Analysis of variance with general errors and grouped and non-grouped data: Some iterative algorithms

Multilevel Analysis of Grouped and Longitudinal Data

Trimming algorithms for clustering contaminated grouped data and their robustness

We establish an affine equivariant, constrained heteroscedastic model and criterion with trimming for clustering contaminated, grouped data. We show existence of the m.l.e., propose a method for determining an appropriate constraint, and design a strategy for finding reasonable partitions. We finally compute breakdown points of the estimated parameters thereby showing asymptotic robustness of t...

Isotonic estimation for grouped data

A non-parametric estimator of a non-increasing density is found in a class of piecewise linear functions when the data consist only of counts. An EM-Algorithm for computing the estimator is developed, and the iterates in the algorithm are shown to converge to the maximum likelihood estimator. Potential applications to distance sampling models are described and illustrated with a numerical examp...

Network Inference from Grouped Data

In medical research, economics, and the social sciences data frequently appear as subsets of a set of objects. Over the past century a number of descriptive statistics have been developed to construct network structure from such data. However, these measures lack a generating mechanism that links the inferred network structure to the observed groups. To address this issue, we propose a modelbas...

Multivariate Analysis Tests Concerning EquicorrelationMatrices with Grouped Normal Data

This article considers three practical hypotheses involving the equicorrelation matrix for grouped normal data. We obtain statistics and computing formulae for common test procedures such as the score test and the likelihood ratio test. In addition, statistics and computing formulae are obtained for various small sample procedures as proposed in Skovgaard (2001). The properties of the tests for...