Separable factor analysis with applications to mortality data

DOI10.1214/13-AOAS694zbMath1454.62185arXiv1211.3813OpenAlexW2057846413WikidataQ30876237 ScholiaQ30876237MaRDI QIDQ2453659

Peter D. Hoff, Bailey K. Fosdick

Publication date: 10 June 2014

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

Full work available at URL: https://arxiv.org/abs/1211.3813

zbMATH Keywords

Kronecker productimputationBayesian estimationmultiway dataarray normal

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15)

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Uses Software

• Human Mortality

Cites Work

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• Tensor Decompositions and Applications
• Modeling and Forecasting U.S. Mortality
• Horseshoes in multidimensional scaling and local kernel methods
• Transposable regularized covariance models with an application to missing data imputation
• EM algorithms for ML factor analysis
• An eight-parameter model of human mortality. The single decrement case
• On the forecasting of mortality reduction factors
• Lee-Carter mortality forecasting with age-specific enhancement.
• Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion
• Maximum likelihood factor analysis with rank-deficient sample covariance matrices
• Some contributions to maximum likelihood factor analysis
• Bayesian graphical Lasso models and efficient posterior computation
• Separable covariance arrays via the Tucker product, with applications to multivariate relational data
• Sparse Bayesian infinite factor models
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Bayesian Inference for General Gaussian Graphical Models With Application to Multivariate Lattice Data
• The decomposition of multitrait-multimethod matrices
• Lee–Carter Mortality Forecasting: A Parallel Generalized Linear Modelling Approach for England and Wales Mortality Projections
• Bayesian analysis of matrix normal graphical models
• Some matrix-variate distribution theory: Notational considerations and a Bayesian application
• A Multilinear Singular Value Decomposition
• Smoothing and forecasting mortality rates
• Bayesian Selection on the Number of Factors in a Factor Analysis Model
• A Reference Bayesian Test for Nested Hypotheses and its Relationship to the Schwarz Criterion
• High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
• Applied Multiway Data Analysis
• Space–Time Covariance Functions
• VI.—The Estimation of Factor Loadings by the Method of Maximum Likelihood
• Maximum Likelihood Estimation of Misspecified Models
• Longevity studies based on kernel hazard estimation

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