Results 191 to 200 of about 23,325 (286)

Computational methods for discrete hidden semi‐Markov chains

Applied Stochastic Models in Business and Industry, 1999
Hidden Markov chains emerged in the 1970s in engineering and have since become a major tool for both pattern recognition applications such as speech or handwriting recognition or biological sequence analysis. Semi-Markov processes (or Markov renewal processes) have been applied for a long time in such diverse fields as biostatistics, operations ...
Yann Guédon
exaly   +10 more sources

Markov Chain Wave Generative Adversarial Network for Bee Bioacoustic Signal Synthesis. [PDF]

Sensors (Basel)
Samarappuli K, Ardekani I, Mohaghegh M, Sarrafzadeh A.   +3 more
europepmc   +1 more source

Testing Distributional Granger Causality With Entropic Optimal Transport

Journal of Time Series Analysis, EarlyView.
ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley   +1 more source

Bayesian Variable Selection for High-Dimensional Mediation Analysis: Application to Metabolomics Data in Epidemiological Studies. [PDF]

Stat Med
Bae Y, Kim C, Wang F, Sun Q, Lee KH.
europepmc   +1 more source

Multiple Chains Markov Switching Vector Autoregression

Journal of Time Series Analysis, EarlyView.
ABSTRACT Both the U.S. stock and bond returns exhibit distinct Markovian regimes. However, because these regimes display limited coherence, conventional models typically require highly parameterized systems to adequately capture their joint distribution.
Leopoldo Catania
wiley   +1 more source

SpaLSTF: Diffusion-based generative model with BiLSTM and XCA-Transformer for spatial transcriptomics imputation. [PDF]

PLoS Comput Biol
Yuan L, Jiang Y, Meng B, Wang Q, Wang C, Huang DS.   +5 more
europepmc   +1 more source

Navigating Supply Shocks: Sector Resilience and Production Prices Through Stochastic Input–Output Modeling

Mathematical Finance, EarlyView.
ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici, Gianluca Fusai, Anna Maria Gambaro, Daniele Marazzina   +3 more
wiley   +1 more source

Dynamic pricing modeling and inventory management in omnichannel retail using Quantum Decision Theory and reinforcement learning. [PDF]

PLoS One
Roosta S, Sadjadi SJ, Makui A.
europepmc   +1 more source

Random Carbon Tax Policy and Investment Into Emission Abatement Technologies

Mathematical Finance, EarlyView.
ABSTRACT We analyze the problem of a profit‐maximizing electricity producer, subject to carbon taxes, who decides on investments into CO2$\rm CO_2$ abatement technologies. We assume that the carbon tax policy is random and that the investment in the abatement technology is divisible, irreversible, and subject to transaction costs.
Katia Colaneri, Rüdiger Frey, Verena Köck   +2 more
wiley   +1 more source

Bayesian hierarchical models for multivariate mixed responses with repeated measures: A case study in arterial occlusive disease. [PDF]

PLoS One
Ebrahim EA, Cengiz MA.
europepmc   +1 more source