Efficient Monte Carlo computation of Fisher information matrix using prior information
From MaRDI portal
Publication:962252
DOI10.1016/j.csda.2009.09.018zbMath1464.62052OpenAlexW1990136720MaRDI QIDQ962252
James C. Spall, Sonjoy Das, Roger G. Ghanem
Publication date: 6 April 2010
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2009.09.018
Related Items
Computing and estimating information matrices of weak ARMA models, A robust solution of a statistical inverse problem in multiscale computational mechanics using an artificial neural network
Cites Work
- Unnamed Item
- Unnamed Item
- An improved method for the computation of maximum likelihood estimates for multinomial overdispersion models
- An alternative inverse Gaussian distribution
- Principal whitened gradient for information geometry
- On the resultant property of the Fisher information matrix of a vector ARMA process
- Adaptive stochastic approximation by the simultaneous perturbation method
- Asymptotic Sampling Distribution for Polynomial Chaos Representation from Data: A Maximum Entropy and Fisher Information Approach
- Estimation and tests of hypotheses for the initial mean and covariance in the kalman filter model
- Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
- Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
- Prediction Intervals for Artificial Neural Networks
- Introduction to Stochastic Search and Optimization
- CramÉr–Rao Bounds for Multiple Poles and Coefficients of Quasi-Polynomials in Colored Noise
- Feedback and Weighting Mechanisms for Improving Jacobian Estimates in the Adaptive Simultaneous Perturbation Algorithm
- Elements of Information Theory
- Linear Statistical Inference and its Applications
- An invariant form for the prior probability in estimation problems
- Filtering, predictive, and smoothing Cramér-Rao bounds for discrete-time nonlinear dynamic systems