Results 251 to 260 of about 529,179 (290)

Estimating normal tail probabilities

Naval Research Logistics Quarterly, 1986
AbstractThe estimation problem of normal tail probabilities is considered. The form of generalized Bayes estimators is derived and the asymptotic behavior of the mean square errors is studied. This study shows that the best unbiased estimator, a formula for which is given, is superior to the maximum likelihoood estimator or to a class of generalized ...
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Tail Inference With Probability Weighted Moments

Mathematical Methods in the Applied Sciences
ABSTRACTThe tail of a probability distribution captures important information about the magnitude and frequency of extreme events. Thus, understanding the tail behavior is crucial in decision making and risk assessment. Statistical analysis and predictions of extreme events often require the estimation of the extreme value index, a key parameter that ...
Frederico Caeiro, Ayana Mateus, Dora Prata Gomes   +2 more
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Tail probability approximations for Student's t-statistics

Probability Theory and Related Fields, 2006
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Zhou, W., Jing, B.-Y.
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A Predictive Approach to Tail Probability Estimation

Extremes, 2001
The problem of high quantiles estimation by an i.i.d. sample \(X_1\),\dots, \(X_n\) is considered. The authors propose a Bayesian approach where \(\Pr\{X-u \mid X>u\}\) is supposed to be a generalized Pareto distribution and the threshold \(u\) is a Bayesian parameter with some prior distribution.
de Zea Bermudes, P., Amaral Turkman, M. A., Turkman, K. F.   +2 more
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Heavy Tails and Earthquake Probabilities

Seismological Research Letters, 2012
The 21st century has already seen its share of devastating earthquakes, some of which have been labeled as “unexpected,” at least in the eyes of some seismologists and more than a few journalists. A list of seismological surprises could include the 2004 Sumatra-Andaman Islands; 2008 Wenchuan, China; 2009 Haiti; 2011 Christchurch, New Zealand; and 2011 ...
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Refinement of Convergence Rates for Tail Probabilities

Journal of Theoretical Probability, 2005
There are many results aimed at providing necessary and sufficient conditions for the convergence of the sum \[ f(x)=\sum_n a_nP(|S_n|>xb_n),\;\;\;x>0, \] where \(S_n=X_1+\cdots+X_n,\) \(\{X,\;X_n;\;n\geq 1\}\) is a sequence of i.i.d. r.v., such that \(P(X\neq 0)>0,\;EX=0\;(E|X|0,\;\sum_n a_n=\infty\) and \(b_n\) is either \(n^{1/p},\;00,\) and so they
Li, Deli, Spătaru, Aurel
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Nonparametric estimation of multivariate tail probabilities and tail dependence coefficients

Journal of Multivariate Analysis, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Krupskii, Pavel, Joe, Harry
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Tail Probabilities for Regression Estimators [PDF]

, 2006
Estimators of regression coefficients are known to be asymptotically normally distributed, provided certain regularity conditions are satisfied. In small samples and if the noise is not normally distributed, this can be a poor guide to the quality of the estimators.
Mikosch, Thomas Valentin, Vries, Casper G. de   +1 more
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Importance Sampling for Tail Probabilities

1991
Abstract : Our interest is in the accurate and efficient evaluation of very small probabilities. Thus, we seek methods with bounded coefficient of variation as the probability decreases and we assess their performance. The univariate case is explored for a heuristic for construction of sampling density families.
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Probable predation on white-tailed kite by red-tailed hawk

1980
(Uploaded by Plazi from the Biodiversity Heritage Library) No abstract provided.
Pinkston, D. Randall, Caraviotis, Jerry G.   +1 more
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