Imposing Economic Constraints in Nonparametric Regression: Survey, Implementation and Extension [PDF]
Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated.
Parmeter, Christopher F. +1 more
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Nonparametric statistical methods using R
, 2014 A Practical Guide to Implementing Nonparametric and Rank-Based ProceduresNonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple ...
Kloke, John, McKean, Joseph W
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Comments on “A Selective Overview of Nonparametric Methods in Financial Econometrics” by Jianqing Fan [PDF]
Our comments on Fan’s paper will concentrate on two issues that relate in important ways to the paper’s focus on misspecification and discretization bias and the role of nonparametric methods in empirical finance.
Jun Yu, Peter C. B. Phillips
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Simple nonparametric estimators for unemployment duration analysis [PDF]
"We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor.
Wilke, Ralf A., Wichert, Laura
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IDENTIFICATION AND ESTIMATION OF NONPARAMETRIC STRUCTURAL [PDF]
This paper concerns a new statistical approach to instrumental variables (IV) method for nonparametric structural models with additive errors. A general identifying condition of the model is proposed, based on richness of the space generated by marginal ...
Woocheol Kim
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Resampling from the past to improve on MCMC algorithms [PDF]
We introduce the idea that resampling from past observations in a Markov Chain Monte Carlo sampler can fasten convergence. We prove that proper resampling from the past does not disturb the limit distribution of the algorithm.
Yves Atchade
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Nonparametric Specification Testing for Nonlinear Time Series with Nonstationarity [PDF]
This paper considers a nonparametric time series regression model with a nonstationary regressor. We construct a nonparametric test for testing whether the regression is of a known parametric form indexed by a vector of unknown parameters.
Zudi Lu +3 more
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Sample sizes for the SF-6D preference based measure of health from the SF-36: a practical guide [PDF]
Background Health Related Quality of Life (HRQoL) measures are becoming more frequently used in clinical trials and health services research, both as primary and secondary endpoints.
Walters, SJ, Brazier, JE
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Conditional quantile processes based on series or many regressors [PDF]
Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework,
Victor Chernozhukov +2 more
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A Bistochastic Nonparametric Estimator [PDF]
We explore the relevance of adopting a bistochastic nonparametric estimator. This estimator has two main implications. First, the estimator reduces variability according to the robust criterion of second-order stochastic (and Lorenz) dominance. This is a
Rafael Salas, Juan Gabriel Rodríguez
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