Jianfeng YAO

Associate Professor

Statistics

- D. Passemier, Zh. Li and J. Yao, 2014.
On estimation of the noise variance in high-dimensional
probabilistic principal component analysis,
*Submitted.* - Q. Wang and J. Yao, 2014.
Joint CLT for several random sesquilinear forms with
applications to large-dimensional spiked population models.
*Submitted.* - Z. Li, G. Pan and J. Yao, 2014.
On singular value distribution of large-dimensional
autocovariance matrices.
*Submitted.* - Zh. Li and J. Yao, 2014.
New procedure for high-dimensional
classification of general populations.
*Submitted.* - S. Zheng, Z. D. Bai and J. Yao, 2014.
Substitution principle for CLT of linear spectral
statistics of high-dimensional sample covariance
matrices with applications to hypothesis testing.
*Submitted.* - S. Zheng, Z. D. Bai and J. Yao, 2013.
CLT for linear spectral statistics of large
dimensional general Fisher matrices.
*Submitted.* - S. Zheng, Z. D. Bai and J. Yao, 2013.
CLT for linear spectral statistics of random matrix $S^{-1}T$.
*Submitted.*

- H. K. Yalamanchili, Zh. Li, P. Wang,
M. P. Wong,
J. Yao and J. Wang, 2014.
SpliceNet: recovering splicing isoform-specific
differential gene networks from RNA-Seq data of
normal and diseased samples.
*Nucleic Acids Research,*doi: 10.1093/nar/gku577 - Q. Wang, J. Silverstein and J. Yao, 2014.
A note on the CLT of the LSS for sample covariance
matrix from a
spiked population model
*J. Multivariate Analysis***130**, 194-207 -
W.M. Li and J. Yao, 2014.
On generalized expectation based
estimation of a population
spectral distribution from high-dimensional data
In Press:
*Annals of the Institute of Statistical Mathematics.* -
C. Wang, H. Liu, J. Yao, R. Davis and W. K. Li, 2014.
Self-excited Threshold Poisson Autoregression
*J. Amer. Statist. Assoc.***109**(506, June 2014), 777-787 -
W.M. Li and J. Yao, 2014.
A local moments estimation of the spectrum of a
large dimensional covariance matrix.
*Statistica Sinica***24**(2, April), 919-936 - N. Raillard, P. Ailliot and J. Yao, 2014.
Modeling extreme values of processes observed at
irregular time steps: application to significant wave
height
*Annals of Applied Statistics***8**(1), 622–647 - D. Passemier and J. Yao, 2014.
On the detection of the number of spikes,
possibly equal, in the high-dimensional case.
*J. Multivariate Analysis***127**, 173-183 -
Q. Wang and J. Yao, 2013.
On the sphericity test with large-dimensional
observations.
*Electronic J. Statistics***7**,2164-2192. -
T. Crivelli, B. Cernuschi-Frias, P. Bouthemy and J. Yao, 2013.
Motion textures: modeling, classification and
segmentation using mixed-state Markov random
fields.
*SIAM Journal on Imaging Sciences***6**(4), 2484–2520. - W.M. Li, J.Q. Chen, Y.L. Qin, J. Yao
and Z.D. Bai, 2013.
Estimation of the population spectral distribution from
a large dimensional sample covariance
matrix.
*J. Statistical Planning and Inference***143**(11, November), 1887–1897 -
Z. D. Bai, D. Jiang, J. Yao and S. Zheng, 2013.
Testing linear hypotheses
in high-dimensional regressions.
*Statistics***47**(6), 1207-1223 On-line First (2012) - D. Passemier and J-F. Yao, 2012.
On determining the number of spikes in a
high-dimensional spiked population model.
*Random Matrix: Theory and Applciations***1**, 1150002 - Z. D. Bai and J. Yao, 2012.
On sample eigenvalues in a generalized
spiked population model.
*J. Multivariate Analysis***106**, 167–177. - J-F. Yao, 2012.
A note on a Marcenko-Pastur type theorem
for time series.
*Statist. and Probab. Letters***82**, 20-28. - L. Truquet and J. Yao, 2012.
On the quasi-likelihood
estimation for random coefficient autoregressions.
*Statistics***46**(4), 505-521. -
J. Chen, B. Delyon and J. Yao, 2011.
On a model selection problem from
high-dimensional sample covariance matrices.
*J. Multivariate Analysis***102**, 1388–1398 - T. Crivelli, · P. Bouthemy, · B. Cernuschi-Frias and J. Yao, 2011.
Simultaneous motion detection and background
reconstruction with a conditional mixed-state Markov
random field.
*Int. J. Computer Vision***94**, 295–316 - T. Crivelli, · P. Bouthemy, · B. Cernuschi-Frias and J. Yao, 2010.
Mixed-state causal modeling for statistical KL-based motion
texture tracking.
*Pattern Recognition Letters***31 (14)**, 2286-2294 - Z.D. Bai, J. Chen and J. Yao, 2010.
On estimation of the population spectral
distribution from a high-dimensional sample
covariance matrix.
*Australian & New Zeland Journal of Statistics***52**, 423-437 -
M. Kachour and J. Yao, 2009.
First-order rounded integer-valued
autoregressive (RINAR(1)) process.
*J. Time Series Analysis***30 (4)**, 417-448 - Z. D. Bai, D. Jiang, J. Yao and S. Zheng, 2009.
Corrections to LRT on Large Dimensional Covariance Matrix by RMT.
*Ann. Statistics***37**(6B), 3822–3840 - C. Hardouin and J. Yao, 2008.
Spatial modelling for mixed-state observations
*Electronic J. Statistics***2**, 213-233 - C. Hardouin and J. Yao, 2008.
Multi-parameter auto-models and their applications.
*Biometrika***95**, 335-349 - Z. D. Bai and J. Yao, 2008.
Central limit theorems for eigenvalues in a spiked population model.
*Annales Inst. Henri Poincaré***44**(3), 447-474

