Results 61 to 70 of about 9,580 (220)

Information Design for Early‐Stage Dose‐Finding Trials

Naval Research Logistics (NRL), EarlyView.
ABSTRACT To enhance enrollment rates in early‐stage dose‐finding clinical trials, we propose an information design approach, where the clinical investigator (CI) commits to an information releasing mechanism (IRM) based on the treatment's uncertain efficacy and toxicity to encourage patients to participate in the trial.
Amin Khademi, Ningyuan Chen
wiley   +1 more source

Long memory with Markov-Switching GARCH [PDF]

The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives su?cient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation
Krämer, Walter
core  

Impact of Packaging and Recycling Systems on Material Recirculation: A Stage‐Decomposition Model

Packaging Technology and Science, EarlyView.
A system‐level view emerges from decomposing recycling into four stages (participation, collection, sorting and process yield), diagnosing constraints and targeting interventions. Cumulative equivalent uses (CEUs) quantify long‐term retention, revealing marginal improvements at high baselines generate disproportionately larger gains than low‐baseline ...
Diogo Figueirinhas, Daniel Hellström, Henrik Pålsson, Yulia Vakulenko   +3 more
wiley   +1 more source

Bivariate postprocessing of wind vectors

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We introduce three novel bivariate postprocessing approaches and analyze their performance for joint postprocessing of bivariate wind‐vector components in Germany. Bivariate vine‐copula‐based models, a bivariate gradient‐boosted version of ensemble model output statistics (EMOS), and a bivariate distributional regression network (DRN) are compared with
Ferdinand Buchner, David Jobst, Annette Möller, Claudia Czado   +3 more
wiley   +1 more source

Estimation of the stationary distribution of a semi-Markov chain

This article is concerned with the estimation of the stationary distribution of a discretetime semi-Markov process. After briefly presenting the discrete-time semi-Markov setting, wepropose an estimator of the associated stationary distribution. The main
Bulla, Jan, Barbu, Vlad, Maruotti, Antonello   +2 more
core  

HMM in dynamic HAC models [PDF]

Understanding the dynamics of high dimensional non-normal dependency structure is a challenging task. This research aims at attacking this problem by building up a hidden Markov model (HMM) for Hierarchical Archimedean Copulae (HAC), where the HAC ...
Wolfgang Karl Härdle, Weining Wang, Ostap Okhrin   +2 more
core  

Epistemic and aleatoric uncertainty quantification in weather and climate models

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Aleatoric and epistemic uncertainties over time on weather and climate time‐scales, estimated through ensembles that sample aleatoric and epistemic uncertainty using Bayesian neural networks for parameterisations in the Lorenz 1996 model. The spread shows the 16th and 84th percentiles.
Laura A. Mansfield, Hannah M. Christensen   +1 more
wiley   +1 more source

Output‐Feedback H∞$$ {H}_{\infty } $$ Detector‐Based Control of Continuous‐Time Markov Jump Lur'e Systems With Sector‐Bound Optimization

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper addresses the problem of dynamic output‐feedback H∞$$ {H}_{\infty } $$ detector‐based control for continuous‐time Markov Jump Lur'e Systems with uncertain transition rate matrices. In contrast to conventional approaches, the proposed synthesis conditions are derived using Finsler's lemma, introducing additional slack variables to ...
Lucas P. M. Silva, Cecilia F. Morais, Ricardo C. L. F. Oliveira   +2 more
wiley   +1 more source

On identifiability of MAP processes [PDF]

Two types of transitions can be found in the Markovian Arrival process or MAP: with and without arrivals. In transient transitions the chain jumps from one state to another with no arrival; in effective transitions, a single arrival occurs.
Michael P. Wiper, Rosa E. Lillo, Pepa Ramirez   +2 more
core  

Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning

SmartBot, EarlyView.
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo, Rodrigo S. Jamisola Jr., Molaletsa Namoshe   +2 more
wiley   +1 more source