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7,997
Nonparametric estimation of average treatment effects under exogeneity: a review
 REVIEW OF ECONOMICS AND STATISTICS
, 2004
"... Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described as exogen ..."
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Cited by 630 (25 self)
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Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described
Nonparametric Estimation of Regression Functions
 in the Presence of Irrelevant Regressors.” The Review of Economics and Statistics
, 2007
"... In this paper we propose a method for nonparametric regression which admits continuous and categorical data in a natural manner using the method of kernels. A datadriven method of bandwidth selection is proposed, and we establish the asymptotic normality of the estimator. We also establish the rate ..."
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Cited by 175 (17 self)
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In this paper we propose a method for nonparametric regression which admits continuous and categorical data in a natural manner using the method of kernels. A datadriven method of bandwidth selection is proposed, and we establish the asymptotic normality of the estimator. We also establish
Nonparametric estimation of . . .
 THE CANADIAN JOURNAL OF STATISTICS
, 2003
"... The authors address the problem of estimating an interevent distribution on the basis of count data. They derive a nonparametric maximum likelihood estimate of the interevent distribution utilizing the EM algorithm both in the case of an ordinary renewal process and in the case of an equilibrium r ..."
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The authors address the problem of estimating an interevent distribution on the basis of count data. They derive a nonparametric maximum likelihood estimate of the interevent distribution utilizing the EM algorithm both in the case of an ordinary renewal process and in the case of an equilibrium
Nonparametric Estimation of StatePrice Densities Implicit In Financial Asset Prices
 JOURNAL OF FINANCE
, 1997
"... Implicit in the prices of traded financial assets are ArrowDebreu prices or, with continuous states, the stateprice density (SPD). We construct a nonparametric estimator for the SPD implicit in option prices and derive its asymptotic sampling theory. This estimator provides an arbitragefree metho ..."
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Cited by 339 (6 self)
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Implicit in the prices of traded financial assets are ArrowDebreu prices or, with continuous states, the stateprice density (SPD). We construct a nonparametric estimator for the SPD implicit in option prices and derive its asymptotic sampling theory. This estimator provides an arbitrage
Nonparametric estimation for an autoregressive model
, 806
"... The paper deals with the nonparametric estimation problem at a given fixed point for an autoregressive model with unknown distributed noise. Kernel estimate modifications are proposed. Asymptotic minimax and efficiency properties for proposed estimators are shown. ..."
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Cited by 3 (3 self)
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The paper deals with the nonparametric estimation problem at a given fixed point for an autoregressive model with unknown distributed noise. Kernel estimate modifications are proposed. Asymptotic minimax and efficiency properties for proposed estimators are shown.
NONPARAMETRIC ESTIMATION OF ADDITIVE MODELS
"... This chapter is about nonparametric additive modeling of a conditional mean or quantile function. Nonparametric additive modeling relaxes the restrictive functional form assumptions of parametric modeling while avoiding many of the disadvantages of fully nonparametric estimation. The chapter reviews ..."
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Cited by 2 (2 self)
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This chapter is about nonparametric additive modeling of a conditional mean or quantile function. Nonparametric additive modeling relaxes the restrictive functional form assumptions of parametric modeling while avoiding many of the disadvantages of fully nonparametric estimation. The chapter
Nonparametric Estimation via
"... Abstract A general notion of universal consistency of nonparametric estimators is introduced that applies to regression estimation, conditional median estimation, curve fitting, pattern recognition, and learning concepts. General methods for proving consistency of estimators based on minimizing th ..."
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Abstract A general notion of universal consistency of nonparametric estimators is introduced that applies to regression estimation, conditional median estimation, curve fitting, pattern recognition, and learning concepts. General methods for proving consistency of estimators based on minimizing
NONPARAMETRIC ESTIMATION OF BOUNDARIES·
"... A dataset consists of independent observations taken at the nodes of a grid. An unknown boundary partitions the grid into two regions: All the observations coming from a particular region share a common distribution, but the distributions are different for the two different regions. These two distr ..."
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distributions are entirely unknown, and they need not differ in e their means, medians, or other measure of "level. " The grid is of arbitrary dimension, and its mesh need not be squares. Our objective is to estimate the boundary, using only the observed data. A class of nonparametric estimators
Noncrossing nonparametric estimates of . . .
, 2007
"... In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the problem of crossing quantile curves [calculated for various p ∈ (0, 1)]. The method uses an initial estimate of the conditional distribution function in a first step and solves the problem of inversion a ..."
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In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the problem of crossing quantile curves [calculated for various p ∈ (0, 1)]. The method uses an initial estimate of the conditional distribution function in a first step and solves the problem of inversion
Nonparametric estimation of composite functions
 ANN. STAT
, 2009
"... We study the problem of nonparametric estimation of a multivariate function g:R d → R that can be represented as a composition of two unknown smooth functions f:R→R and G:R d → R. We suppose that f and G belong to known smoothness classes of functions, with smoothness γ and β, respectively. We obtai ..."
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Cited by 13 (1 self)
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We study the problem of nonparametric estimation of a multivariate function g:R d → R that can be represented as a composition of two unknown smooth functions f:R→R and G:R d → R. We suppose that f and G belong to known smoothness classes of functions, with smoothness γ and β, respectively. We
Results 1  10
of
7,997