An exemplar-based hidden Markov model framework for nonlinear state-space models
, 2016 Redouane Lguensat +3 more
openalex +2 more sources
Spectrum Sensing Using a Hidden Bivariate Markov Model
IEEE Transactions on Wireless Communications, 2013 Thao T. Nguyen, B. L. Mark, Y. Ephraim
semanticscholar +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
Historical Use of Markov Model and Posterior Predictive Checks in Pharmacometrics. [PDF]
CPT Pharmacometrics Syst PharmacolGirard P, Kastrissios H.
europepmc +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
Unsupervised segmentation of noisy and textured images modeled by Markov random fields
, 1992 Georghios K. Gregoriou +2 more
openalex +1 more source
Regime‐Dependent Nowcasting of the Austrian Economy
Journal of Forecasting, EarlyView.ABSTRACT We nowcast and forecast economic activity in Austria, namely, real gross domestic product (GDP), consumption, and investment, which are available at a quarterly frequency, using a preselected number of monthly indicators based on a combination of statistical procedures.
Jaroslava Hlouskova, Ines Fortin
wiley +1 more source
Subtype-specific health and economic impact of delayed breast cancer diagnosis during the early COVID-19 pandemic in Belgium: a Markov model analysis. [PDF]
Breast Cancer ResKhan Y +8 more
europepmc +1 more source
Bayesian Diagnostics of Hidden Markov Structural Equation Models with Missing Data
, 2018 Jingheng Cai +3 more
openalex +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