[HTML][HTML] Spectral information criterion for automatic elbow detection
We introduce a generalized information criterion that contains other well-known information
criteria, such as Bayesian information Criterion (BIC) and Akaike information criterion (AIC) …
criteria, such as Bayesian information Criterion (BIC) and Akaike information criterion (AIC) …
Multioutput feature selection for emulation and sensitivity analysis
Statistical regression methods are widely used in remote sensing applications but tend to
lack physical interpretability. In this article, we introduce a methodological framework to …
lack physical interpretability. In this article, we introduce a methodological framework to …
A variable selection analysis for soundscape emotion modelling using decision tree regression and modern information criteria
During the last decade, soundscape research has become one of the most active topics in
Acoustics. This work provides a nonlinear variable selection analysis over the well-known …
Acoustics. This work provides a nonlinear variable selection analysis over the well-known …
Utilising unsupervised machine learning and IoT for cost-effective anomaly detection in multi-layer wire arc additive manufacturing
Wire arc additive manufacturing (WAAM) is an additive manufacturing process for building
large-sized metal components using gas metal arc welding technology. Detecting defects …
large-sized metal components using gas metal arc welding technology. Detecting defects …
[HTML][HTML] An index of effective number of variables for uncertainty and reliability analysis in model selection problems
An index of an effective number of variables (ENV) is introduced for model selection in
nested models. This is the case, for instance, when we have to decide the order of a …
nested models. This is the case, for instance, when we have to decide the order of a …
On predicting ocean freight rates: a novel hybrid model of combined error evaluation and reinforcement learning
H Guo, H Kuang, C Sui, L Wang - Maritime Economics & Logistics, 2024 - Springer
The prediction of ship** freight rates is crucial for ship** companies and related
professionals, to navigate market changes, refine business strategy, and improve risk …
professionals, to navigate market changes, refine business strategy, and improve risk …
[HTML][HTML] Measuring unit relevance and stability in hierarchical spatio-temporal clustering
Understanding the significance of individual data points within clustering structures is critical
to effective data analysis. Traditional stability methods, while valuable, often overlook the …
to effective data analysis. Traditional stability methods, while valuable, often overlook the …
Second-Moment/Order Approximations by Kernel Smoothers with Application to Volatility Estimation
Volatility estimation and quantile regression are relevant active research areas in statistics,
machine learning and econometrics. In this work, we propose two procedures to estimate …
machine learning and econometrics. In this work, we propose two procedures to estimate …
Spatio-temporal hierarchical clustering of interval time series with application to suicide rates in Europe
In this paper, we investigate similarities of suicide rates in Europe, which are available as
interval time series. For this aim, a novel spatio-temporal hierarchical clustering algorithm for …
interval time series. For this aim, a novel spatio-temporal hierarchical clustering algorithm for …
The Clustered Dose-Response Function Estimator for continuous treatment with heterogeneous treatment effects
Many treatments are non-randomly assigned, continuous in nature, and exhibit
heterogeneous effects even at identical treatment intensities. Taken together, these …
heterogeneous effects even at identical treatment intensities. Taken together, these …