搜索结果: 1-15 共查到“理论统计学 m method”相关记录43条 . 查询时间(2.375 秒)
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
Distributed Optimization Statistical Learning via Alternating Direction Method Multipliers
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2015/7/9
Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasi...
The Cross-Entropy Method for Estimation
cross-entropy estimation rare events importance sampling adaptive Monte Carlo zero-variance distribution
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2015/7/6
This chapter describes how difficult statistical estimation problems can often be solved efficiently by means of the cross-entropy (CE) method. The CE method can be viewed as an adaptive importance sa...
ERROR ANALYSIS OF COARSE-GRAINED KINETIC MONTE CARLO METHOD
Coarse grain kinetic monte carlo simulation grid the stochastic dynamics structural model
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2014/12/25
In this paper we investigate the approximation properties of the coarse-graining procedure applied to kinetic Monte Carlo simulations of lattice stochastic dynamics. We provide both analytical and num...
Adapting the Interrelated Two-way Clustering method for Quantitative Structure-Activity Relationship (QSAR) Modeling of a Diverse Set of Chemical Compounds
Mutagenicity topological indices atom pairs Interrelated Two-way Clustering ridge regression quantum chemical descriptors
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2013/6/14
Interrelated Two-way Clustering (ITC) is an unsupervised clustering method developed to divide samples into two groups in gene expression data obtained through microarrays, selecting important genes s...
Inference in Kingman's Coalescent with Particle Markov Chain Monte Carlo Method
Inference Kingman's Coalescent with Particle Markov Chain Monte Carlo Method
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2013/6/13
We propose a new algorithm to do posterior sampling of Kingman's coalescent, based upon the Particle Markov Chain Monte Carlo methodology. Specifically, the algorithm is an instantiation of the Partic...
A least-squares method for sparse low rank approximation of multivariate functions
least-squares method sparse low rank approximation multivariate functions
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2013/6/14
In this paper, we propose a low-rank approximation method based on discrete least-squares for the approximation of a multivariate function from random, noisy-free observations. Sparsity inducing regul...
ParceLiNGAM: A causal ordering method robust against latent confounders
ParceLiNGAM A causal ordering method robust against latent confounders
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2013/4/28
We consider learning a causal ordering of variables in a linear non-Gaussian acyclic model called LiNGAM. Several existing methods have been shown to consistently estimate a causal ordering assuming t...
Statistical inference for Sobol pick freeze Monte Carlo method
Statistical inference Sobol pick freeze Monte Carlo method
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2013/4/28
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
Goal-oriented error estimation for reduced basis method, with application to certified sensitivity analysis
reduced basis method surrogate model reduced order modelling re-sponse surface method scientific computation sensitivity analysis Sobol index computation Monte-Carlo method
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2013/5/2
The reduced basis method is a powerful model reduction technique designed to speed up the computation of multiple numerical solutions of parameterized partial differential equations (PDEs). We conside...
Estimating the quadratic covariation matrix from noisy observations: local method of moments and efficiency
adaptive estimation asymptotic equivalence asynchronous ob-servations integrated covolatility matrix quadratic covariation semiparametric eciency,microstructure noise spectral estimation
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2013/4/28
An efficient estimator is constructed for the quadratic covariation or integrated covolatility matrix of a multivariate continuous martingale based on noisy and non-synchronous observations under high...
`Truncate, replicate, sample': a method for creating integer weights for spatial microsimulation
microsimulation integerisation iterative proportional fitting
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2013/4/28
Iterative proportional fitting (IPF) is a widely used method for spatial microsimulation. The technique results in non-integer weights for individual rows of data. This is problematic for certain appl...
A parameter estimation method based on random slow manifolds
Parameter estimation Slow-fast system Random slow manifold Quantifying uncer-tainty Numerical optimization
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2013/5/2
A parameter estimation method is devised for a slow-fast stochastic dynamical system, where often only the slow component is observable. By using the observations only on the slow component, the syste...
A Directional Gradient-Curvature Method for Gap Filling of Gridded Environmental Spatial Data with Potentially Anisotropic Correlations
correlation anisotropy spatial interpolation stochastic estimation optimization simulation
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2013/4/27
We introduce the Directional Gradient-Curvature (DGC) method, a novel approach for filling gaps in gridded environmental data. DGC is based on an objective function that measures the distance between ...
An Improved Bound for the Nystrom Method for Large Eigengap
An Improved Bound the Nystrom Method Large Eigengap
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2012/11/23
We develop an improved bound for the approximation error of the Nystr\"{o}m method under the assumption that there is a large eigengap in the spectrum of kernel matrix. This is based on the empirical ...