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In quantitative risk management, it is important and challenging to find sharp bounds for the distribution of the sum of dependent risks with given marginal distributions, but an unspecified dependenc...
In quantitative risk management, it is important and challenging to find sharp bounds for the distribution of the sum of dependent risks with given marginal distributions, but an unspecified dependenc...
We describe a new estimator of the stationary density of a Markov chain on general state space. The new estimator is easier to compute, converges faster, and empirically gives visually superior estima...
We introduce a new class of density estimators, termed look-ahead density estimators, for performance measures associated with a Markov chain. Look-ahead density estimators are given for both transien...
The determinants (|rho^{PT}|) of the partial transposes of 4 x 4 density matrices (rho) have possible values in the interval [-1/16, 1/256], and are nonnegative if and only if rho is separable. In arX...
We investigate the estimation of a weighted density taking the formg=w(F)f, where fdenotes an unknown density,Fthe associated distribution function andwis a known (non-negative) weight.Such a class en...
Skew-symmetric densities recently received much attention in the literature, giving rise to in-creasingly general families of univariate and multivariate skewed densities. Most of those families,howev...
We first introduce a class of divergence measures between power spectral density matrices. These are derived by comparing the suitability of different models in the context of optimal prediction.
This paper shows that large nonparametric classes of conditional multivariate densities can be approximated in the Kullback--Leibler distance by different specifications of finite mixtures of normal ...
Because of their multimodality, mixture posterior densities are difficult to sample with standard Markov chain Monte Carlo (MCMC) methods. We propose a strategy to enhance the sampling of MCMC in th...
This paper considers estimation of the predictive density for a normal linear model with unknown variance under -divergence loss for −1   1. We first give a general canonical form for the...
Many real phenomena may be modelled as random closed sets in Rd, of different Hausdorff dimensions. In many real applications, such as fiber processes and n-facets of random tessellations of dimensi...
We prove uniqueness of the maximum likelihood estimator for the class of k?monotone densities. AMS 2000 subject classifications: Primary 62G07.
Testable weighted graph parameters and equivalent notions of testability are investi- gated based on [4]. We prove that certain balanced minimum multiway cut densities are testable. Using this fact,...
We find evidence of relationships between HRH densities and vaccination rates even at Turkey's relatively elevated levels of each. At the same time, variations in results between different empirical m...

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