# Quantile Fourier regressions for decision making under uncertainty

arXiv: https://arxiv.org/abs/2409.10455 · HTML: https://mlsanity.com/paper/2409.10455/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Sep 2024.

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

- [Frequency Response Identification of Low-Order Systems: Finite-Sample Analysis](https://mlsanity.com/paper/2508.17142/) (2025)

## Abstract (arXiv)

Weconsider Markov decision processes arising from a Markov model of an underlying natural phenomenon. Such phenomena are usually periodic (e.g. annual) in time, and so the Markov processes modelling them must be time-inhomogeneous, with cyclostationary rather than stationary behaviour. We describe a technique for constructing such processes that allows for periodic variations both in the values taken by the process and in the serial dependence structure. We include two illustrative numerical examples: a hydropower scheduling problem and a model of offshore wind power integration.