Understanding resident mobility in Milan through independent component analysis of Telecom Italia mobile usage data

DOI10.1214/16-AOAS913zbMath1400.62343MaRDI QIDQ312926

Haipeng Shen, Paolo Zanini, Young K. Truong

Publication date: 9 September 2016

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

Full work available at URL: https://projecteuclid.org/euclid.aoas/1469199894

zbMATH Keywords

periodogramWhittle likelihoodurban planningmobile phone trafficspatial stochastic processes

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to social sciences (62P25)

Uses Software

• R
• Rcpp
• ProDenICA

Cites Work

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• A General Probabilistic Model for Group Independent Component Analysis and Its Estimation Methods
• Independent Component Analysis Involving Autocorrelated Sources With an Application to Functional Magnetic Resonance Imaging
• Automatic Local Smoothing for Spectral Density Estimation
• Statistics for Spatial Data
• Consistent independent component analysis and prewhitening
• On the estimation of the spectral density for continuous spatial processes