Efficient Estimation for Models With Nonlinear Heteroscedasticity
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2021/07/12
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Indian UGC (journal)
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Refrences35
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Citations1
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Zhanxiong Xu Department of Statistics, Penn State University, University Park, PA
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Zhibiao Zhao Department of Statistics, Penn State University, University Park, PA
Cite
Xu, Zhanxiong, and Zhibiao Zhao. “Efficient Estimation for Models With Nonlinear Heteroscedasticity”. Journal of Business &Amp; Economic Statistics, vol. 40, no. 4, 2021, pp. 1498-0, https://doi.org/10.1080/07350015.2021.1933991.
Xu, Z., & Zhao, Z. (2021). Efficient Estimation for Models With Nonlinear Heteroscedasticity. Journal of Business &Amp; Economic Statistics, 40(4), 1498-1508. https://doi.org/10.1080/07350015.2021.1933991
Xu, Zhanxiong, and Zhibiao Zhao. “Efficient Estimation for Models With Nonlinear Heteroscedasticity”. Journal of Business &Amp; Economic Statistics 40, no. 4 (2021): 1498-1508. https://doi.org/10.1080/07350015.2021.1933991.
Xu Z, Zhao Z. Efficient Estimation for Models With Nonlinear Heteroscedasticity. Journal of Business & Economic Statistics. 2021;40(4):1498-50.
Journal Categories
Science
Mathematics
Probabilities
Mathematical statistics
Social Sciences
Commerce
Business
Social Sciences
Economic theory
Demography
Economics as a science
Social Sciences
Statistics
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Title | 2016 | |||
| Title | Kybernetika |
| 1984 | |
| Title | American Economic Review |
| 1975 | |
| Volatility and Time Series Econometrics: Essays in Honor of Robert F. Engle | 2008 | |||
| Almost Sure Convergence | 1974 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Non‐crossing quantile double‐autoregression for the analysis of streaming time series data | Journal of Time Series Analysis |
| 1 | 2023 |
Citations Analysis
| Category | Category Repetition |
|---|---|
| Science: Mathematics | 1 |
| Science: Mathematics: Probabilities. Mathematical statistics | 1 |
The category
Science: Mathematics 1
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Non‐crossing quantile double‐autoregression for the analysis of streaming time series data and was published in 2023. The most recent citation comes from a 2023 study titled Non‐crossing quantile double‐autoregression for the analysis of streaming time series data. This article reached its peak citation in 2023, with 1 citations. It has been cited in 1 different journals. Among related journals, the Journal of Time Series Analysis cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.