Robust Continuous Quadratic Distance Estimation Using Quantiles for Fitting Continuous Distributions

• 作者: Andrew Luong
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: COVARIANCE Kernel Influence Function HILBERT Space Linear Operator GMM Estimation Spectral Decomposition
• 年，卷（期）: 2019,（4）
• 页码范围: 421-435
• 页数: 15页
• 分类号: O1

摘要

Quadratic distance estimation making use of the sample quantile function over a continuous range is introduced. It extends previous methods which are based only on a few sample quantiles and it parallels the continuous GMM method. Asymptotic properties are established for the continuous quadratic distance estimators (CQDE) and the implementation of the methods are discussed. The methods appear to be useful for balancing robustness and efficiency and useful for fitting distribution with model quantile function being simpler than its density function or distribution function.