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Titlebook: Advances in Mathematical and Statistical Modeling; Roberto Minguez,Jose-Maria Sarabia,Barry C. Arnold Book 2008 Birkh?user Boston 2008 Est

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發(fā)表于 2025-3-28 17:14:51 | 只看該作者
42#
發(fā)表于 2025-3-28 20:13:21 | 只看該作者
43#
發(fā)表于 2025-3-28 23:45:18 | 只看該作者
https://doi.org/10.1007/978-1-4614-5149-5rent interpretations and statistical applications. An extension to a more general family of models of ordered random variables is proposed. Intermediate or fractional order statistics turn out to be a particular sub-model. Their joint density may also be described as ordered Dirichlet distribution.
44#
發(fā)表于 2025-3-29 06:57:10 | 只看該作者
45#
發(fā)表于 2025-3-29 08:01:11 | 只看該作者
SpringerBriefs in Cognitive Computatione the most likely system state. More often than not, in practice the Gaussian and independent measurements assumptions do not hold. In this paper we relax these questionable assumptions and develop techniques to accurately estimate the system state through appropriate transformations of correlated n
46#
發(fā)表于 2025-3-29 13:14:58 | 只看該作者
Cognitive Agent-based Computing-Iility..Many authors have dealt with this problem proposing different CDFs (Cumulative Distribution Functions) and statistical descriptors evolution. One of these works suggests that, for a given sea state, the parameters of the local (at a given point of the profile) wave height CDF depend on the lo
47#
發(fā)表于 2025-3-29 18:34:00 | 只看該作者
Tomas Plch,Tomas Jedli?ka,Cyril Brom are suitable for any (finite) dimension, and are invariant under increasing transformations of the marginal distributions. It is shown that both have a desired property that other coefficients of dependence lack. That is, for the mixture model, mixture between complete dependence and total independ
48#
發(fā)表于 2025-3-29 21:13:17 | 只看該作者
49#
發(fā)表于 2025-3-30 01:17:20 | 只看該作者
Yiru Yang,Dandan Wang,Wenjie Hou,He Lithat the chance of an exceedance of that value is equal to., small. In this paper we provide an empirical data analysis of logreturns associated to a set of financial data, through the use of reduced-bias tail index and associated high quantile estimators. These tail index estimators depend on two s
50#
發(fā)表于 2025-3-30 05:10:02 | 只看該作者
https://doi.org/10.1007/978-0-8176-4626-4Estimator; Factor analysis; Generalized linear model; Measure; Optimization Methods; Pretest; Random varia
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