This chapter describes the principles and the methods applicable to the parameter estimation problem. In particular, it describes the least squares (LS) estimator, the maximum likelihood (ML) estimator, the Bay
Model parameter estimation represents a challenge in many fields. A large number of algorithms exist to address this need. These run the gamut from straightforward steepest descent methods, to genetic algorithms, simulated annealing, regression, Bayesian methods and others (Yang et al., 2019). In ...
Kadeethum, T., O’Malley, D., Fuhg, J.N.et al.A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks.Nat Comput Sci1, 819–829 (2021). https://doi.org/10.1038/s43588-021-00171-3 ...
Mathematics, Statistics & Data Science Communications in Statistics - Theory and Methods List of Issues Volume 31, Issue 6 PARAMETER ESTIMATION BASED ON GROUPED OR ... Search in:This JournalAnywhere Advanced search Communications in Statistics - Theory and MethodsVolume 31, 2002 -Issue 6 Submit...
International Journal of Systems ScienceBennett, R. J.: 1976, ‘Non-Stationary Parameter Estimation for small Sample Situations: A Comparison of Methods’, Int. J. Syst. Sci. 7 , 257–275.Bennett R J, 1976 "Non-stationary parameter estimation for small sample situation: a comparison of ...
As the amount of data increases and new methods are continuously proposed, traditional geophysical research can be combined with advanced data science methods12. In the analysis of logging and seismic data, due to the heterogeneity of the formation and the complexity of the influencing factors of ...
4.Environmental Science and Engineering, University of Northern British Columbia, Prince George V2N 4Z9, Canada Abstract Parameter estimation is defined as the process to adjust or optimize the model parameter using observations. A...
In many applications, count numbers of the diffusing molecular species are very low, leading to the need to explicitly model the inherent variability using stochastic methods. Despite their importance and frequent use, parameter estimation for both deterministic and stochastic reaction-diffusion systems ...
This article presents research into data assimilation methods for morphodynamic model state and parameter estimation. First, we focus on state estimation and describe implementation of a three-dimensional variational (3D-Var) data assimilation scheme in a simple 2D morphodynamic model of Morecambe Bay, ...
While the models, measurements, and parameter estimation methods differ in numerous ways, the patterns in these results may well be a general feature of lumped parameter circulatory models. 5. Conclusion We have applied the stepwise subset reduction method (SSRM) to a closed-loop lumped parameter ...