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Local systems on nilpotent orbits and weighted Dynkin diagrams
Bidirectional mapping bijection clear type double algebras nilpotent orbit
2014/12/29
We study the Lusztig-Vogan bijection for the case of a local system. We compute the bijection explicitly in type A for a local system and then show that the dominant weights obtained for different loc...
Adapting the Stochastic Block Model to Edge-Weighted Networks
Adapting Stochastic Block Model Edge-Weighted Networks
2013/6/14
We generalize the stochastic block model to the important case in which edges are annotated with weights drawn from an exponential family distribution. This generalization introduces several technical...
Weighted estimation of the dependence function for an extreme-value distribution
bivariate extreme dependence function jackknife empirical likelihood method
2013/4/28
Bivariate extreme-value distributions have been used in modeling extremes in environmental sciences and risk management. An important issue is estimating the dependence function, such as the Pickands ...
An Approximate Approach to E-optimal Designs for Weighted Polynomial Regression by Using Tchebycheff Systems and Orthogonal Polynomials
An Approximate Approach E-optimal Designs Weighted Polynomial Regression Using Tchebycheff Systems Orthogonal Polynomials
2013/4/28
In statistics, experimental designs are methods for making efficient experiments. E-optimal designs are the multisets of experimental conditions which minimize the maximum axis of the confidence ellip...
Smoothing effect of Compound Poisson approximation to distribution of weighted sums
characteristic function concentration function compound Poisson distribution Kolmogorov norm weighted random variables.
2013/4/27
The accuracy of compound Poisson approximation to the sum $S=w_1S_1+w_2S_2+...+w_NS_N$ is estimated.
Here $S_i$ are sums of independent or weakly dependent random variables, and $w_i$ denote weights...
Clustering and Classification via Cluster-Weighted Factor Analyzers
Cluster-weighted models factor analysis mixturemodels parsimonious models
2012/11/23
In model-based clustering and classification, the cluster-weighted model constitutes a convenient approach when the random vector of interest constitutes a response variable Y and a set p of explanato...
Weighted bootstrap in GARCH models
asymptotic distribution bootstrap confidence region,GARCH model quasi maximum likelihood
2012/11/22
GARCH models are useful tools in the investigation of phenomena, where volatility changes are prominent features, like most financial data. The parameter estimation via quasi maximum likelihood (QMLE)...
Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization
Fast and Accurate Algorithms Re-Weighted L1-Norm Minimization
2012/9/17
To recover a sparse signal from an underdetermined system, we often solve a constrained`1-norm minimization problem. In many cases, the signal sparsity and the recovery performance can be further impr...
Re-Weighted l_1 Dynamic Filtering for Time-Varying Sparse Signal Estimation
Re-Weighted Dynamic Filtering Time-Varying Signal Estimation
2012/9/17
Signal estimation from incomplete observations improves as more signal structure can be exploited in the inference process. Classic algorithms (e.g., Kalman filtering) have exploited strong dynamic st...
Maximum Likelihood Estimation of Gaussian Cluster Weighted Models and Relationships with Mixtures of Regression
Cluster-weighted modeling finite mixtures of regression EM-algorithm
2012/9/19
Cluster-weighted modeling (CWM) is a mixture approach for modeling the joint probability of a response variable and a set of explanatory variables. The parame-ters are estimated by means of the expect...
On adaptive wavelet estimation of a class of weighted densities
Weighted density density estimation plug-in approach wavelets block thresholding reliability series system parallel system.
2012/9/18
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...
Flexible Mixture Modeling with the Polynomial Gaussian Cluster-Weighted Model
Mixture of distributions Mixture of regressions Polynomial regression Model-based clustering Model-based classification Cluster-weighted models.
2012/9/18
In the mixture modeling frame, this paper presents the polynomial Gaussian cluster-weighted model (CWM). It extends the linear Gaussian CWM, for bivariate data, in a twofold way. Firstly, it allows fo...
Weighted algorithms for compressed sensing and matrix completion
Compressed Sensing Weighted Basis-Pursuit Matrix Completion
2011/7/19
This paper is about iteratively reweighted basis-pursuit algorithms for compressed sensing and matrix completion problems. In a first part, we give a theoretical explanation of the fact that reweighte...
Learning with the Weighted Trace-norm under Arbitrary Sampling Distributions
Learning Weighted Trace-norm Arbitrary Sampling Distributions
2011/7/7
We provide rigorous guarantees on learning with the weighted trace-norm under arbitrary sampling distributions.
CHICOM: A code of tests for comparing unweighted and weighted histograms and two weighted histograms
homogeneity test fit Monte Carlo distribution to data comparison experimental and simulated data data interpretation
2011/6/21
A self-contained Fortran-77 program for calculating test statistics to compare
weighted histogram with an unweighted histogram and two histograms with
weighted entries is presented. The code calcula...