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Econometric applications of positive rank-one modifications of the symmetric factorization of a positive semi-definite matrix

Author

Listed:
  • Enrique Sentana

    (CEMFI, Casado del Alisal 5, E-28014 Madrid, Spain)

Abstract

We present an algorithm for updating the symmetric factorization of a positive semi-definite matrix after a positive rank-one modification, which works even if the matrices involved do not have full rank. Recursive least squares and factor analysis provide two important econometric applications. An illustrative simulation shows that it can be potentially very useful in recursive situations.

Suggested Citation

  • Enrique Sentana, 1999. "Econometric applications of positive rank-one modifications of the symmetric factorization of a positive semi-definite matrix," Spanish Economic Review, Springer;Spanish Economic Association, vol. 1(1), pages 79-90.
    • Handle: RePEc:spr:specre:v:1:y:1999:i:1:p:79-90
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    Cited by:

    1. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.

    More about this item

    Keywords

    Recursive least squares; factor analysis; Cholesky decomposition; multicollinearity;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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