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An Adaptive Sequential Monte Carlo Algorithm for Computing Permanents
Sequential Monte Carlo Permanents Relative Variance
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
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
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
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
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 Bayes test for monotonicity
Bayesian Nonparametric Nonparametric regression Nonparamet-ric hypothesis testing Asymptotic properties
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
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
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...
Adaptive quantile estimation in deconvolution with unknown error distribution
Deconvolution Quantile and distribution function Adaptive es-timation Minimax convergence rates Random Fourier multiplier
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 ...
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors
Adaptive nonparametric estimation Deconvolution Fluorescence lifetimes
2010/11/8
Motivated by fluorescence lifetime measurements this paper considers the problem of nonparametric density estimation in the pile-up model. Adaptive nonparametric estimators are proposed for the pile-u...