standard deviation is the lowest among all of those obtained from all possible subsamples of the same size.

### Usage

```
findSubsample(x, size, fun = sd, minimize = TRUE, niter = 10000)
```

### Arguments

`x` |
a numeric vector. |

`size` |
an integer; the size of the subsample. |

`fun` |
an object of class |

`minimize` |
logical; if TRUE (default) |

`niter` |
an integer indicating the number of iterations, i.e., the number of subsamples to be selected
(without replacement) from the original sample, |

### Value

A list of

`dataname` |
a |

`niter` |
the number of iterations. |

`fun` |
the objective function. |

`stat` |
the achieved statistic for the optimized subsample. |

`criterion` |
a |

`subsample` |
a numeric vector; the optimized subsample. |

`labels` |
a string containg the labels of the subsample values. |

### Author(s)

Anderson Rodrigo da Silva <anderson.agro@hotmail.com>

### See Also

### Examples

```
# Example 1
y <- rnorm(40, 5, 2)
findSubsample(x = y, size = 6)
# Example 2
f <- function(x) diff(range(x)) # max(x) - min(x)
findSubsample(x = y, size = 6, fun = f, minimize = FALSE, niter = 20000)
# End (not run)
```

*biotools*version 4.2 Index]