Results 161 to 170 of about 11,331 (217)

Quantitative MRI in Neuroimaging: A Review of Techniques, Biomarkers, and Emerging Clinical Applications. [PDF]

Brain Sci
Saltarelli G, Di Cerbo G, Innocenzi A, De Felici C, Splendiani A, Di Cesare E.   +5 more
europepmc   +1 more source

Characteristics of T2* and anisotropy parameters in inguinal and epididymal adipose tissues after cold exposure in mice. [PDF]

Sci Rep
Ogawa M, Oshiro H, Tamura Y, Ishido M, Okamoto T, Hata J.   +5 more
europepmc   +1 more source

Langevin Dynamics Study on the Driven Translocation of Polymer Chains with a Hairpin Structure. [PDF]

Molecules
Wu F, Yang X, Wang C, Zhao B, Luo MB.
europepmc   +1 more source

Research on the Impact Toughness of 3D-Printed CoCrMo Alloy Components Based on Fractal Theory. [PDF]

Biomimetics (Basel)
Zhang G, Li J, Wang H, Shangguan C, Xie J, Zhou Y.   +5 more
europepmc   +1 more source

A review of today's stochastic stock-modeling processes with an application in the S&P 500 : how Fractional motions and Lévy distributions compare to the overall used Geometric Brownian Motion

, 2008
openaire   +1 more source

EFFICIENT ESTIMATORS FOR GEOMETRIC FRACTIONAL BROWNIAN MOTION PERTURBED BY FRACTIONAL ORNSTEIN-UHLENBECK PROCESS

Advances and Applications in Statistics, 2020
This paper discusses an enhanced model of geometric fractional Brownian motion where its volatility is assumed to be stochastic volatility model obey fractional Ornstein-Uhlenbeck process. The method of estimation for all parameters in this model are derived.
Alhagyan, Mohammed, Misiran, Masnita, Omar, Zurni   +2 more
openaire   +3 more sources

Pricing geometric asian power options in the sub-fractional brownian motion environment

Chaos, Solitons & Fractals, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wang, Wei, Cai, Guanghui, Tao, Xiangxing
openaire   +2 more sources

Parameter identification for the discretely observed geometric fractional Brownian motion

Journal of Statistical Computation and Simulation, 2013
This paper deals with the problem of estimating all the unknown parameters of geometric fractional Brownian processes from discrete observations. The estimation procedure is built upon the marriage of the quadratic variation and the maximum likelihood approach. The asymptotic properties of the estimators are provided.
Weilin Xiao, Weiguo Zhang, Xili Zhang
openaire   +2 more sources

ESTIMATION OF GEOMETRIC FRACTIONAL BROWNIAN MOTION PERTURBED BY STOCHASTIC VOLATILITY MODEL

Far East Journal of Mathematical Sciences (FJMS), 2015
This article is aimed at to derive geometric fractional Brownian motion where its volatility follow long memory stochastic volatility model, in particular the fractional Ornstein-Uhlenbech process. The innovation algorithm is utilized to simplify such derivation. A simple case of is calculated to illustrate the calculation to accompany this derivation.
Alhagyan, Mohammed, Misiran, Masnita, Omar, Zurni   +2 more
openaire   +3 more sources