Results 241 to 250 of about 529,179 (290)

Characterization of a novel panel of polymorphic microsatellite loci and the mitogenome for the Neotropical marsupial Gracilinanus agilis (Didelphimorphia: Didelphidae). [PDF]

Mol Biol Rep
da Silva MRD, Lima-Rezende CA, Zangrandi PL, Mendonça AF, Caparroz R, Vieira EM, Rodrigues FP.   +6 more
europepmc   +1 more source

Regioselective Sesquiterpene Hydroxylation Directed by Tunnel Remodeling in Rieske Oxygenases. [PDF]

JACS Au
Berger JB, Marques SM, Wissner JL, Schelle JT, Beekwilder J, Damborsky J, Hauer B.   +6 more
europepmc   +1 more source

Epidemic Mean-Field Thresholds of SIS Dynamics on Temporal Multiplex Networks with Activity-Driven Layers

Marjani M, Chatterjee S, Bhattacharyya S, Scoglio C.   +3 more
europepmc   +1 more source

Resistance mutation supply modulates the benefit of CRISPR immunity against virulent phages

Wright RC, Lovell SC, Richmond A, Harrison C, Ashworth E, Kadioglu A, Fothergill JL, Friman V, Westra ER, Brockhurst MA.   +9 more
europepmc   +1 more source

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Tail Probability Approximations

International Statistical Review / Revue Internationale de Statistique, 1987
This paper is a very interesting and clear review on two explicit approximations for the tail probability of a sample mean. The Edgeworth type expansion gives an asymptotic expansion in powers of \(n^{-1/2}\) when \(\bar x-E(X)=O(n^{-1/2})\). For large deviations it can be further reduced to an expansion whose terms decrease by a factor \(n^{-1}.\) A ...
openaire   +3 more sources

Invariant Probabilities with Geometric Tail

Probability in the Engineering and Informational Sciences, 1996
We present necessary and suffi2ient Foster-type conditions for a countable state Markov chain to have an invariant probability with at least a geometric tail. These conditions are obtained by using a generalized Farkas Theorem in Linear Algebra. The purpose of this note is also to pose an interesting and important research problem that is still largely
Tijms, H.C., Lasserre, J.B.
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Tail probability approximations for U-statistics

Statistics & Probability Letters, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Keener, Robert W., Robinson, John, Weber, Neville C.   +2 more
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Tail probabilities from observed likelihoods

Biometrika, 1990
SUMMARY An exponential model not in standard form is fully characterized by an observed likelihood function and its first sample space derivative, up to one-one transformations of the observable variable. This property is used to modify the Lugannani & Rice (1980) tail probability approximation to make it parameterization invariant.
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