Standard Bayesian autoregressive changepoint models can become unstable near sample boundaries. As a candidate changepoint approaches either edge of the series, the local residual degrees of freedom shrink, producing a Gamma-function singularity in t...
This paper proposes a score-driven Bayesian method to detect online mean change-points in a vector autoregressive model. The within-state process follows a multivariate autoregressive structure with time-varying autoregressive coefficient matrices an...
This paper assesses the effectiveness of different unsupervised Bayesian changepoint detection (BCPD) methods for identifying soil layers, using data from cone penetration tests (CPT). It compares four types of BCPD methods: a previously utilised off...
Structural changes, or changepoints, coinciding in multiple ice core records over the Greenland Ice Sheet (GrIS) may reflect a widespread response of the GrIS to atmospheric forcing. Thus, to better understand how atmospheric circulation may regulate...
In this paper, an approach to perform leak state detection and size identification for industrial fluid pipelines with an acoustic emission (AE) activity intensity index curve (AIIC), using b-value and a random forest (RF), is proposed. Initially, th...
While Europe was beginning to deal with the resurgence of COVID-19 due to the Delta variant, the European football championship took place from 11 June to 11 July 2021. We studied the inversion in the decreased/increased rate of new SARS-COV-2 infect...
The usual mean change-point detecting method based on normal linear regression is not robust to heavy-tailed data with potential outlying points. We propose a robust change-point estimation procedure based on a quantile regression model with asymmetr...
The change–point problem is about identifying when a pattern or trend shifts in time–ordered data. In survival analysis, change–point detection focuses on identifying alterations in the distribution of time–to–event data...
Due to the diversity of ship-radiated noise (SRN), audio segmentation is an essential procedure in the ship statuses/categories identification. However, the existing segmentation methods are not suitable for the SRN because of the lack of prior knowl...
In this paper, a Bayesian change-point model was used to examine the phenological changes in the predominant crop producing states of U.S over a 33-year period (1981–2013). Changes of phenological observation were categorized into a no-change model a...
Aiming at tracking sharply maneuvering targets, this paper develops novel variational adaptive state estimators for joint target state and process noise parameter estimation for a class of linear state-space models with abruptly changing parameters....
Following the declaration by the World Health Organisation (WHO) on 11 March 2020, that the global COVID-19 outbreak had become a pandemic, South Africa implemented a full lockdown from 27 March 2020 for 21 days. The full lockdown was implemented aft...
The COVID-19 pandemic has reshaped global infrastructure, highlighting the importance of effective infectious disease management. Identifying when and where infection trends change abnormally can aid strategic planning; yet, existing change point det...
These days, the prices of fruits and vegetables fluctuate significantly, causing issues in the supply chain and for perishable products. This study aimed to use hybrid machine learning methods to cluster regional Chilean produce from 2015 to 2023 bas...
The objective of this article was to compare the performance of two vegetation indices (MODIS EVI (optical) and AMSR-E/ and TMI/TRMM LPRM VOD (microwave)) using an offline Bayesian change-point algorithm to monitor vegetation dynamics (retrospective...
Climate change profoundly impacts hydrological systems, particularly in regions such as Croatia, which is renowned for its diverse geography and climatic variability. This study examined the effect of climate change on streamflow rates in two Croatia...
Volatility regime identification underpins risk management and portfolio allocation in quantitative finance, yet standard mixture models fail in heavy-tailed environments: components are consumed by outliers rather than genuine persistent regimes. We...
Forest fires, intensified by climate change, threaten tropical ecosystems by accelerating biodiversity loss, releasing carbon emissions, and altering hydrological cycles. Continuous detection of fire-induced forest loss is therefore critical. However...
The transition from antibiotic-based (AB) to antibiotic-free (ABF) broiler production represents a major shift in poultry management, with potential implications for flock health, welfare, and processing outcomes. This study evaluated its impact on c...
Increased tourism in Belize over the last decade and the growth of the local population have led to coastal development and infrastructure expansion. Land use alteration and anthropogenic activity may change the sediment and nutrient loads in coastal...
Tropical cyclones (TCs) pose a significant threat in terms of wind-induced damage and storm risk to the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. In this research, annual power dissipation index (PDI) and storm surge and...
Understanding the dynamics of vegetation autumn phenology (i.e., the end of growing season, EOS) is crucial for evaluating impacts of climate change on vegetation growth. Nevertheless, responses of the EOS to climatic factors were unclear at the regi...
Meiyu onset marks the beginning of the rainfall season in the densely populated Yangtze River Basin, whether the Meiyu initiates early or late in June, and thus has a profound effect on the several hundred million people living there. Applying a Baye...
The dynamic monitoring and analysis of wetland vegetation play important roles in revealing the change, restoration and reconstruction of the ecosystem environment. The increasing availability of high spatial-temporal resolution remote sensing data p...
High-precision tunnel breakthroughs depend critically on the north-seeking accuracy of maglev gyroscopes. However, external disturbances during underground construction often introduce abrupt jumps into rotor current signals, significantly reducing t...
Water resource planning in a trans-boundary river basin is complex because of different institutional and scientific concerns and it may become increasingly difficult as a consequence of water scarcity caused by climate change. The analysis of discha...
Freshwater monitoring networks are often biased toward major rivers and chemical indicators, creating blind spots in ecologically sensitive areas. This study tests whether a legacy monitoring network is positioned in the right parts of its catchment,...
Accurate quantification of vegetation vertical structure is crucial for analyzing the ecological functions of urban green spaces. However, constrained by the complexity of vegetation structure and spatial heterogeneity, current approaches for extract...