Results 121 to 130 of about 103,412 (240)
Robust Bernoulli Mixture Models for Credit Portfolio Risk
ABSTRACT This paper presents comparison results and establishes risk bounds for credit portfolios within classes of Bernoulli mixture models, assuming conditionally independent defaults that are stochastically increasing in a common risk factor. We provide simple and interpretable conditions on conditional default probabilities that imply a comparison ...
Jonathan Ansari, Eva Lütkebohmert
wiley +1 more source
Quasiconformal circles and Lipschitz classes
Näkki, Raimo, Palka, Bruce
openaire +2 more sources
Reinforcement Learning for Jump‐Diffusions, With Financial Applications
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley +1 more source
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 +3 more
wiley +1 more source
S2‐PepAnalyst: A Web Tool for Predicting Plant Small Signalling Peptides
ABSTRACT Small signalling peptides (SSPs) serve as crucial mediators of cell‐to‐cell communication in plants, orchestrating diverse physiological processes from development to stress responses. While recent advances in sequencing technologies have improved genome annotation, the identification of novel SSPs remains challenging due to their small size ...
Kelly L. Vomo‐Donfack +5 more
wiley +1 more source
Sensitivity analysis for generalized estimating equation with non‐ignorable missing data
Abstract Many incomplete‐data statistical inference procedures are developed under the missing at random (MAR) assumption. However, the MAR assumption has been criticized as being overly strong for real‐data problems, and is unverifiable by using observed data. To handle data that are missing not at random (MNAR), sensitivity analysis has been proposed
Hui Gong, Kin Wai Chan
wiley +1 more source
Lifts of continuous and Hölder alpha curves in the configuration space MN/SN$M^N/S_N$
Abstract In this paper, we study the quotient space X=MN/SN$X = M^N / S_N$ of equivalence classes of N$N$‐tuples in a metric space (M,dM)$(M, d_M)$, equipped with the metric induced by the minimal total pairing distance. Given a continuous path F:(0,1)→X$F: (0,1) \rightarrow X$, we prove that there exist continuous functions f1,⋯,fN:(0,1)→M$f_1, \dots,
Charles L. Fefferman +3 more
wiley +1 more source
ABSTRACT This paper focuses on state estimation for a fairly general class of systems, involving nonlinear functions and disturbances in both the process dynamics and output equations. A nonlinear observer that satisfies a H∞$$ {\boldsymbol{H}}_{\boldsymbol{\infty}} $$ disturbance attenuation constraint in addition to providing asymptotic stability in ...
Hamidreza Movahedi +2 more
wiley +1 more source
Degree theory for 4‐dimensional asymptotically conical gradient expanding solitons
Abstract We develop a new degree theory for 4‐dimensional, asymptotically conical gradient expanding solitons. Our theory implies the existence of gradient expanding solitons that are asymptotic to any given cone over S3$S^3$ with non‐negative scalar curvature. We also obtain a similar existence result for cones whose link is diffeomorphic to S3/Γ$S^3/\
Richard H. Bamler, Eric Chen
wiley +1 more source
Lipschitz estimates for convex functions with respect to vector fields
We present Lipschitz continuity estimates for a class of convex functions with respect to Hörmander vector fields. These results have been recently obtained in collaboration with M. Scienza, [22].
Valentino Magnani
doaj

