Results 231 to 240 of about 1,263,567 (386)

AN ASYMPTOTIC VALUATION FOR THE OPTION UNDER A GENERAL STOCHASTIC VOLATILITY(Special Issue on Theory, Methodology and Applications in Financial Engneering)

, 2002
Yongjin Kim
openalex   +2 more sources

Experimental studies on multi‐scale data‐driven methods within the framework of structural health monitoring

Civil Engineering Design, EarlyView.
Abstract The German Research Foundation has established the priority program SPP 100+. Its subject is monitoring bridge structures in civil engineering. The data‐driven methods cluster deals with the use of measurements and their special global and local analysis methods, which complement each other in an overall multi‐scale concept in order to realize
Maximilian Rohrer, Jan Backhaus, Ulf Bestmann, Vanessa De Arriba López, Pedro Achanccaray Diaz, Markus Gerke, Carsten Könke, Armin Lenzen, Lukas Lippold, Mehdi Maboudi, Max Moeller, Carlos Luis Paz Villegas, Paul Winkler, Volkmar Zabel   +13 more
wiley   +1 more source

Bayesian Inference for Generalised Markov Switching Stochastic Volatility Models [PDF]

, 2004
Roberto Casarin
openalex   +1 more source

An Efficient and Unified Modeling Framework for Trickle Bed Reactors: A Modular Approach

Chemie Ingenieur Technik, EarlyView.
This review gives an insight in modeling and designing techniques for multiphase catalytic reactors and their associated limitations and potential improvements. To enhance the predictive capabilities and capture events that take place on different scales, a modular approach is proposed.
Vasileios K. Mappas, Bogdan Dorneanu, Norbert Heinzelmann, Klaus Schnitzlein, Harvey Arellano‐Garcia   +4 more
wiley   +1 more source

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student's t-distribution. [PDF]

Stat Interface, 2017
Leão WL, Abanto-Valle CA, Chen MH.
europepmc   +1 more source

Bayesian Monte Carlo Filtering for Stochastic Volatility Models [PDF]

, 2004
Roberto Casarin
openalex   +1 more source

A probabilistic diagnostic for Laplace approximations: Introduction and experimentation

Canadian Journal of Statistics, EarlyView.
Abstract Many models require integrals of high‐dimensional functions: for instance, to obtain marginal likelihoods. Such integrals may be intractable, or too expensive to compute numerically. Instead, we can use the Laplace approximation (LA). The LA is exact if the function is proportional to a normal density; its effectiveness therefore depends on ...
Shaun McDonald, Dave Campbell
wiley   +1 more source

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form [PDF]

, 2004
Charles S. Bos, Neil Shephard
openalex   +1 more source

Harnessing Synergies between Combinatorial Microfluidics and Machine Learning for Chemistry, Biology, and Fluidic Design

Chemistry–Methods, EarlyView.
This review explores the synergy of combinatorial microfluidics and machine learning, highlighting their transformative impact on high‐throughput experimentation, closed‐loop reaction optimization, and autonomous platform development. Key applications in chemical synthesis, biological research, and microfluidic design are discussed, addressing ...
Suyash S. Damir, Julie Probst, Andrew deMello, Stavros Stavrakis   +3 more
wiley   +1 more source

Physical Climate Risk in Asset Management

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Climate‐related phenomena are increasingly affecting regions worldwide, manifesting as floods, water scarcity, and heat waves, significantly impairing companies' assets and productivity. It is essential for asset managers to quantify the exposure of their portfolios to such risk.
Michele Azzone, Matteo Ghesini, Davide Stocco, Lorenzo Viola   +3 more
wiley   +1 more source