A simple resampling method by perturbing the minimand

By Zhezhen Jin, Zhiliang Ying, Lee-Jen Wei. 2001

314 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/851a56d66159c09eab5b2376d51111f01fb1ebf7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Mai Zhou
2. Ling Zhou
3. Chenlei Leng
4. K. Zhu
5. Xingwei Tong
6. Yijian Huang
7. S. Ling
8. Limin Peng

In Management Science and Operations Research

1. K. Zhu
2. S. Ling
3. Ling Zhou
4. Mai Zhou
5. Chenlei Leng
6. Xingwei Tong
7. Yijian Huang
8. Limin Peng

In Statistics and Probability

1. K. Zhu
2. Chenlei Leng
3. S. Ling
4. Xingwei Tong
5. Zhiliang Ying
6. Ling Zhou
7. Mai Zhou
8. Christopher C. Holmes

Citations in the corpus

• Survival Analysis With Quantile Regression Models (2008, methodology): “In this section we propose to use a simple resampling approach that generalizes the minimand perturbing technique proposed by Jin et al. (2001) to the situation considered here with functional estimands.”
• Empirical likelihood analysis of the rank estimator for the censored accelerated failure time model (2005, methodology): “tional methods, Jin et al. (2003) use a resampling method, based on Jin et al. (2001) , in”
• Analysis of least absolute deviation (2008, methodology): “In particular, it has many applications in econometrics and biomedical studies; see Koenker and Bassett (1978), Powell (1984), Buchinsky (1998), Jin, Ying and Wei (2001), among many others.”
• Martingale posterior distributions (2021, background): “One interpretation of the Dirichlet weights is to generate uncertainty through the randomization of the objective function (Newton and Raftery, 1994; Jin et al., 2001; Newton et al., 2020; Ng and Newton, 2020).”
• LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises (2015, methodology): “This approach, as a variant of the traditional wild bootstrap in Wu (1986), was originally proposed by Jin, Ying, and Wei (2001) and provides a way to do statistical inference when the covariance matrix of the estimator cannot be estimated by the conventional methods, see, for example, Chen et al.…”
• A simple censored median regression estimator (2006, methodology): “it is rather di¢ cult to obtain a Wald-type con…dence interval estimate for �. We will develop a resampling scheme similar to Jin, Ying and Wei (2001) to approximate the distribution of ^ �2: To be speci…c, we de…ne”
• A quantile regression estimator for censored data (2013, methodology): “As a consequence, inferential procedures such as the resampling approach in Jin, Ying and Wei [6], or the bootstrap method, can be prohibitive computationally.”
• Partial rank estimation of duration models with general forms of censoring (2007, unknown): “For one, a recent ‘‘wild’’ sampling procedure introduced in Jin, Ying and Wei (2002) appears likely to be applicable (after appropriate modifications)11 to the problem at hand.”
• Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution (2001, background): “A general resampling procedure that repeatedly perturbs a minimand stochastically has been extensively studied by Jin, Ying, and Wei (2001).”