1967
DOI: 10.1007/bf02531883
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Studies with generalized matrix algebra

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Cited by 9 publications
(13 citation statements)
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“…
The classical estimation procedure according to Gauss uses the inversion of nonsingular matrices. The author has earlier presented a number of papers concerning the stochastical estimation with the use of singular inverses (Bjerhammar, 1948(Bjerhammar, -1958.The present paper gives a review of the earlier contributions and an application to selected problems. For a geodetic network all points can be considered unknown and an estimate with a generalized inverse gives the minimum variance of the observations as well as the unknowns.
…”
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confidence: 97%
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“…
The classical estimation procedure according to Gauss uses the inversion of nonsingular matrices. The author has earlier presented a number of papers concerning the stochastical estimation with the use of singular inverses (Bjerhammar, 1948(Bjerhammar, -1958.The present paper gives a review of the earlier contributions and an application to selected problems. For a geodetic network all points can be considered unknown and an estimate with a generalized inverse gives the minimum variance of the observations as well as the unknowns.
…”
mentioning
confidence: 97%
“…The classical estimation procedure according to Gauss uses the inversion of nonsingular matrices. The author has earlier presented a number of papers concerning the stochastical estimation with the use of singular inverses (Bjerhammar, 1948(Bjerhammar, -1958.…”
mentioning
confidence: 99%
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“…XGX X. We therefore define a one-condition generalized inverse (abbreviated to g-inverse) as any matrix X g' satisfying (2) xx'x x. Such a matrix is, of course, nonunique and for convenience we write G X to stand for "G is some g-inverse of X."…”
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confidence: 99%
“…Such a matrix is, of course, nonunique and for convenience we write G X to stand for "G is some g-inverse of X." The algebraic properties and statistical applications of this class of g-inverses have been studied in some detail by Bjerhammar [2], Bose [3], Rao [9] and Rohde [13].…”
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confidence: 99%