This letter illustrates simple assumptions for proving consistency of the maximum likelihood estimator under multivariate Gaussian and Student's t linear cluster-weighted models, which allow density estimation, clustering and linear regression analysis with continuous random predictors in presence of unobserved heterogeneity.
A note on the consistency of the maximum likelihood estimator under multivariate linear cluster-weighted models / Galimberti G; Soffritti G. - In: STATISTICS & PROBABILITY LETTERS. - ISSN 0167-7152. - ELETTRONICO. - 157:(2020), pp. 108630.1-108630.5. [10.1016/j.spl.2019.108630]
A note on the consistency of the maximum likelihood estimator under multivariate linear cluster-weighted models
Galimberti G;Soffritti G
2020
Abstract
This letter illustrates simple assumptions for proving consistency of the maximum likelihood estimator under multivariate Gaussian and Student's t linear cluster-weighted models, which allow density estimation, clustering and linear regression analysis with continuous random predictors in presence of unobserved heterogeneity.File in questo prodotto:
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