Estimation and model selection for finite mixtures of Tukey’s g- &-h distributions

• Published in: Statistics and computing Vol. 35; no. 3; p. 67
• Main Authors: Zhan, Tingting, Yi, Misung, Peck, Amy R., Rui, Hallgeir, Chervoneva, Inna
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2025; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Asymptotic properties; Computer Science; Human tissues; Immunofluorescence; Kurtosis; Normal distribution; Original Paper; Parameter estimation; Performance evaluation; Probabilistic models; Probability and Statistics in Computer Science; Protein expression; Proteins; Quantiles; Skewness; Statistical analysis; Statistical models; Statistical Theory and Methods; Statistics and Computing/Statistics Programs; Quantile least Mahalanobis distance; Tukey’s; Finite mixtures; Indirect estimator; distribution; -; Cellular protein level; Tukey’s g- &-h distribution

A finite mixture of distributions is a popular statistical model, which is especially meaningful when the population of interest may include distinct subpopulations. This work is motivated by analysis of protein expression levels quantified using immunofluorescence immunohistochemistry assays of hum...