Asymptotic properties for estimates of nonparametric regression models based on negatively associated sequences

By Han-Ying Liang, Bing-Yi Jing. 2005

128 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/99541cb5aa2c16bc1be4dbf8a44f54c8bd53b8f9

How researchers see this paper

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

In Artificial Intelligence

1. Shuhe Hu
2. Xuejun Wang
3. Andrei Volodin
4. Chen Xu
5. Tien-Chung Hu
6. Aiting Shen

In Management Science and Operations Research

1. Aiting Shen
2. Shuhe Hu
3. Xuejun Wang
4. Andrei Volodin
5. Chen Xu
6. Lulu Zheng
7. Tien-Chung Hu
8. Yi Wu

In Statistics and Probability

1. Aiting Shen
2. Shuhe Hu
3. Xuejun Wang
4. Chen Xu
5. Andrei Volodin
6. Lulu Zheng
7. Tien-Chung Hu
8. Anna Kuczmaszewska

Citations in the corpus

• On complete convergence for widely orthant-dependent random variables and its applications in nonparametric regression models (2014, methodology): “Remark 4.3 Theorem 4.2 under NA errors is considered by Liang and Jing (2005), so the result of Theorem 4.2 generalizes the corresponding one of Liang and Jing (2005) under NA errors to the case of WOD errors.”
• Complete convergence for weighted sums of END random variables and its application to nonparametric regression models (2016, background): “The class of estimator (7) was first introduced by Stone (1977) and next adapted by Georgiev (1985) to the fixed design case.”
• Bernstein-Type Inequality for Widely Dependent Sequence and Its Application to Nonparametric Regression Models (2013, background): “Yang et al. [12] generalized the results of Liang and Jing [11] for negatively associated sequences to the case of negatively orthant dependent sequences and obtained the strong consistency for the estimator of the nonparametric regression models based on negatively orthant dependent errors.”
• Complete consistency for the estimator of nonparametric regression models based on extended negatively dependent errors (2015, background): “Liang and Jing [25] presented some asymptotic properties for estimates of nonparametric regression models based on negatively associated sequences, Yang et al.”
• Complete convergence for arrays of rowwise negatively superadditive-dependent random variables and its applications (2016, background): “One can refer to Liang and Jing [15], Yang et al.”