Results 121 to 130 of about 565 (145)

A Short Proof of the Cramér-Rao Inequality

Theory of Probability & Its Applications, 1961
A simple proof of the Cramer-Rao inequality which may be regarded as a basis of the theory of efficient estimations is presented.
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On Cramer‐Rao Type Intfgral Inequalities

Calcutta Statistical Association Bulletin, 1990
ABSTRACT: A brief but comprehensive survey of recent work in the area of Cramer‐Rao type integral inequalities leading to lower bounds for the risk of estimators in a Bayesian context is given.
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A Cramer-Rao Type Inequality for a Convex Loss Function

1988
For an unbiased estimator T for τ(θ) lower bounds for the risk ∫g(|Τ- τ(θ)|)dPθ are established. Some generalizations of Rao-Cramer inequality are included as special cases.
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Two quantum analogues of the large deviation Cramer-Rao inequality

Proceedings of 1994 IEEE International Symposium on Information Theory, 2002
Considers a family of probability distributions smoothly parametrized by a single parameter /spl Theta/ ranging over an open set /spl Theta/ in R. Under some regularity conditions, large deviation Cramer-Rao inequality holds. Two types of quantum Fisher information is introduced in the analysis. >
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An extension of the Cramér-Rao inequality for the sequential case

Trabajos de Estadistica y de Investigacion Operativa, 1979
Extensions of the Cramer-Rao inequality have been established by several authors. Among these, Wolfowitz [3] obtained a lower limit for the variance of an estimator when the sampling is performed through a sequential process. By extending the notion of regular estimator function as defined by Godambe [2], we establish an inequality that improves the ...
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The Fisher-information-based uncertainty relation, Cramer–Rao inequality and kinetic energy for theD-dimensional central problem

Journal of Physics A: Mathematical and Theoretical, 2007
The inequality , with L being the grand orbital quantum number, and its conjugate relation for (r2, p−2) are shown to be fulfilled in the D-dimensional central problem. Their use has allowed us to improve the Fisher-information-based uncertainty relation (IρIγ≥ const) and the Cramer–Rao inequalities (r2Iρ ≥ D2; p2Iγ ≥ D2).
J S Dehesa, R González-Férez, P Sánchez-Moreno   +2 more
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Cramer-Rao type integral inequalities for general loss functions

Test, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Note on the Cramér-Rao inequality in the nonregular case: the family of uniform distributions

Journal of Statistical Planning and Inference, 1983
Abstract We consider the family of uniform distributions with range of unit length. The main result of this note asserts that the average variance of any unbiased estimator of the midpoint of the range is not less than (2( n +1))( n +2)) -1 and this lower bound is sharp. The proof is based upon a nonregular version of the Cramer-Rao inequality.
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Generalized Blackwell-Rao and Cramer-Rao's inequalities

2013
Statistica; Vol 59, No 4 (1999)
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The Cramer–Rao inequality

2014
Linden, W., Dose, V., Toussaint, U.
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