Functional wavelet-based modelling of dependence between lupus and stress

DOI10.1007/S11009-014-9424-5zbMath1398.62332OpenAlexW1968830413MaRDI QIDQ905237

Ana M. Aguilera, Manuel Escabias, Mariano J. Valderrama, Francisco A. Ocaña

Publication date: 14 January 2016

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10481/72908

zbMATH Keywords

functional regressionwavelet approximationfunctional PCAlupus

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (1)

Stochastic modeling of random access memories reset transitions

Uses Software

• fda (R)

Cites Work

• Unnamed Item
• Functional linear regression analysis for longitudinal data
• Computational considerations in functional principal component analysis
• Discussion of different logistic models with functional data. Application to systemic lupus erythematosus
• Forecasting with unequally spaced data by a functional principal component approach
• Wavelet methods for continuous-time prediction using Hilbert-valued autoregressive processes
• Functional linear model
• Penalized spline approaches for functional logit regression
• Penalized PCA approaches for B-spline expansions of smooth functional data
• Functional data analysis.
• Forecasting Pollen Concentration by a Two-Step Functional Model
• Orthonormal bases of compactly supported wavelets
• Regression Analysis for a Functional Response
• Principal component models for sparse functional data
• Principal component estimation of functional logistic regression: discussion of two different approaches

This page was built for publication: Functional wavelet-based modelling of dependence between lupus and stress