We address this problem using a subclass of Anderson's (1973) linear covariance models and model several covariance matrices using linear combinations of known ...
Modeling the covariance matrix of multivariate longitudinal data is more challenging as compared to its univariate counterpart due to the presence of ...
Modeling the covariance matrix of multivariate longitudinal data is more challenging as compared to its univariate counterpart due to the presence of ...
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Bibliographic details on Modeling the Cholesky factors of covariance matrices of multivariate longitudinal data.
Dec 14, 2015 · Modeling the covariance matrix of multivariate longitudinal data is more challenging as compared to its univariate counterpart due to the ...
Jul 8, 2019 · Several studies have been conducted to solve these restrictions using modified Cholesky decomposition (MCD) and linear covariance models.
Pourahmadi (1999) proposed to dynamically model the covariance matrices by using the modified Cholesky decomposition (see also, Pourahmadi. (2007); Pan and ...
A new nested Cholesky decomposition and estimation for ...
www.researchgate.net › publication › 30...
In this paper, we propose a nested modified Cholesky decomposition for modeling the covariance structure in multivariate longitudinal data analysis.
The major difficulties in estimating a large covariance matrix are the high dimen- sionality and the positive definiteness constraint.