Autoregressive mixture models for clustering time series
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Publication:6134638
DOI10.1111/jtsa.12644arXiv2006.16539OpenAlexW4214651176MaRDI QIDQ6134638
Publication date: 22 August 2023
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.16539
Wishart distributionexpectation-maximizationtime series clusteringYule-Walkerlatent variable modelling
Cites Work
- Unnamed Item
- Large Sample Properties of Generalized Method of Moments Estimators
- Longitudinal data analysis using generalized linear models
- The Wishart autoregressive process of multivariate stochastic volatility
- The hierarchical spectral merger algorithm: a new time series clustering procedure
- Properties of the singular, inverse and generalized inverse partitioned Wishart distributions
- Time series: theory and methods.
- Estimating the dimension of a model
- Time series clustering via community detection in networks
- Efficient inference for autoregressive coefficients in the presence of trends
- On the convergence of the spectrum of finite order approximations of stationary time series
- Clustering of time series data -- a survey
- Autoregressive coefficient estimation in nonparametric analysis
- A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS
- Random effects mixture models for clustering electrical load series
- Regression and time series model selection in small samples
- Mixtures of marginal models
- A Limited Memory Algorithm for Bound Constrained Optimization
- Communication-Efficient Distributed Statistical Inference
- Clustering Multiple Time Series with Structural Breaks
- Time‐series clustering via quasi U‐statistics
- Biological applications of time series frequency domain clustering
- Time Series Clustering and Classification
- A Large-Sample Test for the Goodness of Fit of Autoregressive Schemes
- A new look at the statistical model identification
- Regularized matrix data clustering and its application to image analysis