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Zhibiao Zhao

Personal Details

First Name:Zhibiao
Middle Name:
Last Name:Zhao
Suffix:
RePEc Short-ID:pzh185
http://www.stat.psu.edu/~zuz13

Affiliation

Pennsylvania State University, Department of Statistics

http://www.stat.psu.edu
University Park

Research output

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Jump to: Working papers Articles

Working papers

  1. Zhibiao Zhao, 2008. "Parametric and nonparametric models and methods in financial econometrics," Papers 0801.1599, arXiv.org, revised Mar 2008.

Articles

  1. Seonjin Kim & Zhibiao Zhao, 2013. "Unified inference for sparse and dense longitudinal models," Biometrika, Biometrika Trust, vol. 100(1), pages 203-212.
  2. Zhao, Zhibiao, 2011. "Nonparametric model validations for hidden Markov models with applications in financial econometrics," Journal of Econometrics, Elsevier, vol. 162(2), pages 225-239, June.
  3. Zhibiao Zhao, 2011. "A self-normalized confidence interval for the mean of a class of nonstationary processes," Biometrika, Biometrika Trust, vol. 98(1), pages 81-90.
  4. Zhao, Zhibiao, 2010. "Density estimation for nonlinear parametric models with conditional heteroscedasticity," Journal of Econometrics, Elsevier, vol. 155(1), pages 71-82, March.
  5. Zhao, Zhibiao & Wu, Wei Biao, 2009. "Nonparametric inference of discretely sampled stable Lévy processes," Journal of Econometrics, Elsevier, vol. 153(1), pages 83-92, November.
  6. Zhao, Zhibiao & Wu, Wei Biao, 2007. "Asymptotic theory for curve-crossing analysis," Stochastic Processes and their Applications, Elsevier, vol. 117(7), pages 862-877, July.
  7. Wei Biao Wu & Zhibiao Zhao, 2007. "Inference of trends in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(3), pages 391-410, June.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Zhibiao Zhao, 2008. "Parametric and nonparametric models and methods in financial econometrics," Papers 0801.1599, arXiv.org, revised Mar 2008.

    Cited by:

    1. Zhao, Zhibiao, 2011. "Nonparametric model validations for hidden Markov models with applications in financial econometrics," Journal of Econometrics, Elsevier, vol. 162(2), pages 225-239, June.
    2. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    3. Xuewei Cheng & Gang Li & Hong Wang, 2024. "The concordance filter: an adaptive model-free feature screening procedure," Computational Statistics, Springer, vol. 39(5), pages 2413-2436, July.
    4. Angeliki Papana & Catherine Kyrtsou & Dimitris Kugiumtzis & Cees Diks, 2023. "Identification of causal relationships in non-stationary time series with an information measure: Evidence for simulated and financial data," Empirical Economics, Springer, vol. 64(3), pages 1399-1420, March.
    5. Marc Hallin & Davide La Vecchia, 2014. "Semiparametrically Efficient R-Estimation for Dynamic Location-Scale Models," Working Papers ECARES ECARES 2014-45, ULB -- Universite Libre de Bruxelles.
    6. Kim, Seonjin & Zhao, Zhibiao, 2014. "Specification test for Markov models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 118-133.

Articles

  1. Seonjin Kim & Zhibiao Zhao, 2013. "Unified inference for sparse and dense longitudinal models," Biometrika, Biometrika Trust, vol. 100(1), pages 203-212.

    Cited by:

    1. Cui, Xia & Zhao, Weihua & Lian, Heng & Liang, Hua, 2019. "Pursuit of dynamic structure in quantile additive models with longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 42-60.
    2. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
    3. Cho, Hyunkeun & Kim, Seonjin, 2017. "Model specification test in a semiparametric regression model for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 160(C), pages 105-116.
    4. Jia Chen & Degui Li & Hua Liang & Suojin Wang, 2014. "Semiparametric GEE Analysis in Partially Linear Single-Index Models for Longitudinal Data," Discussion Papers 14/26, Department of Economics, University of York.
    5. Qian Huang & Jinhong You & Liwen Zhang, 2022. "Efficient inference of longitudinal/functional data models with time‐varying additive structure," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 744-771, June.
    6. Yixin Chen & Weixin Yao, 2017. "Unified Inference for Sparse and Dense Longitudinal Data in Time-varying Coefficient Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 268-284, March.

  2. Zhao, Zhibiao, 2011. "Nonparametric model validations for hidden Markov models with applications in financial econometrics," Journal of Econometrics, Elsevier, vol. 162(2), pages 225-239, June.

    Cited by:

    1. Xun Huang & Huiyue Tang, 2022. "Measuring multi‐volatility states of financial markets based on multifractal clustering model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 422-434, April.
    2. Hui, Yongchang & Wong, Wing-Keung & BAI, ZHIDONG & Zhu, Zhen-Zhen, 2017. "A New Nonlinearity Test to Circumvent the Limitation of Volterra Expansion with Application," MPRA Paper 79692, University Library of Munich, Germany.
    3. Kim, Seonjin & Zhao, Zhibiao, 2014. "Specification test for Markov models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 118-133.
    4. Cui, Yan & Yang, Jun & Zhou, Zhou, 2023. "State-domain change point detection for nonlinear time series regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 3-27.

