Bayesian analysis for parameter estimation for use in PSA - a case study

2010 ◽  
Author(s):  
M. Hari Prasad ◽  
V. V. S. Sanyasi Rao ◽  
A. K. Verma ◽  
A. Srividya
Keyword(s):  
Parameter Estimation ◽  
Bayesian Analysis

State and Parameter Estimation of Bioprocess Models a Case Study

1997 ◽  
Vol 30 (6) ◽  
pp. 1563-1568
Author(s):  
Vincent G. Ryckaert ◽  
Jan F. Van Impe
Keyword(s):  
Parameter Estimation

Bayesian analysis of school bus accidents: a case study of China

2018 ◽  
Vol 95 (3) ◽  
pp. 463-483 ◽  
Author(s):  
Jiansong Wu ◽  
Weipeng Fang ◽  
Xing Tong ◽  
Shuaiqi Yuan ◽  
Weiqi Guo
Keyword(s):  
Bayesian Analysis ◽  
School Bus ◽  
Bus Accidents

scholarly journals Model parameter estimation using Bayesian and deterministic approaches: the case study of the Maddalena Bridge

2018 ◽  
Vol 11 ◽  
pp. 210-217 ◽  
Author(s):  
A. De Falco ◽  
M. Girardi ◽  
D. Pellegrini ◽  
L. Robol ◽  
G. Sevieri
Keyword(s):  
Parameter Estimation ◽  
Model Parameter ◽  
Model Parameter Estimation

scholarly journals Comparison of different algorithms for simultaneous estimation of multiple parameters in kinetic metabolic models

2010 ◽  
Vol 7 (3) ◽  
Author(s):  
Syed Murtuza Baker ◽  
Kai Schallau ◽  
Björn H. Junker
Keyword(s):  
Parameter Estimation ◽  
Computational Models ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Simultaneous Estimation ◽  
Multiple Parameters ◽  
Reliable Parameter ◽  
Metabolic Models ◽  
Parameter Values

SummaryComputational models in systems biology are usually characterized by a lack of reliable parameter values. This is especially true for kinetic metabolic models. Experimental data can be used to estimate these missing parameters. Different optimization techniques have been explored to solve this challenging task but none has proved to be superior to the other. In this paper we review the problem of parameter estimation in kinetic models. We focus on the suitability of four commonly used optimization techniques of parameter estimation in biochemical pathways and make a comparison between those methods. The suitability of each technique is evaluated based on the ability of converging to a solution within a reasonable amount of time. As most local optimization methods fail to arrive at a satisfactory solution we only considered the global optimization techniques. A case study of the upper part of Glycolysis consisting 15 parameters is taken as the benchmark model for evaluating these methods.

Parameter estimation for the first-order BOD equation using nonlinear techniques

1977 ◽  
Vol 4 (4) ◽  
pp. 462-470 ◽  
Author(s):  
Thomas W. Constable ◽  
Edward A. McBean
Keyword(s):  
Parameter Estimation ◽  
Pollution Control ◽  
Control Plant ◽  
Estimation Methods ◽  
First Order ◽  
Expected Values ◽  
Parameter Estimation Methods ◽  
Parameter Estimation Techniques ◽  
Study Application

Two nonlinear parameter estimation techniques are used to obtain expected values, variances, and covariance estimates for L and k in the first-order BOD equation. The techniques are compared with a number of other BOD parameter estimation methods with respect to both estimated values of L and k and necessary assumptions about the measurement error structure of BOD analyses. The techniques that historically have been used to estimate the parameters in the first-order BOD equation are shown to often give erroneous answers because of their use of an incorrect error structure.A case study application of the methodology to the raw influent and primary effluent of the Waterloo Pollution Control Plant is included.

scholarly journals Bayesian analysis of galaxy spectral energy distributions with BayeSED

2012 ◽  
Vol 8 (S295) ◽  
pp. 312-312
Author(s):  
Yunkun Han ◽  
Zhanwen Han
Keyword(s):  
Parameter Estimation ◽  
Complex Systems ◽  
Bayesian Analysis ◽  
Bayesian Model ◽  
Model Comparison ◽  
Spectral Energy ◽  
Infrared Galaxies ◽  
Energy Distributions ◽  
Bayesian Model Comparison ◽  
Rigorous Test

AbstractIn Han & Han (2012), we have preliminarily built BayeSED and applied it to a sample of hyperluminous infrared galaxies. The physically reasonable results obtained from Bayesian model comparison and parameter estimation show that BayeSED could be a useful tool for understanding the nature of complex systems, such as dust obscured starburst-AGN composite galaxies, from decoding their complex SEDs. In this contribution, we present a more rigorous test of BayeSED by making a mock catalog from model SEDs with the value of all parameters to be known in advance.

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