## Re-exports

`pub use percentile::percentile_rand;`

`percentile-rand`

`pub use percentile::median;`

`pub use percentile::percentile;`

`pub use percentile::Fraction;`

`pub use regression::best_fit_ols as regression_best_fit;`

`ols`

`pub use regression::Determination;`

`pub use regression::Predictive;`

## Modules

- Percentile / median calculations.
- regression
`regression`

Various regression models to fit the best line to your data. All written to be understandable.

## Structs

- A list of clusters.
- Owned variant of
`ClusterList`

. Use`Self::borrow`

to get a`ClusterList`

. The inner slice is accessible through the`Deref`

and`DerefMut`

, which means you can use this as a mutable slice. - Returned from
`percentiles_cluster`

and similar functions. - Returned from
`standard_deviation`

and similar functions.

## Traits

- Helper-trait for types used by
`mean`

. - Helper-trait for types used by
`standard_deviation`

.

## Functions

- Mean of
`values`

. - Mean of clustered
`values`

. - Get a collection of percentiles from
`values`

. - Get the standard deviation of
`values`

. The mean is also returned from this, because it’s required to compute the standard deviation. - Get the standard deviation of
`values`

. The mean is also returned from this, because it’s required to compute the standard deviation.

## Type Definitions

As all algorithms are executed in linear time now, this is not as useful, but nevertheless an interesting feature. If you already have clustered data, this feature is great.