2.7k citations · 3.6k across the 79 of their papers we have counts for
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Gamma-ray burst detection with Poisson-FOCuS and other trigger algorithms
Giuseppe Dilillo, Kes Ward, Idris A. Eckley +5
We describe how a novel online changepoint detection algorithm, called Poisson-FOCuS, can be used to optimally detect gamma-ray bursts within the computational constraints imposed…
Online Multivariate Changepoint Detection: Leveraging Links With Computational Geometry
Liudmila Pishchagina, Gaetano Romano, Paul Fearnhead +2
The increasing volume of data streams poses significant computational challenges for detecting changepoints online. Likelihood-based methods are effective, but a naive sequential i…
Simulation Based Composite Likelihood
Lorenzo Rimella, Chris Jewell, Paul Fearnhead
Inference for high-dimensional hidden Markov models is challenging due to the exponential-in-dimension computational cost of calculating the likelihood. To address this issue, we i…
A Constant-per-Iteration Likelihood Ratio Test for Online Changepoint Detection for Exponential Family Models
Kes Ward, Gaetano Romano, Idris Eckley +1
Online changepoint detection algorithms that are based on likelihood-ratio tests have been shown to have excellent statistical properties. However, a simple online implementation i…
A Log-Linear Non-Parametric Online Changepoint Detection Algorithm based on Functional Pruning
Gaetano Romano, Idris A Eckley, Paul Fearnhead
Online changepoint detection aims to detect anomalies and changes in real-time in high-frequency data streams, sometimes with limited available computational resources. This is an…
Improving Power by Conditioning on Less in Post-selection Inference for Changepoints
Rachel Carrington, Paul Fearnhead
Post-selection inference has recently been proposed as a way of quantifying uncertainty about detected changepoints. The idea is to run a changepoint detection algorithm, and then…