Asymptotic equivalence of density estimation and Gaussian white noise
From MaRDI portal
Publication:1354435
DOI10.1214/aos/1032181160zbMath0867.62035OpenAlexW2071325635MaRDI QIDQ1354435
Publication date: 3 August 1997
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1032181160
Gaussian white noiseHungarian constructionempirical processasymptotic minimax riskcurve estimationLe Cam's deficiency distancelikelihood processGaussian regressionbounded lossheteroscedastic Gaussian approximation
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Theory of statistical experiments (62B15) Inference from stochastic processes (62M99)
Related Items
An asymptotic analysis of distributed nonparametric methods, Use of goodness-of-fit procedures in high dimensional testing, Sharp adaptive estimation by a blockwise method, Optimal wavelet estimators of the heteroscedastic pointspread effects and Gauss white noises model, Minimax estimation of low-rank quantum states and their linear functionals, A refined continuity correction for the negative binomial distribution and asymptotics of the median, Asymptotically Minimax Nonparametric Regression in L2, Nonparametric hypothesis testing with small type I or type II error probabilities, Le cam theory on the comparison of statistical models, EFFICIENT ESTIMATION OF INTEGRATED VOLATILITY AND RELATED PROCESSES, Non- and semiparametric statistics: compared and contrasted, Thresholding algorithms, maxisets and well-concentrated bases, On Asymptotic Minimaxity of Kernel-based Tests, Minimax and bayes estimation in deconvolution problem, An asymptotically optimal test for a parametric set of regression functions against a non-parametric alternative, Adaptation to lowest density regions with application to support recovery, Rate exact Bayesian adaptation with modified block priors, Kalman-Based Stochastic Gradient Method with Stop Condition and Insensitivity to Conditioning, Can We Trust Bayesian Uncertainty Quantification from Gaussian Process Priors with Squared Exponential Covariance Kernel?, Minimax nonparametric estimation of pure quantum states, Sharp adaptive estimation of quadratic functionals, Asymptotic equivalence of discretely observed diffusion processes and their Euler scheme: small variance case, Statistical properties of the method of regularization with periodic Gaussian reproducing kernel, Distributed nonparametric function estimation: optimal rate of convergence and cost of adaptation, Estimation of the density of regression errors, On adaptive estimation of linear functionals, Estimation from moments measurements for amyloid depolymerisation, Minimax and adaptive inference in nonparametric function estimation, The root-unroot algorithm for density estimation as implemented via wavelet block thresholding, Asymptotic equivalence of spectral density estimation and Gaussian white noise, Adaptive hypothesis testing using wavelets, A constrained risk inequality with applications to nonparametric functional estimation, Wavelet thresholding in anisotropic function classes and application to adaptive estimation of evolutionary spectra, A continuous Gaussian approximation to a nonparametric regression in two dimensions, Minimax linear estimation in a white noise problem, A complement to Le Cam's theorem, Tusnády's inequality revisited, Asymptotic statistical equivalence for ergodic diffusions: the multidimensional case, Optimal pointwise adaptive methods in nonparametric estimation, Superefficiency in nonparametric function estimation, Asymptotically sufficient statistics in nonparametric regression experiments with correlated noise, Radial basis function regularization for linear inverse problems with random noise, A regularity class for the roots of nonnegative functions, Adaptive testing on a regression function at a point, Limit experiments of GARCH, Lower bound for the oracle projection posterior convergence rate, Asymptotic equivalence for nonparametric regression with non-regular errors, Larry Brown's contributions to parametric inference, decision theory and foundations: a survey, Gaussianization machines for non-Gaussian function estimation models, Honest Bayesian confidence sets for the \(L^2\)-norm, Asymptotic equivalence for pure jump Lévy processes with unknown Lévy density and Gaussian white noise, Information bounds for inverse problems with application to deconvolution and Lévy models, Quantile coupling inequalities and their applications, Minimax hypothesis testing for curve registration, Asymptotic equivalence of functional linear regression and a white noise inverse problem, Optimal calibration for multiple testing against local inhomogeneity in higher dimension, Minimax goodness-of-fit testing in multivariate nonparametric regression, Model selection and sharp asymptotic minimaxity, Asymptotic equivalence of nonparametric autoregression and nonparametric regression, Large-sample study of the kernel density estimators under multiplicative censoring, Asymptotic minimax risk of predictive density estimation for non-parametric regression, Nonparametric signal detection with small type I and type II error probabilities, A general framework for Bayes structured linear models, Statistical convergence of Markov experiments to diffusion limits, Estimation and detection of high-variable functions from