Robust estimators and a data-driven tuning algorithm are introduced for inflated beta regression to reduce outlier impact while retaining model interpretability.
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Categorical trajectories are mapped to multivariate binary indicator functions and reduced via functional PCA, with consistent mean and covariance estimators under continuity in probability.
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Robust inference in inflated beta regression
Robust estimators and a data-driven tuning algorithm are introduced for inflated beta regression to reduce outlier impact while retaining model interpretability.
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Statistical description and dimension reduction of continuous time categorical trajectories with multivariate functional principal components
Categorical trajectories are mapped to multivariate binary indicator functions and reduced via functional PCA, with consistent mean and covariance estimators under continuity in probability.