Stochastic optimization algorithms of a Bayesian design criterion for Bayesian parameter estimation of nonlinear regression models: Application in pharmacokinetics
DOI10.1016/S0025-5564(97)00017-5zbMath0877.62030OpenAlexW2079333735WikidataQ52259280 ScholiaQ52259280MaRDI QIDQ1366975
Publication date: 16 December 1997
Published in: Mathematical Biosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0025-5564(97)00017-5
information criterionadaptive samplingpseudogradient algorithmsKiefer-WolfowitzBayesian design criterion
Applications of statistics to biology and medical sciences; meta analysis (62P10) Optimal statistical designs (62K05) Bayesian inference (62F15) General nonlinear regression (62J02) Numerical optimization and variational techniques (65K10) Stochastic programming (90C15)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A Mathematical Theory of Communication
- Optimal Bayesian experimental design for linear models
- Incorporating prior parameter uncertainty in the design of sampling schedules for pharmacokinetic parameter estimation experiments
- Qualitative and quantitative experiment design for phenomenological models - a survey
- Discrete approximations to continuous density functions that are \(L_ 1\) optimal
- Discrete approximation of multivariate densities with application to Bayesian estimation
- Robust experiment design via stochastic approximation
- Nonparametric EM algorithms for estimating prior distributions
- Expected information as ecpected utility
- Bayesian experimental design: A review
- Penalty function methods for constrained stochastic approximation
- Pseudogradient adaptation and training algorithms
- Adaption and learning in automatic systems. Translated by Z. J. Nikolic
- Optimal Design via Curve Fitting of Monte Carlo Experiments
- On a Measure of the Information Provided by an Experiment
- Accelerated Stochastic Approximation
- Once more: optimal experimental design for regression models (with discussion)
- On sampling controlled stochastic approximation
- Acceleration of Stochastic Approximation by Averaging
- A maximum likelihood estimation method for random coefficient regression models
- Population Pharmacokinetic/Pharmacodynamic Methodology and Applications: A Bibliography
- Uncertainty, Information, and Sequential Experiments
- The use of prior distributions in the design of experiments for parameter estimation in non-linear situations
- A Simplex Method for Function Minimization
- Stochastic Estimation of the Maximum of a Regression Function
- A Stochastic Approximation Method
This page was built for publication: Stochastic optimization algorithms of a Bayesian design criterion for Bayesian parameter estimation of nonlinear regression models: Application in pharmacokinetics
