We study the role of partial autocorrelations in the reparameterization and parsimonious modeling of a covariance matrix. The work is motivated by and tries ...
We study the role of partial autocorrelations in the reparameterization and parsimonious modeling of a covariance matrix. The work is motivated by and tries ...
We study the role of partial autocorrelations in the reparameterization and parsimonious modeling of a covariance matrix. The work is motivated by and tries ...
Downloadable (with restrictions)! We study the role of partial autocorrelations in the reparameterization and parsimonious modeling of a covariance matrix.
We study the role of partial autocorrelations in the reparameterization and parsimonious modeling of a covariance matrix. The work is motivated by and tries ...
May 3, 2009 · We study the role of partial autocorrelations in the reparameterization and parsimonious modeling of a covariance matrix.
Abstract: The covariance matrix plays an important role in statistical inference, yet modeling a covariance matrix is often a difficult task in practice due ...
Su, L, and Daniels, M.J. (2015) Bayesian modeling of the covariance structure for irregular longitudinal data using the partial autocorrelation function. To ...
We model a covariance matrix in terms of its correspond- ing standard deviations and correlation matrix. We discuss two general modeling situations where this ...
MA Models, Partial Autocorrelation, Notational Conventions
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This lesson defines moving average terms. A moving average term in a time series model is a past error (multiplied by a coefficient).