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Separation-based parameterization strategies for estimation of restricted covariance matrices in multivariate model systems

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  • Saxena, Shobhit
  • Bhat, Chandra R.
  • Pinjari, Abdul Rawoof

Abstract

Many multivariate model systems involve the estimation of a covariance matrix that must be positive-definite. A common strategy to ensure positive definiteness of the covariance matrix is through the use of a Cholesky parameterization of the covariance matrix. However, several model systems require imposing restrictions on the elements of the covariance elements. For instance, modelling systems may require fixing some (or all) of the diagonal elements in the covariance matrix to unity due to identification considerations. However, imposing such restrictions using the traditional Cholesky decomposition approach is not feasible and requires the additional parameterization of the Cholesky elements.

Suggested Citation

  • Saxena, Shobhit & Bhat, Chandra R. & Pinjari, Abdul Rawoof, 2023. "Separation-based parameterization strategies for estimation of restricted covariance matrices in multivariate model systems," Journal of choice modelling, Elsevier, vol. 47(C).
    • Handle: RePEc:eee:eejocm:v:47:y:2023:i:c:s175553452300012x
    DOI: 10.1016/j.jocm.2023.100411
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