Abstract
It is well-known that singularity of the dispersion matrix in a Gauss-Markov model may have various consequences, which remain obscure in models furnished with a regular dispersion matrix (see e.g. Rao [9] or Zyskind [16]). Roughly speaking, these consequences appear in form of inherent restrictions on the vector of observations or parameters (or both).
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Nordström, K. (1985). On a Decomposition of the Singular Gauss-Markov Model. In: Caliński, T., Klonecki, W. (eds) Linear Statistical Inference. Lecture Notes in Statistics, vol 35. Springer, New York, NY. https://doi.org/10.1007/978-1-4615-7353-1_19
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DOI: https://doi.org/10.1007/978-1-4615-7353-1_19
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