Subsampling inference in cube root asymptotics with an application to Manski's maximum score estimator.

DOI10.1016/S0165-1765(01)00494-3zbMath1056.91546OpenAlexW2045637015WikidataQ29544541 ScholiaQ29544541MaRDI QIDQ5958691

No author found.

Publication date: 3 March 2002

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-1765(01)00494-3

zbMATH Keywords

Cube root asymptoticsHypothesis testsSubsampling

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Inference from stochastic processes (62M99) Statistical methods; economic indices and measures (91B82) Functional limit theorems; invariance principles (60F17)

Related Items (25)

Semiparametric estimation of a binary response model with a change-point due to a covariate threshold ⋮ Quantile regression models for current status data ⋮ A consistent bootstrap procedure for the maximum score estimator ⋮ SPECIFICATION TESTING WHEN THE NULL IS NONPARAMETRIC OR SEMIPARAMETRIC ⋮ THE BOOTSTRAP IN THRESHOLD REGRESSION ⋮ Best subset binary prediction ⋮ A multiple variance ratio test using subsampling ⋮ Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes ⋮ Isotonic regression discontinuity designs ⋮ The linear stochastic order and directed inference for multivariate ordered distributions ⋮ Inference for Constrained Estimation of Tumor Size Distributions ⋮ Simulated maximum likelihood estimation for discrete choices using transformed simulated frequencies ⋮ Classical Laplace estimation for \(\root3\of n\)-consistent estimators: improved convergence rates and rate-adaptive inference ⋮ Binary quantile regression with local polynomial smoothing ⋮ Inference on functionals under first order degeneracy ⋮ Semiparametric estimation of the random utility model with rank-ordered choice data ⋮ Subsampling \(p\)-values ⋮ Confidence sets for split points in decision trees ⋮ Unnamed Item ⋮ Comments on: ``An updated review of goodness-of-fit tests for regression models ⋮ Confidence Intervals for Current Status Data ⋮ Binary quantile regression and variable selection: A new approach ⋮ Comparison of Separable Components in Different Samples ⋮ A general approach to categorizing a continuous scale according to an ordinal outcome ⋮ Subsampling vector autoregressive tests of linear constraints

Cites Work

• Cube root asymptotics
• Semiparametric analysis of discrete response. Asymptotic properties of the maximum score estimator
• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Maximum score estimation of the stochastic utility model of choice
• Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
• Subsampling
• Large sample confidence regions based on subsamples under minimal assumptions
• Weak convergence and empirical processes. With applications to statistics
• Estimation of the mode
• Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model
• Consistent Estimation of Scaled Coefficients
• Efficiency Bounds for Distribution-Free Estimators of the Binary Choice and the Censored Regression Models
• A Smoothed Maximum Score Estimator for the Binary Response Model
• An Efficient Semiparametric Estimator for Binary Response Models

This page was built for publication: Subsampling inference in cube root asymptotics with an application to Manski's maximum score estimator.