Statistical paleoclimate reconstructions via Markov random fields

DOI10.1214/14-AOAS794zbMath1454.62443arXiv1309.6702OpenAlexW3105683880MaRDI QIDQ2349575

Dominique Guillot, Julien Emile-Geay, Bala Rajaratnam

Publication date: 17 June 2015

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1309.6702

zbMATH Keywords

model selectionsparsityMarkov random fieldscovariance matrix estimationclimate reconstructionspseudoproxies

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Applications of statistics to environmental and related topics (62P12) Climate science and climate modeling (86A08)

Related Items (4)

A note on covariance estimation in the unbiased estimator of risk framework ⋮ Evaluating Proxy Influence in Assimilated Paleoclimate Reconstructions—Testing the Exchangeability of Two Ensembles of Spatial Processes ⋮ Bayesian analysis of the covariance matrix of a multivariate normal distribution with a new class of priors ⋮ Efficient reconstructions of Common Era climate via integrated nested Laplace approximations

Uses Software

• RegEM
• VanHuffel
• glasso
• ElemStatLearn

Cites Work

• Sparse inverse covariance estimation with the graphical lasso
• An Analysis of the Total Least Squares Problem
• Flexible covariance estimation in graphical Gaussian models
• Lectures on the theory of estimation of many parameters
• Bootstrap procedures under some non-i.i.d. models
• Regularization methods for large-scale problems
• Hyper Markov laws in the statistical analysis of decomposable graphical models
• Wishart distributions for decomposable graphs
• The EM Algorithm and Extensions, 2E
• Regularization by Truncated Total Least Squares
• The Value of Multiproxy Reconstruction of Past Climate
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Ridge Regression: Applications to Nonorthogonal Problems
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