搜索结果: 1-15 共查到“理论统计学 Adaptive”相关记录60条 . 查询时间(0.055 秒)
Complexity of Non-Adaptive Optimization Algorithms for a Class of Diffusions
Global optimization average-case complexity diffusion processes
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2015/7/8
This paper is concerned with the analysis of the average error in approximating the global minimum of a 1-dimensional, time-homogeneous diffusion by non-adaptive methods. We derive the limiting distri...
An Adaptive Sequential Monte Carlo Algorithm for Computing Permanents
Sequential Monte Carlo Permanents Relative Variance
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2013/6/14
We consider the computation of the permanent of a binary n by n matrix. It is well- known that the exact computation is a #P complete problem. A variety of Markov chain Monte Carlo (MCMC) computationa...
Adaptive estimation in nonparametric regression with one-sided errors
adaptive convergence rates non-regular regression frontier estimation bandwidth selection Lepski's method minimax optimality Pickands estimator
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2013/6/14
We consider the model of non-regular nonparametric regression where smoothness constraints are imposed on the regression function and the regression errors are assumed to decay with some sharpness lev...
Adaptive confidence intervals for regression functions under shape constraints
Adaptation confidence interval convex function coverage probability expected length minimax estimation modulus of continuity monotone func-tion nonparametric regression shape constraint white noise model
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2013/6/14
Adaptive confidence intervals for regression functions are constructed under shape constraints of monotonicity and convexity. A natural benchmark is established for the minimum expected length of conf...
On adaptive posterior concentration rates
Bayesian nonparametrics minimax adaptive estimation poste-rior concentration rates sup-norm rates of convergence
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2013/6/14
We investigate the problem of deriving posterior concentration rates under different loss functions in nonparametric Bayes. We first provide a lower bound on posterior coverages of shrinking neighbour...
Bayesian Multi-Dipole Modeling of Single MEG Topographies by Adaptive Sequential Monte Carlo Samplers
Magnetoencephalography inverse problem Multi-object estimation Multi-dipole models Adaptive Sequential Monte Carlo samplers
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2013/6/14
We describe a novel Bayesian approach to the estimation of neural currents from a single distribution of magnetic field, measured by magnetoencephalography. We model neural currents as an unknown numb...
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
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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...
Adaptive Bayes test for monotonicity
Bayesian Nonparametric Nonparametric regression Nonparamet-ric hypothesis testing Asymptotic properties
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2013/4/28
We study the asymptotic behaviour of a Bayesian nonparametric test of qualitative hypotheses. More precisely, we focus on the problem of testing monotonicity of a regression function. Even if some res...
Two General Methods for Population Pharmacokinetic Modeling: Non-Parametric Adaptive Grid and Non-Parametric Bayesian
Population pharmacokinetic modeling non-parametric maximum likelihood Bayesian Stick-breaking Pmetrics RJags
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2013/5/2
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian...
Adaptive Priors based on Splines with Random Knots
Adaptive estimation bayesian non-parametric optimal contrac-tion rate spline random knots
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2013/4/27
Splines are useful building blocks when constructing priors on nonparametric models indexed by functions. Recently it has been established in the literature that hierarchical priors based on splines w...
Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach
Adaptive Monte Carlo algorithms Bayesian model comparison Normalising constants Path sampling Thermodynamic integration
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2013/4/27
Model comparison for the purposes of selection, averaging and validation is a problem found throughout statistics and related disciplines. Within the Bayesian paradigm, these problems all require the ...
Adaptive quantile estimation in deconvolution with unknown error distribution
Deconvolution Quantile and distribution function Adaptive es-timation Minimax convergence rates Random Fourier multiplier
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2013/4/27
We study the problem of quantile estimation in deconvolution with ordinary smooth error distributions. In particular, we focus on the more realistic setup of unknown error distributions. We develop a ...
Statistically adaptive learning for a general class of cost functions (SA L-BFGS)
Statistically adaptive learning general class cost functions
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2012/11/23
We present a system that enables rapid model experimentation for tera-scale machine learning with trillions of non-zero features, billions of training examples, and millions of parameters. Our contrib...
Bayesian Adaptive Smoothing Spline using Stochastic Differential Equations
Adaptive smoothing Markov chain Monte Carlo Smoothing spline Stochastic dierential equation
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2012/11/22
The smoothing spline is one of the most popular curve-fitting methods, partly because of empirical evidence supporting its effectiveness and partly because of its elegant mathematical formulation. How...
Adaptive Markov Chain Monte Carlo confidence intervals
Adaptive Markov Chain Monte Carlo confidence intervals
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2012/11/22
In Adaptive Markov Chain Monte Carlo (AMCMC) simulation, classical estimators of asymptotic variances are inconsistent in general. In this work we establish that despite this inconsistency, confidence...