Sloan-Woźniakowski space, Adaptive Bayesian inference on the mean of an infinite-dimensional normal distribution, Adaptive estimation of and oracle inequalities for probability densities and characteristic functions, Nonparametric estimators which can be ``plugged-in., Asymptotic equivalence for regression under fractional noise, Asymptotic equivalence for nonparametric regression with multivariate and random design, The Le Cam distance between density estimation, Poisson processes and Gaussian white noise, Strong Gaussian approximation of the mixture Rasch model, Local asymptotic equivalence of pure states ensembles and quantum Gaussian white noise, Robust nonparametric estimation via wavelet median regression, On information pooling, adaptability and superefficiency in nonparametric function estimation, Optimal rates of entropy estimation over Lipschitz balls, A maxiset approach of a Gaussian noise model, Equivalence theory for density estimation, Poisson processes and Gaussian white noise with drift, Asymptotic equivalence for inference on the volatility from noisy observations, On minimax density estimation on \(\mathbb R\), Maxisets for model selection, Adaptive nonparametric confidence sets, Adaptive minimax estimation of a fractional derivative, Asymptotic equivalence for inhomogeneous jump diffusion processes and white noise, General empirical Bayes wavelet methods and exactly adaptive minimax estimation, Asymptotic equivalence of nonparametric diffusion and Euler scheme experiments, Adaptive filtering of a random signal in Gaussian white noise, Nonparametric hypothesis testing for intensity of the Poisson process, Adaptation bounds for confidence bands under self-similarity, Asymptotic nonequivalence of density estimation and Gaussian white noise for small densities, Cross-validation for comparing multiple density estimation procedures, On the posterior pointwise convergence rate of a Gaussian signal under a conjugate prior, Estimating the intensity of a random measure by histogram type estimators, A review of uncertainty quantification for density estimation, Asymptotic nonequivalence of nonparametric experiments when the smoothness index is \(1/2\), New goodness-of-fit tests and their application to nonparametric confidence sets, Regression-type inference in nonparametric autoregression, Empirical Bayesian test of the smoothness, On the Le Cam distance between multivariate hypergeometric and multivariate normal experiments, On distinguishability of two nonparametric sets of hypothesis, Asymptotic equivalence and adaptive estimation for robust nonparametric regression, Asymptotic equivalence for nonparametric regression with dependent errors: Gauss-Markov processes, Bayesian aspects of some nonparametric problems, Tensor product space ANOVA models., Multiscale testing of qualitative hypotheses, Generalized likelihood ratio statistics and Wilks phenomenon, Sharp adaptive estimation of linear functionals., Random rates in anisotropic regression. (With discussion), The statistical work of Lucien Le Cam., Asymptotic equivalence theory for nonparametric regression with random design, Deficiency distance between multinomial and multivariate normal experiments, Asymptotic equivalence of estimating a Poisson intensity and a positive diffusion drift, Asymptotic nonequivalence of GARCH models and diffusions, A functional Hungarian construction for the sequential empirical process, Testing the regularity of a smooth signal, Curve registration by nonparametric goodness-of-fit testing, The Bayesian analysis of complex, high-dimensional models: can it be CODA?, Lower bounds for the asymptotic minimax risk with spherical data, Asymptotic statistical equivalence for scalar ergodic diffusions
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Estimation of square-integrable probability density of a random variable
- Sur l'approximation de familles de mesures par des familles gaussiennes
- Mathematical theory of statistics. Statistical experiments and asymptotic decision theory
- Spline smoothing in regression models and asymptotic efficiency in \(L_ 2\)
- Asymptotic methods in statistical decision theory
- The statistical information contained in additional observations
- Optimal filtering of square-integrable signals in Gaussian noise
- Renormalization and white noise approximation for nonparametric functional estimation problems
- Renormalization exponents and optimal pointwise rates of convergence
- Poisson approximation of empirical processes
- Square integrable martingales orthogonal to every stochastic integral
- Komlós-Major-Tusnády approximation for the general empirical process and Haar expansions of classes of functions
- Local invariance principles and their application to density estimation
- Asymptotic minimax risk for sup-norm loss: Solution via optimal recovery
- Asymptotic equivalence of nonparametric regression and white noise
- Minimax estimation via wavelet shrinkage
- On minimax filtering over ellipsoids
- A course on point processes
- Asymptotic minimax theorems for the sample distribution function
- LAN in Problems of Nonparametric Estimation of Functions and Lower Bounds for Quadratic Risks
- An Asymptotically Minimax Regression Estimator in the Uniform Norm up to Exact Constant
- On the Maximum Deviation of the Sample Density