Search Results - "Eckley, Idris A."

A computationally efficient nonparametric approach for changepoint detection by Haynes, Kaylea, Fearnhead, Paul, Eckley, Idris A.

“…In this paper we build on an approach proposed by Zou et al. ( 2014 ) for nonparametric changepoint detection. This approach defines the best segmentation for…”
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Gamma-Ray Burst Detection with Poisson-FOCuS and Other Trigger Algorithms by Dilillo, Giuseppe, Ward, Kes, Eckley, Idris A., Fearnhead, Paul, Crupi, Riccardo, Evangelista, Yuri, Vacchi, Andrea, Fiore, Fabrizio

“…Abstract We describe how a novel online change-point detection algorithm, called Poisson-FOCuS, can be used to optimally detect gamma-ray bursts within the…”
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changepoint : An R Package for Changepoint Analysis by Killick, Rebecca, Eckley, Idris A.

“…One of the key challenges in changepoint analysis is the ability to detect multiple changes within a given time series or sequence. The changepoint package has…”
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Detection of changes in variance of oceanographic time-series using changepoint analysis by Killick, Rebecca, Eckley, Idris A., Ewans, Kevin, Jonathan, Philip

“…Changepoint analysis is used to detect changes in variability within GOMOS hindcast time-series for significant wave heights of storm peak events across the…”
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Computationally Efficient Changepoint Detection for a Range of Penalties by Haynes, Kaylea, Eckley, Idris A., Fearnhead, Paul

“…In the multiple changepoint setting, various search methods have been proposed, which involve optimizing either a constrained or penalized cost function over…”
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A Log-Linear Nonparametric Online Changepoint Detection Algorithm Based on Functional Pruning by Romano, Gaetano, Eckley, Idris A., Fearnhead, Paul

“…Online changepoint detection aims to detect anomalies and changes in real time within high frequency data streams, sometimes with limited available…”
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Detection of Emergent Anomalous Structure in Functional Data by Austin, Edward, Eckley, Idris A., Bardwell, Lawrence

“…Motivated by an example arising from digital networks, we propose a novel approach for detecting the emergence of anomalies in functional data. In contrast to…”
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A communication-efficient, online changepoint detection method for monitoring distributed sensor networks by Yang, Ziyang, Eckley, Idris A., Fearnhead, Paul

“…We consider the challenge of efficiently detecting changes within a network of sensors, where we also need to minimise communication between sensors and the…”
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High-Dimensional Time Series Segmentation via Factor-Adjusted Vector Autoregressive Modeling by Cho, Haeran, Maeng, Hyeyoung, Eckley, Idris A., Fearnhead, Paul

“…Vector autoregressive (VAR) models are popularly adopted for modeling high-dimensional time series, and their piecewise extensions allow for structural changes…”
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Sparse temporal disaggregation by Mosley, Luke, Eckley, Idris A., Gibberd, Alex

“…Temporal disaggregation is a method commonly used in official statistics to enable high‐frequency estimates of key economic indicators, such as gross domestic…”
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Innovative and Additive Outlier Robust Kalman Filtering With a Robust Particle Filter by Fisch, Alexander T. M., Eckley, Idris A., Fearnhead, Paul

“…In this paper, we propose CE-BASS, a particle mixture Kalman filter which is robust to both innovative and additive outliers, and able to fully capture…”
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BayesProject: Fast computation of a projection direction for multivariate changepoint detection by Hahn, Georg, Fearnhead, Paul, Eckley, Idris A.

“…This article focuses on the challenging problem of efficiently detecting changes in mean within multivariate data sequences. Multivariate changepoints can be…”
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Subset Multivariate Collective and Point Anomaly Detection by Fisch, Alexander T. M., Eckley, Idris A., Fearnhead, Paul

“…In the recent years, there has been a growing interest in identifying anomalous structure within multivariate data sequences. We consider the problem of…”
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Estimating Time-Evolving Partial Coherence Between Signals via Multivariate Locally Stationary Wavelet Processes by Park, Timothy, Eckley, Idris A., Ombao, Hernando C.

“…We consider the problem of estimating time-localized cross-dependence in a collection of nonstationary signals. To this end, we develop the multivariate…”
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Semiparametric detection of changepoints in location, scale, and copula by Agarwal, Gaurav, Eckley, Idris A., Fearnhead, Paul

“…This paper proposes a new method to detect changepoints in the location and scale of univariate data sequences. The proposed method assumes that the data…”
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A linear time method for the detection of collective and point anomalies by Fisch, Alexander T. M., Eckley, Idris A., Fearnhead, Paul

“…The challenge of efficiently identifying anomalies in data sequences is an important statistical problem that now arises in many applications. Although there…”
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Most Recent Changepoint Detection in Panel Data by Bardwell, Lawrence, Fearnhead, Paul, Eckley, Idris A., Smith, Simon, Spott, Martin

“…Detecting recent changepoints in time-series can be important for short-term prediction, as we can then base predictions just on the data since the…”
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Automatic locally stationary time series forecasting with application to predicting UK gross value added time series by Killick, Rebecca, Knight, Marina I, Nason, Guy P, Nunes, Matthew A, Eckley, Idris A

“…Abstract Accurate forecasting of the UK gross value added (GVA) is fundamental for measuring the growth of the UK economy. A common nonstationarity in GVA…”
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Real time anomaly detection and categorisation by Fisch, Alexander T. M., Bardwell, Lawrence, Eckley, Idris A.

“…The ability to quickly and accurately detect anomalous structure within data sequences is an inference challenge of growing importance. This work extends…”
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A wavelet-based approach for imputation in nonstationary multivariate time series by Wilson, Rebecca E., Eckley, Idris A., Nunes, Matthew A., Park, Timothy

“…Many multivariate time series observed in practice are second order nonstationary, i.e. their covariance properties vary over time. In addition, missing…”
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