Discriminant and cluster analysis for Gaussian stationary processes: local linear fitting approach

DOI10.1080/10485250410001656453zbMath1076.62063OpenAlexW2115600696MaRDI QIDQ4831085

Sonia Pértega, José Antonio Vilar

Publication date: 20 December 2004

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485250410001656453

zbMATH Keywords

Discriminant AnalysisCluster AnalysisLinear Gaussian ProcessLocal Polynomial FitSpectral Disparity Measure

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric tolerance and confidence regions (62G15) Stationary stochastic processes (60G10) Inference from stochastic processes and spectral analysis (62M15)

Related Items

Comparing several parametric and nonparametric approaches to time series clustering: a simulation study ⋮ Clustering of time series using quantile autocovariances ⋮ Time series clustering using the total variation distance with applications in oceanography ⋮ Temporal clustering of time series via threshold autoregressive models: application to commodity prices ⋮ Time series clustering based on nonparametric multidimensional forecast densities ⋮ Unexpected properties of bandwidth choice when smoothing discrete data for constructing a functional data classifier ⋮ Non-linear time series clustering based on non-parametric forecast densities ⋮ Robust fuzzy clustering based on quantile autocovariances ⋮ Quantile autocovariances: a powerful tool for hard and soft partitional clustering of time series ⋮ Classifying time series data: a nonparametric approach ⋮ Functional sufficient dimension reduction for functional data classification ⋮ Clustering brain signals: a robust approach using functional data ranking

Cites Work

• Unnamed Item
• Curves discrimination: a nonparametric functional approach
• Multivariate regression estimation: Local polynomial fitting for time series
• Clusters of time series
• Asymptotic theory of statistical inference for time series
• A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS
• Disoominkfrcn between gaussian time series based on their spectral differences
• Automatic Local Smoothing for Spectral Density Estimation
• DISCRIMINANT ANALYSIS FOR STATIONARY VECTOR TIME SERIES
• Discrimination of AR, MA and ARMA time series models
• Discriminant analysis for non-gaussian vector stationary processes
• Nonparametric approach for discriminant analysis in time series
• A significance test for classifying arma models
• An asymptotic simultaneous diagonalization procedure for pattern recognition
• On the Asymptotic Optimality of Spectral Analysis for Testing Hypotheses About Time Series