Browsing by Subject "Nonparametric regression"
Now showing items 1-14 of 14
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A comparative simulation study of wavelet shrinkage estimators for Poisson counts
(2004)Using computer simulations, the finite sample performance of a number of classical and Bayesian wavelet shrinkage estimators for Poisson counts is examined. For the purpose of comparison, a variety of intensity functions, ...
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Dynamic misspecification in nonparametric cointegrating regression
(2012)Linear cointegration is known to have the important property of invariance under temporal translation. The same property is shown not to apply for nonlinear cointegration. The limit properties of the Nadaraya-Watson (NW) ...
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Empirical bayes approach to wavelet regression using ε-contaminated priors
(2004)We consider an empirical Bayes approach to standard nonparametric regression estimation using a nonlinear wavelet methodology. Instead of specifying a single prior distribution on the parameter space of wavelet coefficients, ...
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Frequentist optimality of bayes factor estimators in wavelet regression models
(2007)We investigate the theoretical performance of Bayes factor estimators in wavelet regression models with independent and identically distributed errors that are not necessarily normally distributed. We compare these estimators ...
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Minimax rates of convergence and optimality of bayes factor wavelet regression estimators under pointwise risks
(2009)We consider function estimation in nonparametric regression over Besov spaces and under pointwise lu-risks (1 ≤ u < ∞). First we derive both non-adaptive and adaptive minimax pointwise rates of convergence in the standard ...
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Nonparametric predictive regression
(2015)A unifying framework for inference is developed in predictive regressions where the predictor has unknown integration properties and may be stationary or nonstationary. Two easily implemented nonparametric F-tests are ...
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Nonparametric regression estimation based on spatially inhomogeneous data: Minimax global convergence rates and adaptivity
(2014)We consider the nonparametric regression estimation problem of recovering an unknown response function f on the basis of spatially inhomogeneous data when the design points follow a known density g with a finite number of ...
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Nonparametric regression with infinite order flat-top kernels
(2004)The problem of nonparametric regression is addressed, and a kernel smoothing estimator is proposed which has favorable asymptotic performance (bias, variance and mean squared error). The proposed class of kernels is ...
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On pointwise optimality of Bayes factor wavelet regression estimators
(2006)We investigate the theoretical performance of Bayes factor estimators at a single point in wavelet regression models with independent and identically distributed errors that are not necessarily normally distributed. We ...
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Optimal testing for additivity in multiple nonparametric regression
(2009)We consider the problem of testing for additivity in the standard multiple nonparametric regression model. We derive optimal (in the minimax sense) non- adaptive and adaptive hypothesis testing procedures for additivity ...
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Wavelet analysis and its statistical applications
(2000)In recent years there has been a considerable development in the use of wavelet methods in statistics. As a result, we are now at the stage where it is reasonable to consider such methods to be another standard tool of the ...
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Wavelet estimators in nonparametric regression: A comparative simulation study
(2001)Wavelet analysis has been found to be a powerful tool for the nonparametric estimation of spatially-variable objects. We discuss in detail wavelet methods in nonparametric regression, where the data are modelled as ...
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Wavelet shrinkage for natural exponential families with quadratic variance functions
(2001)We propose a wavelet shrinkage methodology for univariate natural exponential families with quadratic variance functions, covering the Gaussian, Poisson, gamma, binomial, negative binomial and generalised hyperbolic secant ...
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Wavelet thresholding via a Bayesian approach
(1998)We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in nonparametric regression. A prior distribution is imposed on the wavelet coefficients of the unknown response function, designed ...