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Marginal empirical likelihood and sure independence screening
Empirical likelihood high dimensional data analysis independence sure screening large deviation
2016/1/25
We study a marginal empirical likelihood approach in scenarios when the num-ber of variables grows exponentially with the sample size. The marginal empirical likelihood ratios as functions of the para...
Bounds for the Sum of Dependent Risks and Worst Value-at-Risk with Monotone Marginal Densities
Complete mixability Monotone density Sum of dependent risks Value-at- Risk
2016/1/25
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...
Marginal empirical likelihood and sure independence screening
Empirical likelihood high dimensional data analysis independence sure screening large deviation
2016/1/20
We study a marginal empirical likelihood approach in scenarios when the num-ber of variables grows exponentially with the sample size. The marginal empirical likelihood ratios as functions of the para...
Bounds for the Sum of Dependent Risks and Worst Value-at-Risk with Monotone Marginal Densities
Complete mixability Monotone density Sum of dependent risks Value-at- Risk
2016/1/20
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...
On the Marginal Standard Error Rule and the Testing of Initial Transient Deletion Methods
Marginal Standard Error Rule Testing Initial Transient Deletion Methods
2015/7/6
In this paper, we introduce several theoretically useful measures for the magni- tude of the initial transient in the setting of single replication steady-state simulations. These measures help suppor...
Biofuel development,food security and the use of marginal land in China
Bioethanol Development Food Security Marginal Lands China
2014/3/12
With concerns of energy shortages, China, like the US, EU and other countries, is promoting the development of biofuels. However, China also faces high future demand for food and feed, and so its bioe...
Marginal AMP Chain Graphs
Marginal AMPChain Graphs
2013/6/13
We present a new family of graphical models that may have undirected, directed and bidirected edges. We name these new models marginal AMP (MAMP) chain graphs because each of them can be seen as the r...
Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods
Distributed Learning Gaussian Graphical Models Marginal Likelihoods
2013/4/28
We consider distributed estimation of the inverse covariance matrix, also called the concentration matrix, in Gaussian graphical models. Traditional centralized estimation often requires iterative and...
Learning AMP Chain Graphs and some Marginal Models Thereof under Faithfulness
Learning AMP Chain Graphs some Marginal Models Thereof under Faithfulness
2013/4/27
This paper deals with chain graphs under the Andersson-Madigan-Perlman (AMP) interpretation. In particular, we present a constraint based algorithm for learning an AMP chain graph a given probability ...
Toward Practical N2 Monte Carlo: the Marginal Particle Filter
Practical N2 Monte Carlo Marginal Particle Filter
2012/9/19
Sequential Monte Carlo techniques are useful for state estimation in non-linear, non-Gaussian dy-namic models. These methods allow us to ap-proximate the joint posterior distribution using sequential ...
Finite mixture models with predictive recursion marginal likelihood
Density estimation Dirichlet distribution mixture com-plexity
2011/7/6
Estimation of finite mixture models when the mixing distribution support is unknown is an important and challenging problem. In this paper, a new approach is given based on the recently proposed predi...
Semiparametric inference in mixture models with predictive recursion marginal likelihood
Density estimation Dirichlet process mixture empirical Bayes filtering algorithm
2011/7/5
Predictive recursion is an accurate and computationally efficient algorithm for nonparametric estimation of mixing densities in mixture models. In semiparametric mixture models, however, the algorithm...
Marginal log-linear parameters for graphical Markov models
multivariate discrete statistical models parametrization marginal log-linear graphical Markov models
2011/6/20
The parametrization of multivariate discrete statistical models by marginal log-linear
(MLL) parameters provides a great deal of flexibility; in particular, different MLL parametrizations
under line...
An asymptotic approximation of the marginal likelihood for general Markov models
Statistics Theory (math.ST)
2010/12/17
The standard Bayesian Information Criterion (BIC) is derived under regularity conditions which are not always satisfied by the graphical models with hidden variables.
On the Marginal Distributions of Stationary AR(1) Sequences
Semi-selfdecomposability infinite divisibility AR(1) process
2010/4/28
In this note we correct an omission in our paper (Satheesh and Sandhya, 2005)
in defining semi-selfdecomposable laws and also show with examples that the marginal
distributions of a stationary AR(1)...