# The Splice Bootstrap

arXiv: https://arxiv.org/abs/1311.5828 · HTML: https://mlsanity.com/paper/1311.5828/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Nov 2013.

## Built on by (most cited first, 1 of 1)

- [Robust Nonparametric Distribution Forecast with Backtest-based Bootstrap and Adaptive Residual Selection](https://mlsanity.com/paper/2202.07955/) (2022)

## Abstract (arXiv)

This paper proposes a new bootstrap method to compute predictive intervals for nonlinear autoregressive time series model forecast. This method we call the splice boobstrap as it involves splicing the last p values of a given series to a suitably simulated series. This ensures that each simulated series will have the same set of p time series values in common, a necessary requirement for computing conditional predictive intervals. Using simulation studies we show the methods gives 90% intervals intervals that are similar to those expected from theory for simple linear and SETAR model driven by normal and non-normal noise. Furthermore, we apply the method to some economic data and demonstrate the intervals compare favourably with cross-validation based intervals.