- B. Belmudez, V. Prinet, J. Yao, P. Bouthemy and X. Descombes, 2009. Conditional mixed-state model for structural change analysis from very high resolution optical images. International Geoscience and Remote Sensing Symposium (IGARSS) Volume 2, 2009, Pages II988-II991
- Th. Crivelli, P. Bouthemy, B. Cernuschi-Frias,
and J. Yao, 2009.
Learning
mixed-state Markov models for statistical motion texture
tracking.
In
*Proc. ICCV'09, Int. Workshop on Machine Learning for Vision-based Motion Analysis (MLVMA'09)*, Kyoto, Japan, October 2009. - Th. Crivelli, G. Piriou, B. Cernuschi-Frias,
P. Bouthemy, J. Yao, 2008.
Simultaneous motion detection and background
reconstruction with a mixed-state conditional Markov
random field.
In
*Proc. Eur. Conf. Computer Vision (ECCV'08)*, Volume 1, Pages 113-126, Marseille, France, October 2008. - Th. Crivelli, B. Cernuschi-Frias, P. Bouthemy,
J. Yao, 2008.
Temporal
modeling of motion textures with mixed-states Markov chains.
In
*Proc. Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP'08)*, Pages 881-884, Las Vegas, USA, April 2008. - Th. Crivelli, B. Cernuschi-Frias, P. Bouthemy,
J. Yao, 2008..
Recognition
of dynamic video contents based on motion texture
statistical models.
In
*Proc. Int. Conf. on Computer Vision Theory and Applications (VISAPP'08)*, Volume 1, Pages 283-289, Funchal, Portugal, January 2008. - J. Yao and D. Passemier, 2014
On estimation of the noise variance in a high-dimensional signal
detection model.
In
*Proc. 2014 IEEE Workshop on Statistical Signal Processing (SSP)*, Pages 17-20, Gold Coast, Australia, July 2014.