Simulation of linear parameter estimation in spectrophotometry

Parameter Estimation in Linear Descriptor Systems

Linear descriptor systems form the natural way in which linear models of physical systems are delivered from an object-oriented modeling tool like Modelica. Linear descriptor systems are also known as linear differentialalgebraic equations in the continuous-time case. If some parameters in such models are unknown, one might need to estimate them from measured data from the modeled system. This ...

Parameter Estimation in Spatial Generalized Linear Mixed Models with Skew Gaussian Random Effects using Laplace Approximation

 Spatial generalized linear mixed models are used commonly for modelling non-Gaussian discrete spatial responses. We present an algorithm for parameter estimation of the models using Laplace approximation of likelihood function. In these models, the spatial correlation structure of data is carried out by random effects or latent variables. In most spatial analysis, it is assumed that rando...

Parameter estimation of switching piecewise linear system

During the last years, a number of methodological papers on models with discrete parameter shifts have revived interest in the so-called regime switching models. Piecewise linear models are attractive when modelling a wide range of nonlinear system and determining simultaneously i) the data partition ii) the time instant of change iii) the parameter values of the different local models. This is...

Stochastic Parameter Estimation of Non-Linear Systems

Many mechanical and structural systems respond dynamically to random environmental loads, such as wind, wave or earthquake forces. Examples include flexible buildings vibrating due to turbulent wind loading and offshore structures moving as a result of combining wave and wind loading. To assess the reliability of such structures it is important to predict their dynamic response, at the design s...

Simulation and Parameter Estimation of Spectrophotometric Instruments