This package provides jackknife resampling and estimation functions for Julia.

None of the functions here are exported, so you'll have to call them with the prefix
`Jackknife.`

or explicitly import them.

Each function takes the following two arguments:

A point estimator, given as a

`Function`

. The function must return a scalar when passed a vector.A real-valued vector of length > 1.

```
leaveoneout(estimator, x)
```

Compute a vector of point estimates based on systematic subsamples of `x`

wherein
each index is omitted one at a time.
These are the "leave-one-out" estimates.
The resulting vector will have length `length(x) - 1`

.

```
variance(estimator, x)
```

The variance of the estimator computed using the jackknife technique.

```
bias(estimator, x)
```

The bias of the estimator computed using the jackknife technique.

```
estimate(estimator, x)
```

The bias-corrected jackknife estimate of the parameter.

07/15/2016

about 2 months ago

22 commits