Clustering time series by linear dependency
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Publication:2329790
DOI10.1007/s11222-018-9830-6zbMath1430.62191OpenAlexW2892224330MaRDI QIDQ2329790
Publication date: 18 October 2019
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10016/32941
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05)
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Cites Work
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- Estimating the Number of Clusters in a Data Set Via the Gap Statistic
- Model-based clustering of categorical time series
- Comparing several parametric and nonparametric approaches to time series clustering: a simulation study
- Factor modeling for high-dimensional time series: inference for the number of factors
- Fuzzy clustering of time series in the frequency domain
- A periodogram-based metric for time series classification
- Time series clustering based on forecast densities
- Time series clustering and classification by the autoregressive metric
- Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
- Descriptive measures of multivariate scatter and linear dependence
- Comparison of non-stationary time series in the frequency domain
- Fuzzy clustering of time series using extremes
- Time series clustering with ARMA mixtures
- Quantile autocovariances: a powerful tool for hard and soft partitional clustering of time series
- Comparing clusterings -- an information based distance
- Clustering of time series using quantile autocovariances
- Non-linear time series clustering based on non-parametric forecast densities
- Factor models in high-dimensional time series: A time-domain approach
- Adaptive dissimilarity index for measuring time series proximity
- Clustering of time series data -- a survey
- Improved multivariate portmanteau test
- A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS
- Identifying a Simplifying Structure in Time Series
- Discrimination and Clustering for Multivariate Time Series
- Stochastic Limit Theory
- A Powerful Portmanteau Test of Lack of Fit for Time Series
- Forecasting Simultaneously High‐Dimensional Time Series: A Robust Model‐Based Clustering Approach
- Extreme value and cluster analysis of European daily temperature series
- Periodic Seasonal Reg-ARFIMA–GARCH Models for Daily Electricity Spot Prices
- Clustering High-Dimensional Time Series Based on Parallelism