Forecasting binary longitudinal data by a functional PC-ARIMA model

DOI10.1016/j.csda.2007.09.015zbMath1452.62691OpenAlexW2075565949MaRDI QIDQ1023652

Ana M. Aguilera, Manuel Escabias, Mariano J. Valderrama

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.09.015

zbMATH Keywords

logistic regressionfunctional principal component analysisARIMA modelling

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Inference from stochastic processes and prediction (62M20) Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Generalized linear models (logistic models) (62J12)

Related Items (4)

Variational Bayesian functional PCA ⋮ Forecasting Pollen Concentration by a Two-Step Functional Model ⋮ Testing linearity in semi-parametric functional data analysis ⋮ Editorial: Some recent trends in applied stochastic modeling and multidimensional data analysis

Uses Software

• fda (R)

Cites Work

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