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Least distance method for a confluent model with homoskedasticity in the matrix columns and the right-hand side

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Abstract

The article investigates the most common particular case of a confluent regression model for a passive experiment in which the variance is different for different observation vectors and homoskedastic within each observation vector. The regression parameters are estimated by the least distance method. The results are illustrated with an econometric example.

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References

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Authors
  1. A. S. Mechenov
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Additional information

Translated from Prikladnaya Matematika i Informatika, No. 2, pp. 94–98, 1999.

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Mechenov, A.S. Least distance method for a confluent model with homoskedasticity in the matrix columns and the right-hand side. Comput Math Model 11, 299–304 (2000). https://doi.org/10.1007/BF02361135

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  • DOI: https://doi.org/10.1007/BF02361135

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