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High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood Variable selec- tion
2016/1/26
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
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...
High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood
2016/1/20
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
CreditRisk Model with Dependent Risk Factors
CreditRisk + model conditional independence dependent risk factors
2016/1/20
The CreditRisk + model is widely used in industry for computing the loss of a credit port-folio. The standard CreditRisk + model assumes independence among a set of common risk factors, a simplified a...
The backbone decomposition for spatially dependent supercritical superprocesses
Superprocesses N-measure backbone decomposition
2016/1/20
Consider any supercritical Galton-Watson process which may become extinct with positive probability. It is a well-understood and intuitively obvious phenomenon that,on the survival set, the process ma...
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...
Computation of the Maximum H_infinity-norm of Parameter-Dependent Linear Systems by a Branch and Bound Algorithm
Computation Maximum H_infinity-norm Parameter-Dependent Linear Systems Bound Algorithm
2015/7/13
For linear systems that contain unspecified parameters that lie in given intervals, we present a branch and bound algorithm for computing the maximum H_infinity-norm over the set of uncertain paramete...
Branch and Bound Algorithm for Computing the Minimum Stability Degree of Parameter-Dependent Linear Systems
Branch Bound Algorithm Computing Minimum Stability Degree Parameter-Dependent Linear Systems
2015/7/13
We consider linear systems with unspecified parameters that lie between given upper and lower bounds. Except for a few special cases, the computation of many quantities of interest for such systems ca...
DTMW: A New Congestion Control Scheme for Long-Range Dependent Traffic
New Congestion Control Scheme Long-Range Dependent Traffic
2015/7/8
Recent measurements based on long empirical traces have revealed that many important types of traffic (e.g., LAN, WAN and VBR video) possesses long range dependent (LRD) characteristics. Studies have ...
CAPABILITIES,BUSINESS PROCESSES,AND COMPETITIVE ADVANTAGE: CHOOSING THE DEPENDENT VARIABLE IN EMPIRICAL TESTS OF THE RESOURCE-BASED VIEW
resource-based view information technology business processes insurance competitive advantage
2015/1/26
CAPABILITIES,BUSINESS PROCESSES,AND COMPETITIVE ADVANTAGE: CHOOSING THE DEPENDENT VARIABLE IN EMPIRICAL TESTS OF THE RESOURCE-BASED VIEW.
From Feshbach-resonance managed Bose-Einstein condensates to anisotropic universes: Applications of the Ermakov-Pinney equation with time-dependent nonlinearity
Two-dimensional condensate time-varying magnetic confinement scattering wave function ordinary differential equations
2014/12/25
In this work we revisit the topic of two-dimensional Bose–Einstein condensates under the influence of time-dependent magnetic confinement and time-dependent scattering length. A moment approach reduce...
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Dynamic Clustering Asymptotics Dependent Dirichlet Process Mixture
2013/6/17
This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The alg...
Limit theorems for kernel density estimators under dependent samples
Kernel density estimator consistency convergence rate mixing rate
2013/6/14
In this paper, we construct a moment inequality for mixing dependent random variables, it is of independent interest. As applications, the consistency of the kernel density estimation is investigated....
A Semiparametric Estimator for Long-Range Dependent Multivariate Processes
Multivariate processes Long-range dependence Semiparametric estimation VARFIMA processes Asymptotic theory
2013/6/14
In this paper we propose a generalization of a class of Gaussian Semiparametric Estimators (GSE) of the fractional differencing parameter for long-range dependent multivariate time series. We generali...
Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
Ergodic convergence Markov Chain Monte Carlo Metropolis-within Gibbs composite sampling Multivariatet mixtures Simulated annealing Variational Approx-imation
2013/6/14
This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributio...