Computes a nonlinearity statistic based on Teräsvirta's nonlinearity test of a time series.
The statistic is \(10X^2/T\) where \(X^2\) is the Chi-squared statistic from
Teräsvirta's test, and T is the length of the time series. This takes large values
when the series is nonlinear, and values around 0 when the series is linear.

## Arguments

- x
a univariate time series

## Author

Yanfei Kang and Rob J Hyndman

## Examples

```
nonlinearity(lynx)
#> nonlinearity
#> 0.8959046
```