Results 61 to 70 of about 57,825 (288)
On the quasi-likelihood estimation for random coefficient autoregressions [PDF]
We examine the Gaussian quasi-maximum likelihood estimator (QMLE) for random coefficient autoregressions. Consistency and asymptotic normality are established for general random coefficients and general correlation structure between these coefficients ...
Truquet, L, Yao, J
core +3 more sources
Phase‐field simulations coupled with dislocation‐density‐based crystal plasticity modeling reproduce γ′ rafting behavior in single‐crystal Ni‐based superalloys under varied loading conditions. The model captures both macroscopic creep and microscopic morphology evolution, with results matching high‐temperature creep experiments.
Micheal Younan +5 more
wiley +1 more source
Quasi-maximum likelihood estimator of Laplace (1, 1) for GARCH models
This paper studies the quasi-maximum likelihood estimator (QMLE) for the generalized autoregressive conditional heteroscedastic (GARCH) model based on the Laplace (1,1) residuals.
Xuan Haiyan +3 more
doaj +1 more source
We study primordial non-Gaussian signatures in the redshift-space halo field on nonlinear scales, using a quasi-maximum likelihood estimator based on optimally compressed power spectrum and modal bispectrum statistics. We train and validate the estimator
Gabriel Jung +8 more
doaj +1 more source
Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading
The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
wiley +1 more source
This plot compares experimental tensile stress–strain curves (with 4 different strain rates) and corresponding modelled curves (obtained using the optimised sets of Voce and Miller–Norton parameter values shown). The inferred M‐N values, characterizing the creep, are very similar to those obtained via conventional creep testing.
S. Ooi, R. P. Thompson, T. W. Clyne
wiley +1 more source
ARCH and GARCH Models: Quasi-Likelihood and Asymptotic Quasi-Likelihood Approaches
This chapter considers estimation of autoregressive conditional heteroscedasticity (ARCH) and the generalized autoregressive conditional heteroscedasticity (GARCH) models using quasi-likelihood (QL) and asymptotic quasi-likelihood (AQL) approaches. The QL and AQL estimation methods for the estimation of unknown parameters in ARCH and GARCH models are ...
openaire +3 more sources
Quasi maximum likelihood estimation and prediction in the compound Poisson ECOGARCH(1,1) model [PDF]
This paper deals with the problem of estimation and prediction in a compound Poisson ECOGARCH(1,1) model. For this we construct a quasi maximum likelihood estimator under the assumption that all jumps of the log-price process are observable.
Czado, Claudia, Haug, Stephan
core +1 more source
The study presents biodegradable and recyclable mixed‐matrix membranes (MMMs), hydrogels, and cryogels using luminescent nanoscale metal‐organic frameworks (nMOFs) and biopolymers. These bio‐nMOF‐MMMs combine europium‐based nMOFs as probes for the status of the materials with the biopolymers agar and gelatine and present alternatives to conventional ...
Moritz Maxeiner +4 more
wiley +1 more source
Quasi-Likelihood Estimation in the Fractional Black–Scholes Model
In this paper, we consider the parameter estimation for the fractional Black–Scholes model of the form StH=S0H+μ∫0tSsHds+σ∫0tSsHdBsH, where σ>0 and μ∈R are the parameters to be estimated. Here, BH={BtH,t≥0} denotes a fractional Brownian motion with Hurst
Wenhan Lu, Litan Yan, Yiang Xia
doaj +1 more source

