Publications

1. Change point inference in high-dimensional regression models under temporal dependence.
   Haotian Xu, Daren Wang, Zifeng Zhao, and Yi Yu.
   Annals of Statistics, 52.3 (2024): 999-1026. DOI

2. Change point detection and inference in multivariate nonparametric models under mixing conditions.
   Carlos Misael Madrid Padilla, Haotian Xu, Daren Wang, Oscar Hernan Madrid Padilla, and Yi Yu.
   NeurIPS (2023). arXiv

3. Localising change points in piecewise polynomials of general degrees.
   Yi Yu, Sabyasachi Chatterjee, and Haotian Xu.
   Electronic Journal of Statistics, 16.1 (2022): 1855–1890. DOI

4. Robust two-step wavelet-based inference for time series models.
   Stéphane Guerrier, Roberto Molinari, Maria-Pia Victoria-Feser, and Haotian Xu.
   Journal of the American Statistical Association (Theory & Methods), 117.540 (2022): 1996-2013. DOI

5. Wavelet-based moment-matching techniques for inertial sensor calibration.
   Stéphane Guerrier, Juan Jurado, Mehran Khaghani, Gaetan Bakalli, Mucyo Karemera, Roberto Molinari, Samuel Orso, John Raquet, Christine Schubert Kabban, Jan Skaloud, Haotian Xu, and Yuming Zhang.
   IEEE Transactions on Instrumentation and Measurement, 69.10 (2020): 7542-7551. DOI

6. Multivariate signal modeling with applications to inertial sensor calibration.
   Haotian Xu, Stéphane Guerrier, Roberto Molinari, and Mucyo Karemera.
   IEEE Transactions on Signal Processing, 67.19 (2019): 5143-5152. DOI

7. Is nonmetastatic cutaneous melanoma predictable through genomic biomarkers?
   Mattia Branca, Samuel Orso, Roberto Molinari, Haotian Xu, Stéphane Guerrier, Yuming Zhang, and Nabil Mili.
   Melanoma Research, 28.1 (2018): 21-29. DOI

8. An optimalvirtual inertial sensor framework using wavelet cross covariance.
   Yuming Zhang, Haotian Xu, Ahmed Radi, Roberto Molinari, Stéphane Guerrier, Mucyo Karemera, and Naser El-Sheimy.
   In 2018 IEEE/ION Position, Locationand Navigation Symposium (PLANS) (pp. 1342-1350). DOI

9. A study of the Allan variance for constant-mean nonstationary processes.
   Haotian Xu, Stéphane Guerrier, Roberto Molinari, and Yuming Zhang.
   IEEE Signal Processing Letters, 24.8 (2017): 1257-1260. DOI

Preprints

1. Nonparametric estimation of intensity functions in spatial point processes using a higher-order tensor approach.
   Haotian Xu, Carlos Misael Madrid Padilla, Oscar Hernan Madrid Padilla, and Daren Wang.
   (preparing for submission).

2. Multiple change points detection problems for high-dimensional time series.
   Di Xiao, Haotian Xu, Jeongyoun Ahn, Stéphane Guerrier, Runze Li, and Yuan Ke.
   (preparing for submission).

3. Inference for large scale regression models with dependent errors.
   Lionel Voirol, Haotian Xu, Yuming Zhang, Luca Insolia, Roberto Molinari, and Stéphane Guerrier.
   (preparing for submission). arXiv

4. Change point localisation and inference in fragmented functional data.
   Gengyu Xue, Haotian Xu, and Yi Yu.
   (submitted). arXiv

5. Estimation and inference for change points in functional regression time series.
   Shivam Kumar, Haotian Xu, Haeran Cho, and Daren Wang.
   (submitted). arXiv

6. Online network change point detection with missing values and temporal dependence.
   Haotian Xu, Paromita Dubey, and Yi Yu.
   (Submitted). arXiv

7. Nonasymptotic theories for tail-robust autocovariance matrix estimation methods.
   Haotian Xu, Stéphane Guerrier, Runze Li, and Yuan Ke.
   (Submitted).

Softwares

1. changepoints, an R package containing several methods for change point localization.

2. FragmentCP, an R package performing change point localisation and inference in fragmented functional data.

3. avar, an R package implementing the allan variance and allan variance linear regression estimator for time series models.

Ebook

Applied time series analysis with R.
Stéphane Guerrier, Roberto Molinari, Haotian Xu, and Yuming Zhang.
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