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Full-Text Articles in Physical Sciences and Mathematics
Analysis Of Repeated Measures Data Under Circular Covariance, Andrew Montgomery Hartley
Analysis Of Repeated Measures Data Under Circular Covariance, Andrew Montgomery Hartley
Mathematics & Statistics Theses & Dissertations
Circular covariance is important in modelling phenomena in epidemiological, communications and numerous physical contexts. We introduce and develop a variety of methods which make it a more versatile tool. First, we present two classes of estimators for use in the presence of missing observations. Using simulations, we show that the mean squared errors of the estimators of one of these classes are smaller than those of the Maximum Likelihood (ML) estimators under certain conditions. Next, we propose and discuss a parsimonious, autoregressive type of circular covariance structure which involves only two parameters. We specify ML and other types of estimators …
Analysis Of Growth Curves Under Some Special Covariance Structures, Shobha Prabhala
Analysis Of Growth Curves Under Some Special Covariance Structures, Shobha Prabhala
Mathematics & Statistics Theses & Dissertations
In this dissertation we consider the growth curve or generalized MANOVA model in its most general form given by and develop statistical methodology for analyzing data using this model. Here g represents the number of groups, Yij is the observation matrix, ξ is a matrix of unknown parameters, Ai is a known matrix of rank g, and Bij is a matrix of rank k. Further, the rows of the error matrix ∈ij are independent and each distributed as Npij (0, Σij).This model accommodates different kinds of unbalanced data, such as, monotone data, data …