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Efficient Estimation of Nonparametric Simultaneous Equations Models
Local Polynomial Regression Nonparametric Additive Models Structural Models Instrumental Variables
2016/1/26
This paper defines a new procedure to efficiently estimate nonparametric simultaneous e-quations models that have been explored by Newey et al (1999) and Su and Ullah (2008).The proposed estimation pr...
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...
Efficient Estimation of Nonparametric Simultaneous Equations Models
Local Polynomial Regression Nonparametric Additive Models Structural Models Instrumental Variables
2016/1/20
This paper defines a new procedure to efficiently estimate nonparametric simultaneous e-quations models that have been explored by Newey et al (1999) and Su and Ullah (2008).The proposed estimation pr...
Testing Additive Separability of Error Term in Nonparametric Structural Models
Additive Separability Hypotheses Testing Nonparametric Structural Equation
2016/1/20
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...
Nonparametric and Semiparametric Regressions Subject to Monotonicity Constraints: Estimation and Forecasting
Nonlinearity Nonparametric regression Semiparametric regression Local mono- tonicity Bagging
2016/1/20
This paper considers nonparametric and semiparametric regression models subject to monotonicity constraint. We use bagging as an alternative approach to Hall and Huang(2001). Asymptotic properties of ...
Nonparametric Regression with Discrete Covariate and Missing Values
Nonparametric Regression Discrete kernel smoothing Imputation Missing Values Variance Reduction
2016/1/19
We consider nonparametric regression with a mixture of continuous and discrete ex-planatory variables where realizations of the response variable may be missing. An impu-tation based nonparametric reg...
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...
Nonparametric Estimation of Tail Probabilities for the Single-Server Queue
Nonparametric Estimation Tail Probabilities Single-Server Queue
2015/7/8
We consider the estimation of tail probabilities in queues via the nonparametric estimator constructed by simple computing the observed fraction of time that the queue is out in the tail. We show that...
A Nonparametric Approach to Multiproduct Pricing
pricing:multiproduct pricing marketing: buyer behavior choice models
2015/7/6
Developed by General Motors (GM), the Auto Choice Advisor website (http://www.autochoiceadvisor.com) recommends vehicles to consumers based on their requirements and budget constraints. Through the we...
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...
Switching Nonparametric Regression Models and the Motorcycle Data revisited
nonparametric regression machine learning mixture of Gaussian processes latent variables EM algorithm motorcy-cle data
2013/6/14
We propose a methodology to analyze data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y depends on a covariate...
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 ...