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Chinese Physics C> 2007, Vol. 31> Issue(8) : 745-749 

Unbiased χ2 Estimator for Linear Function Fit Involving Correlated Data

  •  Institute of High Energy Physics, CAS, Beijing 100049, China

  • An unbiased factorized chi-square estimator is constructed to deal with the correlated data for linear function fit. The difference between the biased and unbiased chi-square fitting is expounded. In addition, the simplified R-value measurement is quoted to test the conclusion quantitatively.
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  • References

    [1] . D'Agostini G. Nucl. Instrum. Methods, 1994, A346: 3062. Takeuchi T. Prog. Thero. Phys., 1996, 123(Suppl.): 2473. MO X H, ZHU Y S. HEP NP, 2003, 27: 371(in Chinese)(莫晓虎，朱永生.高能物理.与核物理, 2003, 27: 371)4. MO X H. HEP NP, 2006, 30: 140-146(in Chinese)(莫晓虎.高能物理与核物理，2006, 30: 140-146)5. MO X H, ZHU Y S. HEP NP, 2003, 27: 747(in Chinese)(莫晓虎，朱永生.高能物理与核物理，2003, 27: 747)6. Bartel W et al(JADE Collab.). Phys. Lett., 1983, B129:1457. BAI J Z et al(BES Collab.). Phys. Rev. Lett., 2000, 84:5948. BAI J Z et al(BES Collab.). Phys. Rev. Lett., 2002, 88:1018029. Siegrist J L et al. Phys. Rev., 1982, D26: 969-99010. CERN Library. MINUIT Reference Manual, version 92.1,March 1992

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MO Xiao-Hu. Unbiased χ2 Estimator for Linear Function Fit Involving Correlated Data[J]. Chinese Physics C, 2007, 31(8): 745-749.
MO Xiao-Hu. Unbiased χ2 Estimator for Linear Function Fit Involving Correlated Data[J]. Chinese Physics C, 2007, 31(8): 745-749. shu
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Received: 2006-10-09
Revised: 2006-11-29
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Unbiased χ2 Estimator for Linear Function Fit Involving Correlated Data

    Corresponding author: MO Xiao-Hu,
  • Institute of High Energy Physics, CAS, Beijing 100049, China
  • Received Date: 2006-10-09
  • Accepted Date: 2006-11-29
  • Available Online: 2007-08-05

Abstract: An unbiased factorized chi-square estimator is constructed to deal with the correlated data for linear function fit. The difference between the biased and unbiased chi-square fitting is expounded. In addition, the simplified R-value measurement is quoted to test the conclusion quantitatively.

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