When did global warming start? A new baseline for carbon budgeting

HB Ameur, X Han, Z Liu, J Peillex - Economic Modelling, 2022 - Elsevier
The global temperatures over the period 1850–1900 are widely used by academia and
policymaker as a pre-industrial baseline to assess global warming, but there remains a clear …

Anomaly detection approach using adaptive cumulative sum algorithm for controller area network

H Olufowobi, U Ezeobi, E Muhati, G Robinson… - Proceedings of the …, 2019 - dl.acm.org
The modern vehicle has transformed from a purely mechanical system to a system that
embeds several electronic devices. These devices communicate through the in-vehicle …

Sequential change diagnosis revisited and the Adaptive Matrix CuSum

A Warner, G Fellouris - Bernoulli, 2024 - projecteuclid.org
The supplement (Warner and Fellouris (2024)) is composed of Appendices A–F.
Appendices A and B provide properties of CuSum statistics and stopping times. The …

The optimal time to buy and hold stock in a reversal

X Han, Z Liu - International Journal of Finance & Economics, 2023 - Wiley Online Library
Investors cannot anticipate a return reversal in the stock market. Therefore, choosing the
optimal time to buy and hold a stock is vital. This paper formulates a disorder problem using …

Model misspecification in discrete time Bayesian online change detection

S Dayanik, SO Sezer - Methodology and Computing in Applied Probability, 2023 - Springer
We revisit the classical formulation of the discrete time Bayesian online change detection
problem in which the common distribution of an observed sequence of random variables …

Fail-Operational Intrusion Detection Systems (FO-IDS): A Mechanism for Securing Automotive In-Vehicle Networks

HD Olufowobi - 2019 - search.proquest.com
The security and privacy of automotive vehicles is a significant problem to address. By
adding functionality to enhance safety and comfort, vehicles increasingly depend on …

[图书][B] Epidemic Detection in Two Populations

K Shatskikh - 2017 - search.proquest.com
Traditional epidemic detection algorithms make decisions using only local information. We
propose a novel approach that explicitly models spatial information fusion from several meta …