Results 211 to 220 of about 164,472 (335)

Alternative Approaches for Estimating Highest‐Density Regions

International Statistical Review, EarlyView.
Summary Among the variety of statistical intervals, highest‐density regions (HDRs) stand out for their ability to effectively summarise a distribution or sample, unveiling its distinctive and salient features. An HDR represents the minimum size set that satisfies a certain probability coverage, and current methods for their computation require ...
Nina Deliu, Brunero Liseo
wiley   +1 more source

Factor Graph-Based Time-Synchronized Trajectory Planning for UAVs in Ground Radar Environment Simulation. [PDF]

Sensors (Basel)
Słowak P, Kaczmarek P, Kapski A, Kaniewski P.   +3 more
europepmc   +1 more source

On a rigidity property for quadratic Gauss sums [PDF]

Alexander P. Mangerel
openalex   +1 more source

Gauss sums of some matrix groups over $\Bbb Z/n\Bbb Z$ [PDF]

, 2018
Su Hu, Guoxing He, Yingtong Meng, Yan Li
openalex   +1 more source

Specification Tests for Jump‐Diffusion Models Based on the Characteristic Function

International Statistical Review, EarlyView.
Summary Goodness‐of‐fit tests are suggested for several popular jump‐diffusion processes. The suggested test statistics utilise the marginal characteristic function of the model and its L2‐type discrepancy from an empirical counterpart. Model parameters are estimated either by minimising the aforementioned L2‐type discrepancy or by maximum likelihood ...
Gerrit Lodewicus Grobler, Denis Belomestny, Simos George Meintanis, Emanuele Taufer   +3 more
wiley   +1 more source

Gas-Phase Electrophoresis (nES GEMMA Instrumentation) of SARS-CoV-2-Based Virus-like Particles. [PDF]

ACS Omega
Weiss VU, Marchetti-Deschmann M.
europepmc   +1 more source

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, EarlyView.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source

A multimodal tiered magnetic polarity inversion features dataset for space weather forecasting. [PDF]

Data Brief
Khani Z, Ji A, Georgoulis MK, Aydin B.
europepmc   +1 more source

Some conjectures concerning Gauss sums.

Journal für die reine und angewandte Mathematik (Crelles Journal), 1978
openaire   +1 more source

Universal Gauss-Thakur sums and L-series

, 2013
Bruno Anglès, Federico Pellarin
openalex   +2 more sources