Results 61 to 70 of about 4,387 (252)
A goodness‐of‐fit test for regression models with discrete outcomes
Canadian Journal of Statistics, EarlyView.Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang +2 more
wiley +1 more source
Frontiers in Neuroscience, 2018 This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike ...
Kan Li, José C. Príncipe
doaj +1 more source
Journal of Forecasting, EarlyView.ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann +2 more
wiley +1 more source
$V$-geometrical ergodicity of Markov kernels via finite-rank approximations
Electronic Communications in Probability, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hervé, Loïc, Ledoux, James
openaire +5 more sources
A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios
Journal of Forecasting, EarlyView.ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley +1 more source
Integrated point-line-network model for road extraction based on tree-shaped point process
Egyptian Journal of Remote Sensing and Space SciencesUnsupervised road extraction methods based on traditional point processes have long faced challenges such as bottlenecks in processing efficiency and deficiencies in topological connectivity.
You Wu, Chen Wang
doaj +1 more source
Using DSGE and Machine Learning to Forecast Public Debt for France
Journal of Forecasting, EarlyView.ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
wiley +1 more source
A Hybrid Large-Kernel CNN and Markov Feature Framework for Remaining Useful Life Prediction
MachinesRemaining Useful Life (RUL) prediction has become a crucial component in predictive maintenance and condition-based operation with the rapid advancement of industrial automation and the increasing complexity of mechanical systems.
Yuke Wang +4 more
doaj +1 more source
Quantum tomography, phase-space observables and generalized Markov kernels [PDF]
Journal of Physics A: Mathematical and Theoretical, 2009 20 pages, 3 ...
openaire +2 more sources
International Journal of Finance &Economics, EarlyView.ABSTRACT This study aims to classify pivotal fintech innovations and explore the prospects and pitfalls associated with emerging fintech services extensively discussed in the literature. We conducted a multistage systematic review of research published on fintech over the past decade from a technological perspective. Using the Preferred Reporting Items
Muhammad Imran Qureshi, Nohman Khan
wiley +1 more source