Displaying similar documents to “GAMS langauage in description of method of minimum total variation.”

On parameter estimation in an in vitro compartmental model for drug-induced enzyme production in pharmacotherapy

Jurjen Duintjer Tebbens, Ctirad Matonoha, Andreas Matthios, Štěpán Papáček (2019)

Applications of Mathematics

Similarity:

A pharmacodynamic model introduced earlier in the literature for in silico prediction of rifampicin-induced CYP3A4 enzyme production is described and some aspects of the involved curve-fitting based parameter estimation are discussed. Validation with our own laboratory data shows that the quality of the fit is particularly sensitive with respect to an unknown parameter representing the concentration of the nuclear receptor PXR (pregnane X receptor). A detailed analysis of the influence...

Set-membership identifiability of nonlinear models and related parameter estimation properties

Carine Jauberthie, Louise Travé-Massuyès, Nathalie Verdière (2016)

International Journal of Applied Mathematics and Computer Science

Similarity:

Identifiability guarantees that the mathematical model of a dynamic system is well defined in the sense that it maps unambiguously its parameters to the output trajectories. This paper casts identifiability in a set-membership (SM) framework and relates recently introduced properties, namely, SM-identifiability, μ-SM-identifiability, and ε-SM-identifiability, to the properties of parameter estimation problems. Soundness and ε-consistency are proposed to characterize these problems and...

Numerical methods for linear minimax estimation

Norbert Gaffke, Berthold Heiligers (2000)

Discussiones Mathematicae Probability and Statistics

Similarity:

We discuss two numerical approaches to linear minimax estimation in linear models under ellipsoidal parameter restrictions. The first attacks the problem directly, by minimizing the maximum risk among the estimators. The second method is based on the duality between minimax and Bayes estimation, and aims at finding a least favorable prior distribution.

Identification of parametric models with a priori knowledge of process properties

Krzysztof B. Janiszowski, Paweł Wnuk (2016)

International Journal of Applied Mathematics and Computer Science

Similarity:

An approach to estimation of a parametric discrete-time model of a process in the case of some a priori knowledge of the investigated process properties is presented. The knowledge of plant properties is introduced in the form of linear bounds, which can be determined for the coefficient vector of the parametric model studied. The approach yields special biased estimation of model coefficients that preserves demanded properties. A formula for estimation of the model coefficients is derived...

Variance function estimation via model selection

Teresa Ledwina, Jan Mielniczuk (2010)

Applicationes Mathematicae

Similarity:

The problem of estimating an unknown variance function in a random design Gaussian heteroscedastic regression model is considered. Both the regression function and the logarithm of the variance function are modelled by piecewise polynomials. A finite collection of such parametric models based on a family of partitions of support of an explanatory variable is studied. Penalized model selection criteria as well as post-model-selection estimates are introduced based on Maximum Likelihood...

Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with a moving measurement window

Kazimierz Duzinkiewicz (2006)

International Journal of Applied Mathematics and Computer Science

Similarity:

The paper considers a set membership joint estimation of variables and parameters in complex dynamic networks based on parametric uncertain models and limited hard measurements. A recursive estimation algorithm with a moving measurement window is derived that is suitable for on-line network monitoring. The window allows stabilising the classic recursive estimation algorithm and significantly improves estimate tightness. The estimator is validated on a case study regarding a water distribution...

A simplified treatment of the restricted analysis of a slightly disproportionate factorial experiment.

José M. Prieto, José M. Caridad (1988)

Qüestiió

Similarity:

This paper considers a procedure to obtain effect estimators in the least squares analysis of a slightly disproportionate factorial design when a sample survey is made of the results of an extensive experiment. Explicit formulae have been found for the restricted estimators and their variances, when the constraints normally imposed upon a proportional model are used. In addition, an approximate analysis of the original model is used to perform that estimation, and an approximate analysis...

Nonlinear Bayesian state filtering with missing measurements and bounded noise and its application to vehicle position estimation

Lenka Pavelková (2011)

Kybernetika

Similarity:

The paper deals with parameter and state estimation and focuses on two problems that frequently occur in many practical applications: (i) bounded uncertainty and (ii) missing measurement data. An algorithm for the state estimation of the discrete-time non-linear state space model whose uncertainties are bounded is proposed. The algorithm also copes with situations when some measurements are missing. It uses Bayesian approach and evaluates maximum a posteriori probability (MAP) estimates...