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Standard spot return/forward premium regressions have long been known to provide a strong rejection of unbiasedness.
The proposed FIR filter is shown to have good inherent properties such as unbiasedness and deadbeat.
The unbiasedness of these estimators assures good estimation for large samples, but not for small samples.
The unbiasedness condition, however, does not guarantee "good estimate" [8].
Accuracy consists of precision and unbiasedness.
Two levels of weights can be utilized to achieve unbiasedness and to gain efficiency.
Very secure.
Convergence results and unbiasedness properties have been proved for this estimator in a previous work.
Precision is dealt with by statistical methods, but for unbiasedness one needs expert judgment.
Its Moran Coefficient based estimators exhibit statistical properties of unbiasedness, efficiency, and consistency.
However, their application to non-Gaussian data introduces difficulties in the analysis in conjunction with low robustness or unbiasedness.
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