Clustering Inference

We develop a likelihood-based weighted fuzzy c-means method for soft clustering under cluster imbalance, with consistent estimation, asymptotic normality, and valid inference. Its effectiveness is demonstrated in medical applications including single-cell RNA-seq and ADNI studies.