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  • We describe efficient algorithms for computing solutions of numerically exacting parts of used complicated polynomial regression tasks. In particular, we use a numerically stable way of generating the values of normalized orthogonal polynomials on a discrete set points; we use „the Arnoldi algorithm with reorthogonalization“, which is the key ingredient of our approach. The generated vectors can then be considered orthogonal also on finite precision arithmetic (up to a small inaccuracy proportional to machine precision). We then use the special algebraic structure of the covariance matrix to find algebraically the inversion of the matrix of the system of normal equations. Therefore, we do not need to compute numerically the inversion of the covariance matrix and we do not even need to solve the system of normal equations numerically. Some consequences of putting the algorithms mentioned into the practice are discussed.
  • We describe efficient algorithms for computing solutions of numerically exacting parts of used complicated polynomial regression tasks. In particular, we use a numerically stable way of generating the values of normalized orthogonal polynomials on a discrete set points; we use „the Arnoldi algorithm with reorthogonalization“, which is the key ingredient of our approach. The generated vectors can then be considered orthogonal also on finite precision arithmetic (up to a small inaccuracy proportional to machine precision). We then use the special algebraic structure of the covariance matrix to find algebraically the inversion of the matrix of the system of normal equations. Therefore, we do not need to compute numerically the inversion of the covariance matrix and we do not even need to solve the system of normal equations numerically. Some consequences of putting the algorithms mentioned into the practice are discussed. (en)
Title
  • Note on generating orthogonal polynomials and their application in solving complicated polynomial regression tasks
  • Note on generating orthogonal polynomials and their application in solving complicated polynomial regression tasks (en)
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  • Note on generating orthogonal polynomials and their application in solving complicated polynomial regression tasks
  • Note on generating orthogonal polynomials and their application in solving complicated polynomial regression tasks (en)
skos:notation
  • RIV/00209805:_____/10:#0000123!RIV11-GA0-00209805
http://linked.open...avai/riv/aktivita
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  • I, P(GAP304/10/0868), P(NS9812), V, Z(AV0Z10300504), Z(AV0Z10750506)
http://linked.open...iv/cisloPeriodika
  • J10
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  • 275158
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  • RIV/00209805:_____/10:#0000123
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  • polynomial regression, orthogonalization, numerical mathods, markers, biomarkers (en)
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  • IN - Indická republika
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  • [6774226D0643]
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  • International journal of mathematics and computation
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  • 7
http://linked.open...iv/tvurceVysledku
  • Vojtěšek, Bořivoj
  • Bouchal, Pavel
  • Knížek, J.
  • Nenutil, Rudolf
http://linked.open...n/vavai/riv/zamer
issn
  • 0974-5718
number of pages
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