A robust outlier identification algorithm for mixed continuous-ordinal data that extends the Minimum Covariance Determinant estimator to latent Gaussian models for ordinals, supported by a breakdown theorem and simulation results.
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Introduces a robust fuzzy clustering approach for cellwise outliers that leverages cluster-specific variable relationships to detect and correct anomalous cells while controlling assignment fuzziness.
FAMM approximates full MM-estimation via weighted least squares to speed up outlier-robust model selection while preserving performance and satisfying consistency conditions.
A Hidden Markov Model on STFT-derived spectral features from welding current signals identifies three temporally coherent arc regimes: transient, stable, and extinction.
Survey of thinning-based INARMA models for count random fields on regular 2D grids, covering thinning operators, model orders, and unilateral/multilateral structures.
citing papers explorer
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A unified approach to outlier identification for mixed-type data
A robust outlier identification algorithm for mixed continuous-ordinal data that extends the Minimum Covariance Determinant estimator to latent Gaussian models for ordinals, supported by a breakdown theorem and simulation results.
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Robust fuzzy clustering with cellwise outliers
Introduces a robust fuzzy clustering approach for cellwise outliers that leverages cluster-specific variable relationships to detect and correct anomalous cells while controlling assignment fuzziness.
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Fast Approximate MM-Estimation for Outlier Robust Model Selection
FAMM approximates full MM-estimation via weighted least squares to speed up outlier-robust model selection while preserving performance and satisfying consistency conditions.
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A Hidden Markov Framework for Physically Interpretable Arc Stability Dynamics in Welding Systems
A Hidden Markov Model on STFT-derived spectral features from welding current signals identifies three temporally coherent arc regimes: transient, stable, and extinction.
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INARMA Models for Count Random Fields -- a Survey
Survey of thinning-based INARMA models for count random fields on regular 2D grids, covering thinning operators, model orders, and unilateral/multilateral structures.