Abstract: In the field of optimization and machine learning, the statistical assessment of results has played a key role in conducting algorithmic performance comparisons. Classically, null hypothesis ...

Anomaly response in aerospace systems increasingly relies on multi-model analysis in digital twins to replicate the system’s behaviors and inform decisions. However, computer model calibration methods ...

Credit risk modelling is a cornerstone of modern finance, enabling lenders to quantify the risk that a borrower will default on their obligations. One of the most important metrics in this domain is ...

Inference of gene flow using genomic data requires powerful methods as the process of coalescent, migration, and mutation is highly stochastic. However, it is challenging to implement the multispecies ...

ELFI is a statistical software package written in Python for likelihood-free inference (LFI) such as Approximate Bayesian Computation (ABC). The term LFI refers to a family of inference methods that ...

Inferring parameters of computational models that capture experimental data is a central task in cognitive neuroscience. Bayesian statistical inference methods usually require the ability to evaluate ...

The performance of crop models in simulating various aspects of the cropping system is sensitive to parameter calibration. Parameter estimation is challenging, especially for time-dependent parameters ...

Cavendish Laboratory, Department of Physics, University of Cambridge, J.J. Thomson Avenue, Cambridge CB3 0HE, U.K. ISIS Neutron and Muon Source, STFC Rutherford ...

The entropy function takes as input a vector of frequency counts (the observed frequencies for a set of classes or states) and an alphabet size (the number of classes with non-zero probability, ...

1 Capital University of Economic and Business, Beijing, China. 2 Beijing University of Posts and Telecommunications, Beijing, China. 3 Sichuan University, Chengdu, China. 4 Zhejiang University, ...