Nonparametric estimation of marginal effects in regression-spline random effects models
DOI10.1080/07474938.2020.1772569zbMath1490.62101OpenAlexW3035939009MaRDI QIDQ5861013
Jeffrey S. Racine, Aman Ullah, Shujie Ma
Publication date: 4 March 2022
Published in: Econometric Reviews (Search for Journal in Brave)
Full work available at URL: https://pure.au.dk/portal/da/publications/nonparametric-estimation-of-marginal-effects-in-regressionspline-random-effects-models(24742e74-ed07-453d-980a-213721e17132).html
Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Nonparametric estimation and testing of fixed effects panel data models
- Parameter estimation for a generalized semiparametric model with repeated measurements
- Semiparametric and nonparametric methods in econometrics
- Additive regression and other nonparametric models
- Nonparametric statistics for stochastic processes. Estimation and prediction.
- Consistency of two-step sample selection estimators despite misspecification of distribution
- The use of polynomial splines and their tensor products in multivariate function estimation. (With discussion)
- Convergence rate of sieve estimates
- Bézier and B-spline techniques
- Spectral bounds for \(\| A^{-1}\| _{\infty}\)
- Simultaneous variable selection and estimation in semiparametric modeling of longitudinal/clustered data
- Spline-backfitted kernel smoothing of nonlinear additive autoregression model
- Algorithm 909
- A jump-detecting procedure based on spline estimation
- Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models
- Efficient Estimation in Marginal Partially Linear Models for Longitudinal/Clustered Data Using Splines
- Uniform Convergence in Probability and Stochastic Equicontinuity
- Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
- The Asymptotic Variance of Semiparametric Estimators
- Marginal nonparametric kernel regression accounting for within-subject correlation
- Additive regression splines with irrelevant categorial and continuous regressors
- Equivalent kernels of smoothing splines in nonparametric regression for clustered/longitudinal data
- Efficient Semiparametric Marginal Estimation for Longitudinal/Clustered Data
- A practical guide to splines.
This page was built for publication: Nonparametric estimation of marginal effects in regression-spline random effects models