Parsimonious Covariance Matrix Estimation for Longitudinal Data
From MaRDI portal
Publication:4468512
DOI10.1198/016214502388618942zbMath1041.62044OpenAlexW1965752946MaRDI QIDQ4468512
No author found.
Publication date: 10 June 2004
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1198/016214502388618942
Estimation in multivariate analysis (62H12) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40) Analysis of variance and covariance (ANOVA) (62J10)
Related Items
Bayesian stochastic search for VAR model restrictions, Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models, Bayesian geoadditive seemingly unrelated regression, A class of shrinkage priors for the dependence structure in longitudinal data, Stochastic model specification search for Gaussian and partial non-Gaussian state space models, Unnamed Item, Regularization in statistics, Dynamic factors in periodic time-varying regressions with an application to hourly electricity load modelling, Bayesian modeling of the dependence in longitudinal data via partial autocorrelations and marginal variances, Bayesian Approaches to Shrinkage and Sparse Estimation, Testing diagonality of high-dimensional covariance matrix under non-normality, Robust variable selection in semiparametric mixed effects longitudinal data models, Bayesian nonstationary and nonparametric covariance estimation for large spatial data (with discussion), Bayesian nonparametric density autoregression with lag selection, Bayesian model selection for logistic regression models with random intercept, Unnamed Item, Sparse permutation invariant covariance estimation, Covariance estimation: the GLM and regularization perspectives, Sparse seemingly unrelated regression modelling: applications in finance and econometrics, Dynamic dependence networks: Financial time series forecasting and portfolio decisions, Posterior graph selection and estimation consistency for high-dimensional Bayesian DAG models, Efficient Bayesian regularization for graphical model selection, A Bayesian regression model for multivariate functional data, Bayesian estimation of random effects models for multivariate responses of mixed data, Cholesky-GARCH models with applications to finance, Variable selection for market basket analysis, Sparse estimation of large covariance matrices via a nested Lasso penalty, A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data, Model uncertainty, Sparse variational analysis of linear mixed models for large data sets, Bayesian estimation and stochastic model specification search for dynamic survival models, Modelling covariance matrices by the trigonometric separation strategy with application to hidden Markov models, Constructing priors based on model size for nondecomposable Gaussian graphical models: a simulation based approach, A double varying-coefficient modeling approach for analyzing longitudinal observations, A nonparametric test for block-diagonal covariance structure in high dimension and small samples, Implicit copulas from Bayesian regularized regression smoothers, Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction, Joint Variable Selection for Fixed and Random Effects in Linear Mixed-Effects Models, Compressed covariance estimation with automated dimension learning, Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions, Bayesian model determination for multivariate ordinal and binary data, Bayesian estimation of large precision matrix based on Cholesky decomposition, Adaptive hierarchical priors for high-dimensional vector autoregressions, Sparsistency and rates of convergence in large covariance matrix estimation, Nonparametric Modeling of Longitudinal Covariance Structure in Functional Mapping of Quantitative Trait Loci, Nonparametric seemingly unrelated regression, GIBBS SAMPLERS FOR A SET OF SEEMINGLY UNRELATED REGRESSIONS, Modeling the density of US yield curve using Bayesian semiparametric dynamic Nelson-Siegel model, Bayesian analysis of multivariate stochastic volatility with skew return distribution