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A Strong Law of Large Numbers for Super-stable Processes
Strong Law Large Numbers Super-stable Processes
2016/1/20
A Strong Law of Large Numbers for Super-stable Processes.
B-stable ideals in the nilradical of a Borel subalgebra
Connection is simple and complex algebraic groups $borel subgroup lie algebra
2014/12/29
Let $G$G be a connected simple algebraic group over the complex numbers and $B$B a Borel subgroup. Let $\germ g$g be the Lie algebra of $G$G and $\germ b$b the Lie algebra of $B$B . A subspace of the ...
Let be a simple algebraic group over the complex numbers containing a Borel subgroup . Given a -stable ideal in the nilradical of the Lie algebra of , we define natural numbers which we call ideal exp...
Stable structures with high topological charge in nonlinear photonic quasicrystals
Whirlpool analysis of photonic crystals nonlinear
2014/12/24
Stable vortices with topological charges of 3 and 4 are examined numerically and analytically in photonic quasicrystals created by interference of five as well as eight beams, for cubic as well as sat...
Stable Vortex–Bright-Soliton Structures in Two-Component Bose-Einstein Condensates
Numerical two-component structure condensate ordinary topological charge symbiotic state defocusing eddy
2014/12/24
We report the numerical realization of robust two-component structures in 2D and 3D Bose-Einstein condensates with nontrivial topological charge in one component. We identify a stable symbiotic state ...
Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties
Covariance estimation Regularization Condition number Canonical correlation analysis Discriminant analysis Clustering
2013/6/14
Estimation of covariance matrices or their inverses plays a central role in many statistical methods. For these methods to work reliably, estimated matrices must not only be invertible but also well-c...
Linear system identification using stable spline kernels and PLQ penalties
linear system identification bias-variance trade off kernel-based regularization robust statistics interior point methods piecewise linear quadratic densities
2013/4/27
The classical approach to linear system identification is given by parametric Prediction Error Methods (PEM). In this context, model complexity is often unknown so that a model order selection step is...
Max-stable processes and the functional D-norm revisited
Max-stable process D-norm functional max-domain of attraction copula process generalized Pareto process δ-neighborhood of generalized Pareto process t-test for max-stable and for generalized Pareto process
2013/5/2
Aulbach et al. (2012) introduced some mathematical framework for extreme value theory in the space of continuous functions on compact intervals. Continuous max-stable processes on [0,1] were character...
Learning Stable Multilevel Dictionaries for Sparse Representation of Images
Learning Stable Multilevel Dictionaries Sparse Representation Images
2013/4/28
Dictionaries adapted to the data provide superior performance when compared to predefined dictionaries in applications involving sparse representations. Algorithmic stability and generalization are de...
Conditional simulation of max-stable processes
Conditional simulation Markov chain Monte Carlo Max-stable process Precipitation Regular conditional distribution Temperature.
2012/9/18
Since many environmental processes such as heat waves or precipitation are spatial in extent,it is likely that a single extreme event affects several locations and the areal modelling of ex-tremes is ...
Nonparametric Inference for Max-Stable Dependence
Nonparametric Inference Max-Stable Dependence
2012/9/17
The choice for parametric techniques in the dis-cussion article is motivated by the claim that for multivariate extreme-value distributions, “owing to
the curse of dimensionality, nonparametric estim...
A simple and numerical stable algorithm for solving the cone projection problem based on a Gram-Schmidt process
cone projection algorithm convexity constraints convexity test simulations Gram-Schmidt
2012/9/19
We are presenting a simple and numerical stable algorithm for the solution of the cone projection problem which is suitable for relative small data sets and for simulation purposes needed for con-vexi...
Analytic Loss Distributional Approach Model for Operational Risk from the alpha-Stable Doubly Stochastic Compound Processes and Implications for Capital Allocation
Operational Risk Loss Distributional Approach Doubly stochastic Poisson Process -Stable Basel II Solvency II
2011/3/25
Under the Basel II standards, the Operational Risk (OpRisk) advanced measurement approach is not prescriptive regarding the class of statistical model utilised to undertake capital estimation. It has ...
In this paper, we show new representations of one-sided L\'{e}vy stable distributions for irrational L\'{e}vy indices of the type $\left(\frac{p}{q}\right)^{\frac{l_{2}}{l_{1}}}$ which are not covered...
Feynman-Kac Penalisations of Symmetric Stable Processes
symmetric stable process Feynman-Kac functional penalisation Kato measure
2010/2/24
In K. Yano, Y. Yano and M. Yor (2009), limit theorems for the one-dimensional symmetric α-stable process normalized by negative (killing) Feynman-Kac functionals were studied. We consider the same pro...