Results 121 to 130 of about 559 (266)

Density‐Valued ARMA Models by Spline Mixtures

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This paper proposes a novel framework for modeling time series of probability density functions by extending autoregressive moving average (ARMA) models to density‐valued data. The method is based on a transformation approach, wherein each density function on a compact domain [0,1]d$$ {\left[0,1\right]}^d $$ is approximated by a B‐spline ...
Yasumasa Matsuda, Rei Iwafuchi
wiley   +1 more source

Nonlinear approximations in tomography, quadrature construction, and multivariate reductions

open access: yes, 2012
This thesis consists of contributions to three topics: algorithms for computing generalized Gaussian quadratures, tomographic imaging algorithms, and reduction algorithms. Our approach is based on using non-linear approximations of functions.
Reynolds, Matthew Jason
core   +1 more source

A Nodal Immersed Finite Element-Finite Difference Method. [PDF]

open access: yesJ Comput Phys, 2023
Wells D   +3 more
europepmc   +1 more source

On the computation of symmetric Szegő-type quadrature formulas

open access: yes, 2010
By z = exp(iθ) and x = cos θ, one may relate x ∈ I=(-1,1], with θ ∈ (-π,π] and a point z on the complex unit circle T. Hence there is a connection between the integrals of 2π-periodic functions, integrals of functions over I and over T.
Bultheel, Adhemar   +3 more
core  

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

open access: yesMathematical Finance, EarlyView.
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

The Optimal Mean–Variance Selling Problem With Finite Horizon

open access: yesMathematical Finance, EarlyView.
ABSTRACT The optimal mean–variance selling problem seeks to determine a dynamically optimal stopping time in the nonlinear problem sup0≤τ≤TE(Xτ)−cVar(Xτ)$\sup _{0 \le \tau \le T} \left[ \mathsf {E}\,\!(X_\tau) - c\, \mathsf {V}ar\,\!(X_\tau) \right]$, where X$X$ is a geometric Brownian motion with strictly positive drift, the supremum is taken over ...
Peter Johnson   +2 more
wiley   +1 more source

Solving Stochastic Climate‐Economy Models: A Deep Least‐Squares Monte Carlo Approach

open access: yesMathematical Finance, EarlyView.
ABSTRACT Stochastic versions of recursive integrated climate‐economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of state variables and stochastic shocks increases, solving these models via deterministic grid‐based dynamic programming (e.g., value‐function iteration/projection ...
Aleksandar Arandjelović   +4 more
wiley   +1 more source

Root Structural and Metabolic Plasticity Confers Tolerance to Salinity in Wild Barley Species Grown Under Waterlogging

open access: yesPlant, Cell &Environment, EarlyView.
ABSTRACT Salinity combined with waterlogging is a major abiotic stress that severely limits crop growth and yield. We investigated species‐specific adaptations to salinity under constant waterlogging conditions in the wild halophytic barleys Hordeum marinum and H. glaucum, compared with the cultivated H. vulgare.
Stanislav Isayenkov   +10 more
wiley   +1 more source

Reading Dürer in Late Sixteenth‐Century Padua: Matteo Macigni (ca. 1510–1582), His Library and the Annotated Institutionum geometricarum (Paris, 1535)

open access: yesRenaissance Studies, EarlyView.
ABSTRACT This article contributes to the history of material culture and intellectual biography by definitively identifying the Paduan scholar Matteo Macigni (ca. 1510–1582) as the author of the annotations found in a 1535 copy of Albrecht Dürer’s Institutionum geometricarum currently preserved in Vicenza.
Laura Moretti
wiley   +1 more source

Home - About - Disclaimer - Privacy