Approximations to the determinant term in gaussian maximum likelihood estimation of some spatial models

DOI10.1080/03610929308831013zbMath0800.62570OpenAlexW2146976706MaRDI QIDQ3137536

No author found.

Publication date: 1 November 1993

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929308831013

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Numerical computation of determinants (65F40) Probabilistic methods, stochastic differential equations (65C99)

Related Items

Computing efficient exact designs of experiments using integer quadratic programming ⋮ Approximate implementation of the logarithm of the matrix determinant in Gaussian process regression ⋮ Likelihood ratio tests of correlated multivariate samples ⋮ A randomized algorithm for approximating the log determinant of a symmetric positive definite matrix ⋮ Log-det approximation based on uniformly distributed seeds and its application to Gaussian process regression ⋮ Chebyshev approximation of log-determinants of spatial weight matrices ⋮ An \(O(N)\) parallel method of computing the log-Jacobian of the variable transformation for models with spatial interaction on a lattice ⋮ Fast maximum likelihood estimation of very large spatial autoregressive models: a characteristic polynomial approach. ⋮ Likelihood-based estimation for Gaussian MRFs ⋮ Performance contest between MLE and GMM for huge spatial autoregressive models ⋮ Nonintrusive approximation of parametrized limits of matrix power algorithms – application to matrix inverses and log-determinants ⋮ Monte Carlo estimates of the log determinant of large sparse matrices

Uses Software

• spatial

Cites Work

• Unnamed Item
• Unnamed Item
• First-order autoregressive models: A method for obtaining eigenvalues for weighting matrices
• Maximum likelihood estimation of models for residual covariance in spatial regression
• Exact maximum likelihood for incomplete data from a correlated gaussian process
• Estimation Methods for Models of Spatial Interaction
• ON STATIONARY PROCESSES IN THE PLANE
• Statistical Inference for Spatial Processes