Generalized sensitivities and optimal experimental design

DOI10.1515/jiip.2010.002zbMath1279.62089OpenAlexW2334390166WikidataQ57440333 ScholiaQ57440333MaRDI QIDQ2874435

Stacey L. Ernstberger, S. Dediu, Franz Kappel, Harvey Thomas Banks

Publication date: 30 January 2014

Published in: jiip (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/jiip.2010.002

zbMATH Keywords

design of experimentsFisher information matrixleast squares inverse problemssensitivity and generalized sensitivity functions

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Multivariate analysis (62H99) Numerical optimization and variational techniques (65K10) Sensitivity, stability, parametric optimization (90C31) Design techniques (robust design, computer-aided design, etc.) (93B51) Statistical aspects of information-theoretic topics (62B10)

Related Items (15)

A physiologically based model of vascular refilling during ultrafiltration in hemodialysis ⋮ Merging Mathematical and Physiological Knowledge: Dimensions and Challenges ⋮ Parameter Selection Methods in Inverse Problem Formulation ⋮ Inverse problem of shape identification from boundary measurement for Stokes equations: shape differentiability of Lagrangian ⋮ Generalized sensitivity functions for multiple output systems ⋮ Optimal design for parameter estimation in EEG problems in a 3D multilayered domain ⋮ Standard error computations for uncertainty quantification in inverse problems: asymptotic theory vs. bootstrapping ⋮ A model of vascular refilling with inflammation ⋮ Optimal design for dynamical modeling of pest populations ⋮ Practical identifiability and uncertainty quantification of a pulsatile cardiovascular model ⋮ Modelling and optimal control of immune response of renal transplant recipients ⋮ Using inverse problem methods with surveillance data in pneumococcal vaccination ⋮ Host immune responses that promote initial HIV spread ⋮ Estimation of probability distributions of parameters using aggregate population data: analysis of a CAR T-cell cancer model ⋮ Optimal design of non-equilibrium experiments for genetic network interrogation

Cites Work

• Stochastic and deterministic models for agricultural production networks
• Sensitivity of dynamical systems to parameters in a convex subset of a topological vector space
• Modelling and estimating uncertainty in parameter estimation
• Standard errors and confidence intervals in inverse problems: sensitivity and associated pitfalls
• Sensitivity functions and their uses in inverse problems
• Asymptotic Properties of Non-Linear Least Squares Estimators

This page was built for publication: Generalized sensitivities and optimal experimental design