  3. Zhao, Zhibiao, 2010. "Density estimation for nonlinear parametric models with conditional heteroscedasticity," Journal of Econometrics, Elsevier, vol. 155(1), pages 71-82, March.

    Cited by:

    1. Zhao, Zhibiao, 2011. "Nonparametric model validations for hidden Markov models with applications in financial econometrics," Journal of Econometrics, Elsevier, vol. 162(2), pages 225-239, June.
    2. Yin Liao & John Stachurski, 2011. "Parametric Conditional Monte Carlo Density Estimation," ANU Working Papers in Economics and Econometrics 2011-562, Australian National University, College of Business and Economics, School of Economics.
    3. Li, Shuo & Tu, Yundong, 2016. "n-consistent density estimation in semiparametric regression models," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 91-109.
    4. Wang, Chuan-Sheng & Zhao, Zhibiao, 2016. "Conditional Value-at-Risk: Semiparametric estimation and inference," Journal of Econometrics, Elsevier, vol. 195(1), pages 86-103.

  4. Zhao, Zhibiao & Wu, Wei Biao, 2009. "Nonparametric inference of discretely sampled stable Lévy processes," Journal of Econometrics, Elsevier, vol. 153(1), pages 83-92, November.

    Cited by:

    1. Cui, Zhenyu & Kirkby, J. Lars & Nguyen, Duy, 2021. "A data-driven framework for consistent financial valuation and risk measurement," European Journal of Operational Research, Elsevier, vol. 289(1), pages 381-398.
    2. Stefan Birr & Stanislav Volgushev & Tobias Kley & Holger Dette & Marc Hallin, 2017. "Quantile spectral analysis for locally stationary time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1619-1643, November.
    3. Hounyo, Ulrich & Varneskov, Rasmus T., 2017. "A local stable bootstrap for power variations of pure-jump semimartingales and activity index estimation," Journal of Econometrics, Elsevier, vol. 198(1), pages 10-28.
    4. Jing, Bing-Yi & Kong, Xin-Bing & Liu, Zhi & Mykland, Per, 2012. "On the jump activity index for semimartingales," Journal of Econometrics, Elsevier, vol. 166(2), pages 213-223.
    5. Adam D. Bull, 2014. "Near-optimal estimation of jump activity in semimartingales," Papers 1409.8150, arXiv.org, revised Jan 2016.
    6. Fabian Mies & Ansgar Steland, 2019. "Nonparametric Gaussian inference for stable processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 525-555, October.
    7. Fabienne Comte & Céline Duval & Valentine Genon-Catalot, 2014. "Nonparametric density estimation in compound Poisson processes using convolution power estimators," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(1), pages 163-183, January.

  5. Zhao, Zhibiao & Wu, Wei Biao, 2007. "Asymptotic theory for curve-crossing analysis," Stochastic Processes and their Applications, Elsevier, vol. 117(7), pages 862-877, July.

    Cited by:

    1. Vitali Alexeev & Alex Maynard, 2010. "Localized Level Crossing Random Walk Test Robust to the Presence of Structural Breaks," Working Papers 1001, University of Guelph, Department of Economics and Finance.

  6. Wei Biao Wu & Zhibiao Zhao, 2007. "Inference of trends in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(3), pages 391-410, June.

    Cited by:

