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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...
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 ...
Adaptive estimation in the nonparametric random coefficients binary choice model by needlet thresholding
Discrete choice models random coefficients inverse problems
2011/7/6
In this article we consider the estimation of the joint distribution of the random coefficients and error term in the nonparametric random coefficients binary choice model. In this model from economic...
Bayesian nonparametric estimation and consistency of mixed multinomial logit choice models
Bayesian consistency blocked Gibbs sampler discrete choice models mixed multinomial logit random probability measures stick-breaking priors
2011/3/24
This paper develops nonparametric estimation for discrete choice models based on the mixed multinomial logit (MMNL) model. It has been shown that MMNL models encompass all discrete choice models deriv...
Tight conditions for consistent variable selection in high dimensional nonparametric regression
variable selection high dimensional nonparametric regression
2011/3/22
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of covariates is very large. The main focus is on the situation where the nu...
Nonparametric regression with filtered data
censoring counting process theory hazard functions kernel estimation local linear estimation truncation
2011/3/21
We present a general principle for estimating a regression function nonparametrically, allowing for a wide variety of data filtering, for example, repeated left truncation and right censoring. Both th...
A nonparametric urn-based approach to interacting failing systems with an application to credit risk modeling
Failing system Urn model Neutral to the right processes
2010/10/19
In this paper we propose a new nonparametric approach to interacting failing systems (FS), that is systems whose probability of failure is not negligible in a fixed time horizon, a typical example be...