A flexible spatial autoregressive modelling framework for mixed covariates of multiple data types

DOI10.1080/03610918.2019.1626885zbMath1497.62255arXiv1811.02809OpenAlexW2963125570WikidataQ127661419 ScholiaQ127661419MaRDI QIDQ5082793

Tingting Huang, Shan-shan Wang, Hui-Wen Wang

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1811.02809

zbMATH Keywords

maximum likelihood estimationcompositional datafunctional dataspatial autoregressive modelilr transformationFPCA

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Inference from spatial processes (62M30) Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Functional data analysis (62R10)

Related Items (1)

A Spatial Durbin Model for Compositional Data

Uses Software

• fda (R)
• Arc_Mat

Cites Work

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