Results 91 to 100 of about 776,491 (337)
Bayesian kernel-based system identification with quantized output data
, 2015 In this paper we introduce a novel method for linear system identification with quantized output data. We model the impulse response as a zero-mean Gaussian process whose covariance (kernel) is given by the recently proposed stable spline kernel, which ...
Bottegal, Giulio +2 more
core +1 more source
Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models
Applied Stochastic Models in Business and Industry, EarlyView.ABSTRACT Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs.
Mariflor Vega Carrasco +4 more
wiley +1 more source
Valuation of Defaultable Corporate Bonds Under Regime Switching
MathematicsThis study investigates the valuation of defaultable corporate bonds using a two-factor model of Markov-modulated stochastic volatility with double exponential jumps (2FMMSVDEJ).
Yu-Min Lian, Jun-Home Chen
doaj +1 more source
An Iterative Reduced KPCA Hidden Markov Model for Gas Turbine Performance Fault Diagnosis
Energies, 2018 To improve gas-path performance fault pattern recognition for aircraft engines, a new data-driven diagnostic method based on hidden Markov model (HMM) is proposed.
Feng Lu +3 more
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
Entropy, 2004 We define heat kernel measure on punctured spheres. The random field which is got by this procedure is not Gaussian. We define a stochastic line bundle on the loop space, such that the punctured sphere corresponds to a generalized parallel transport on ...
Rémi Léandre
doaj +1 more source
Total positivity of copulas from a Markov kernel perspective [PDF]
Journal of Mathematical Analysis and Applications, 2022 S. Fuchs, Marco Tschimpke
semanticscholar +1 more source
Blind Super-Resolution via Meta-Learning and Markov Chain Monte Carlo Simulation [PDF]
IEEE Transactions on Pattern Analysis and Machine IntelligenceLearning based approaches have witnessed great successes in blind single image super-resolution (SISR) tasks, however, handcrafted kernel priors and learning based kernel priors are typically required. In this paper, we propose a meta-learning and Markov
Jingyuan Xia +6 more
semanticscholar +1 more source
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
IEEE Access, 2018 Research on the uncertainty of wind power has a significant influence on power system planning and decision-making. This paper proposes a novel method for wind power interval forecasting based on rough sets theory, weighted Markov chain, and kernel ...
Xiyun Yang +3 more
doaj +1 more source