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Testing Additive Separability of Error Term in Nonparametric Structural Models
Additive Separability Hypotheses Testing Nonparametric Structural Equation Non- separable Models
2016/1/25
This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model non-additively.We...
Assessing the significance of global and local correlations under spatial autocorrelation;a nonparametric approach
Geostatistics Monte-Carlo methods Resampling Spatial autocorrelation Spatial statistics Variogram
2015/8/21
In this paper we present a method to assess the significance of the correlation coefficient when at least one of the variables is spatially autocorrelated. The standard test assumes independence of th...
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...
A nonparametric CUSUM control chart based on the Mann-Whitney statistic
Change-point Mann-Whitney statistic cumulative sum chart
2013/6/14
This article aims to consider a new univariate nonparametric cumulative sum (CUSUM) control chart for small shift of location based on both change-point model and Mann-Whitney statistic. Some comparis...
Moderate deviations for a nonparametric estimator of sample coverage
Sample coverage moderate deviations Good’s estimator
2013/6/14
In this paper, we consider moderate deviations for Good's coverage estimator. The moderate deviation principle and the self-normalized moderate deviation principle for Good's coverage estimator are es...
Functional and Parametric Estimation in a Semi- and Nonparametric Model with Application to Mass-Spectrometry Data
Local linear regression Bandwidth selection Nonparamet-ric estimation
2013/6/13
Motivated by modeling and analysis of mass-spectrometry data, a semi- and nonparametric model is proposed that consists of a linear parametric component for individual location and scale and a nonpara...
Simultaneous L^2- and L^inf-Adaptation in Nonparametric Regression
Adaptive estimation nonparametric regression thresholding wavelets
2013/4/27
Consider the nonparametric regression framework. It is a classical result that the minimax rates for L^2- and L^inf-risk over a H\"older ball with smoothness index \beta are n^(-\beta/(2\beta+1)) and ...
Nonparametric functionals as generalized functions
Nonparametric functionals generalized functions
2013/4/27
The paper considers probability distribution, density, conditional distribution and density and conditional moments as well as their kernel estimators in spaces of generalized functions. This approach...
Nonparametric Independence Screening in Sparse Ultra-High Dimensional Varying Coefficient Models
Sure independence screening Variable selection Sparsity Conditional permutation False posi-tive rates
2013/4/27
The varying-coefficient model is an important nonparametric statistical model that allows us to examine how the effects of covariates vary with exposure variables. When the number of covariates is big...
Nonparametric Independence Screening in Sparse Ultra-High Dimensional Varying Coefficient Models
Sure independence screening Variable selection Sparsity Conditional permutation False posi-tive rates
2013/4/27
The varying-coefficient model is an important nonparametric statistical model that allows us to examine how the effects of covariates vary with exposure variables. When the number of covariates is big...
This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of mo...
Nonparametric testing for no-effect with functional responses and functional covariates
functional data regression nearest neighbors smoothing nonparametric testing
2012/11/22
This paper studies the problem of nonparametric testing for the no-effect of a random functional covariate on a functional response. That means testing whether the conditional expectation of the respo...
Nonparametric instrumental regression with non-convex constraints
Nonparametric instrumental regression non-convex constraints
2012/11/21
This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also ...
Nonparametric estimation of multivariate extreme-value copulas
empirical copula extreme-value copula Pickands dependence function
2011/7/19
Extreme-value copulas arise in the asymptotic theory for componentwise maxima of independent random samples. An extreme-value copula is determined by its Pickands dependence function, which is a funct...
Density Estimation and Classification via Bayesian Nonparametric Learning of Affine Subspaces
Dimension reduction Classi er Variable selection Nonparametric Bayes
2011/6/20
It is now practically the norm for data to be very high dimensional in areas such as genetics, machine
vision, image analysis and many others. When analyzing such data, parametric models are often to...