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Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models

Cizek, Pavel - 2009

sensitive to misspecification and data errors. This sensitivity addressed by the theory of robust statistics which builds upon …

Persistent link: https://www.econbiz.de/10013154935

Regression Discontinuity in Time : Considerations for Empirical Applications

Hausman, Catherine - 2017

Recent empirical work in several economic fields, particularly environmental and energy economics, has adapted the regression discontinuity (RD) framework to applications where time is the running variable and treatment begins at a particular threshold in time. In this guide for practitioners,...

Persistent link: https://www.econbiz.de/10012951355

Adaptive Bayesian Inference in Nonlinear Regression Models

Yang, Ji Yeon - 2017

There has been continuing interest in Bayesian regressions without imposing any parametric assumption on the error distribution, but the asymptotic efficiency of such procedures has not been fully understood yet. In this article, we consider semiparametric Bayesian nonlinear regression models....

Persistent link: https://www.econbiz.de/10012958697

Numerical Techniques of Nonlinear Regression Model Estimation

Donthi, Dr Ranadheer - 2020

The literature on numerical methods for fitting nonlinear regression model has grown enormously in the fast five decades. An important phase in nonlinear regression problems is the exploration of the relation between the independent and dependent variables. A largely unexplored area of research...

Persistent link: https://www.econbiz.de/10012824412

Comparing Old and New Partial Derivative Estimates from Nonlinear Nonparametric Regressions : Supplemental Materials

Vinod, Hrishikesh D. - 2020

Persistent link: https://www.econbiz.de/10012824663

Comparing Old and New Partial Derivative Estimates from Nonlinear Nonparametric Regressions

Vinod, Hrishikesh D. - 2020

Partial derivatives have a special place in economics since the marginal revolution of the 1850s. We present results from multivariate partial derivative estimates using nonlinear non-parametric regressions in a finite difference method, accessible via the R-package NNS. Numerical partial...

Persistent link: https://www.econbiz.de/10012824721

Model Specification Testing for Nonlinear Multivariate Cointegrating Regressions

Dong, Chaohua - 2016

the resulting asymptotic theory is established. The test statistic is constructed based on a natural distance function …

Persistent link: https://www.econbiz.de/10013006720

Model Averaging for Nonlinear Regression Models

Feng, Yang - 2020

This paper considers the problem of model averaging for regression models that can be nonlinear in their parameters and variables. We consider a nonlinear model averaging (NMA) framework and propose a weight-choosing criterion, the nonlinear information criterion (NIC). We show that up to a...

Persistent link: https://www.econbiz.de/10012855034

Nonlinear Cointegrating Power Function Regression with Endogeneity

Hu, Zhishui - 2019

This paper develops an asymptotic theory for nonlinear cointegrating power function regression. The framework extends …. Accompanying the asymptotic theory of nonlinear regression, the paper establishes some new results on weak convergence to … stochastic integrals that go beyond the usual semi-martingale structure and considerably extend existing limit theory …

Persistent link: https://www.econbiz.de/10012858171

Simultaneous Confidence Bands in Nonlinear Regression Models with Nonstationarity

Li, Degui - 2015

We consider nonparametric estimation of the regression function g(*) in a nonlinear regression model Yt = g(Xt) o(Xt)et, where the regressor Xt is a nonstationary unit root process and the error et is s sequence of independent and identically distributed (i.i.d.) random variables. With proper...

Persistent link: https://www.econbiz.de/10013018853