搜索结果: 1-12 共查到“管理学 Divergence”相关记录12条 . 查询时间(0.07 秒)
Some results on a $χ$-divergence, an~extended~Fisher information and~generalized~Cramer-Rao inequalities
Some results $χ$-divergence an~extended~Fisher information generalized~Cramer-Rao inequalities
2013/6/17
We propose a modified $\chi^{\beta}$-divergence, give some of its properties, and show that this leads to the definition of a generalized Fisher information. We give generalized Cram\'er-Rao inequalit...
Maximal Information Divergence from Statistical Models defined by Neural Networks
neural network exponential family Kullback-Leibler diver-gence multi-information
2013/4/27
We review recent results about the maximal values of the Kullback-Leibler information divergence from statistical models defined by neural networks, including naive Bayes models, restricted Boltzmann ...
A procedure for the change point problem in parametric models based on phi-divergence test-statistics
Change point Information criterion Divergence Wald test-statistic
2011/7/19
This paper studies the change point problem for a general parametric, univariate or multivariate family of distributions.
Change point analysis of an exponential model based on Phi-divergence test-statistics: simulated critical points case
Change poin Exponential model Likelihood ratio test
2011/7/19
Recently Batsidis \textit{et al.} (2011) have presented a new procedure based on divergence measures for testing the hypothesis of the existence of a change point in exponential populations.
Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence
Online algorithms Nonnegative Matrix Factorization Itakura-Saito divergence
2011/7/6
Nonnegative matrix factorization (NMF) is now a common tool for audio source separation.
Bayesian predictive densities for linear regression models under alpha-divergence loss：some results and open problems
shrinkage prior Bayesian predictive density alpha-divergence Stein effect
2010/3/10
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...
On Bahadur Efficiency of Power Divergence Statistics
Bahadur efficiency consistency power divergence Renyi divergence
2010/3/10
It is proved that the information divergence statistic
is infinitely more Bahadur efficient than the power divergence
statistics of the orders > 1 as long as the sequence of
alternatives is conti...
Republicanism and the Politics of Citizenship in Germany and France: Convergence or Divergence?
Republicanism the Politics of Citizenship Germany and France Convergence Divergence
2009/9/29
In this article it is argued that the models of German citizenship are quite dynamic and evolving. The German tradition today is more in line with the French and U.S. republican model of jus soli citi...
Time-inhomogeneous diffusions corresponding to symmetric divergence form operators
Time-inhomogeneous diffusions symmetric divergence form operators
2009/9/21
We consider a time-inhomogeneous Markov family
(X, P,3 corresponding to a symmetric uniformly elliptic divergence
form operator. We show that for any rp in the Sobolev space W: n Wi
with p = 2 if d...
On Homogenization of Non-Divergence Form Partial Difference Equations
pde with random coecients homogenization
2009/4/24
In this paper a method for proving homogenization of divergence form elliptic equations is extended to the non-divergence case. A new proof of homogenization is given when the coefficients in the equa...
On Homogenization of Non-Divergence Form Partial Difference Equations
Homogenization Non-Divergence Partial Difference Equations
2009/4/7
In this paper a method for proving homogenization of divergence form elliptic equations is extended to the non-divergence case. A new proof of homogenization is given when the coefficients in the equa...
Information，Divergence and Risk for Binary Experiments
Information Divergence Risk Binary Experiments
2010/3/17
We unify f-divergences, Bregman divergences, surrogate loss bounds (regret bounds),
proper scoring rules, matching losses, cost curves, ROC-curves and information. We do
this by systematically study...