    1. Zhao, Zhibiao & Wu, Wei Biao, 2009. "Nonparametric inference of discretely sampled stable Lévy processes," Journal of Econometrics, Elsevier, vol. 153(1), pages 83-92, November.
    2. Jiaqi Li & Likai Chen & Kun Ho Kim & Tianwei Zhou, 2022. "Simultaneous Inference of a Partially Linear Model in Time Series," Papers 2212.10359, arXiv.org, revised Sep 2023.
    3. Pedro Carneiro & Tewolde Ghebremeskel & Joseph Keating & Andrea Locatelli, 2012. "Do public health interventions crowd out private health investments? Malaria control policies in Eritrea," CeMMAP working papers CWP12/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Alessandro Casini & Pierre Perron, 2021. "Change-Point Analysis of Time Series with Evolutionary Spectra," Papers 2106.02031, arXiv.org, revised Aug 2024.
    5. Ngai Hang Chan & Linhao Gao & Wilfredo Palma, 2022. "Simultaneous variable selection and structural identification for time‐varying coefficient models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 511-531, July.
    6. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    7. Yujiao Yang & Qiongxia Song, 2014. "Jump detection in time series nonparametric regression models: a polynomial spline approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 325-344, April.
    8. Marina Friedrich & Eric Beutner & Hanno Reuvers & Stephan Smeekes & Jean-Pierre Urbain & Whitney Bader & Bruno Franco & Bernard Lejeune & Emmanuel Mahieu, 2020. "A statistical analysis of time trends in atmospheric ethane," Climatic Change, Springer, vol. 162(1), pages 105-125, September.
    9. Barbara Rossi & Raffaella Giacomini, 2010. "Model Comparisons in Unstable Environments," Working Papers 10-29, Duke University, Department of Economics.
    10. Li Cai & Lisha Li & Simin Huang & Liang Ma & Lijian Yang, 2020. "Oracally efficient estimation for dense functional data with holiday effects," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 282-306, March.
    11. Anderson Ara & Francisco Louzada & Carlos A. R. Diniz, 2017. "Statistical monitoring of a web server for error rates: a bivariate time-series copula-based modeling approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2287-2300, October.
    12. Jan Mielniczuk & Zhou Zhou & Wei Biao Wu, 2009. "On nonparametric prediction of linear processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 652-673, November.
    13. Raffaella Giacomini & Barbara Rossi, 2012. "Model comparisons in unstable environments," CeMMAP working papers 13/12, Institute for Fiscal Studies.
    14. Zhibiao Zhao, 2015. "Inference for Local Autocorrelations in Locally Stationary Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 296-306, April.
    15. Zheng, Shuzhuan & Yang, Lijian & Härdle, Wolfgang Karl, 2010. "A confidence corridor for sparse longitudinal data curves," SFB 649 Discussion Papers 2011-002, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Zifeng Zhao & Feiyu Jiang & Xiaofeng Shao, 2022. "Segmenting time series via self‐normalisation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1699-1725, November.
    17. Kim, Kun Ho & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function," IRTG 1792 Discussion Papers 2020-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
    19. Israel Martínez‐Hernández & Marc G. Genton, 2021. "Nonparametric trend estimation in functional time series with application to annual mortality rates," Biometrics, The International Biometric Society, vol. 77(3), pages 866-878, September.
    20. Friedrich, Marina & Smeekes, Stephan & Urbain, Jean-Pierre, 2020. "Autoregressive wild bootstrap inference for nonparametric trends," Journal of Econometrics, Elsevier, vol. 214(1), pages 81-109.
    21. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    22. Li Cai & Suojin Wang, 2021. "Global statistical inference for the difference between two regression mean curves with covariates possibly partially missing," Statistical Papers, Springer, vol. 62(6), pages 2573-2602, December.
    23. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2019. "Inference of Break-Points in High-Dimensional Time Series," IRTG 1792 Discussion Papers 2019-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    24. Zhibiao Zhao & Yiyun Zhang & Runze Li, 2014. "Non-Parametric Estimation Under Strong Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 4-15, January.
    25. Holger Dette & Theresa Eckle & Mathias Vetter, 2020. "Multiscale change point detection for dependent data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1243-1274, December.
    26. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.
    27. Yuanyuan Zhang & Lijian Yang, 2018. "A smooth simultaneous confidence band for correlation curve," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 247-269, June.
    28. Luis A. Gil-Alana, 2009. "Warming break trends and fractional integration in the northern, southern and global temperature anomaly series," Faculty Working Papers 09/09, School of Economics and Business Administration, University of Navarra.
    29. Shuzhuan Zheng & Rong Liu & Lijian Yang & Wolfgang K. Härdle, 2016. "Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 607-626, December.
    30. Zhang, Rongmao & Chan, Ngai Hang & Chi, Changxiong, 2023. "Nonparametric testing for the specification of spatial trend functions," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    31. Bibinger, Markus & Madensoy, Mehmet, 2019. "Change-point inference on volatility in noisy Itô semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 129(12), pages 4878-4925.
    32. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
    33. Jabin J. Deguma & Emerson D. Peteros & Reylan G. Capuno & Ricardo Q. Ybañez & Danilo F. Cebe & Helen O. Revalde & Regina E. Sitoy & Melona C. Deguma, 2021. "Analyzing Heart Disease Mortality of Filipino: From Statistical Modeling to Health and Lifestyle Education Implications," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 10, July.
    34. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    35. Jialiang Li & Yaguang Li & Tailen Hsing, 2022. "On functional processes with multiple discontinuities," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 933-972, July.
    36. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
    37. Bibinger, Markus & Jirak, Moritz & Vetter, Mathias, 2015. "Nonparametric change-point analysis of volatility," SFB 649 Discussion Papers 2015-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    38. Zhao, Wenbiao & Zhu, Lixing, 2024. "Detecting change structures of nonparametric regressions," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
    39. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    40. Erhua Zhang & Xiaojun Song & Jilin Wu, 2022. "A non‐parametric test for multi‐variate trend functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 856-871, November.
    41. Zheng, Shuzhuan & Liu, Rong & Yang, Lijian & Härdle, Wolfgang Karl, 2014. "Simultaneous confidence corridors and variable selection for generalized additive models," SFB 649 Discussion Papers 2014-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    42. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Papers 2303.10117, arXiv.org, revised Mar 2024.
    43. Degras, David, 2008. "Asymptotics for the nonparametric estimation of the mean function of a random process," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2976-2980, December.
    44. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

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