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Constrained Cramér–Rao Lower Bound in Errors-In Variables (EIV) models: Revisited

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  • Al-Sharadqah, A.
  • Ho, K.C.

Abstract

The Constrained Cramér–Rao Lower Bound (CCRB) works only for an unbiased estimator. The CCRB of Stoica and Ng (1998) is revisited and generalized. The bound is applied to two applications in the nonlinear EIV models.

Suggested Citation

  • Al-Sharadqah, A. & Ho, K.C., 2018. "Constrained Cramér–Rao Lower Bound in Errors-In Variables (EIV) models: Revisited," Statistics & Probability Letters, Elsevier, vol. 135(C), pages 118-126.
    • Handle: RePEc:eee:stapro:v:135:y:2018:i:c:p:118-126
    DOI: 10.1016/j.spl.2017.10.009
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    References listed on IDEAS

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    1. Chernov, N. & Lesort, C., 2004. "Statistical efficiency of curve fitting algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 47(4), pages 713-728, November.
    2. Chernov, N. & Sapirstein, P.N., 2008. "Fitting circles to data with correlated noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5328-5337, August.
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