Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Haihan Tang"'
Autor:
Oliver B. Linton, Haihan Tang
Publikováno v:
Journal of the American Statistical Association. 117:117-117
Publikováno v:
2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC).
In this study, shaking noise existing in defect detection of steel wire ropes are discussed based on magnetic flux leakage signals while using a multi-channel Hall sensor array. The causes and features of shaking noise are also studied according to t
Autor:
Anders Bredahl Kock, Haihan Tang
Publikováno v:
Kock, A B & Tang, H 2019, ' Uniform inference in highdimensional dynamic panel data models with approximately sparse fixed effects ', Econometric Theory, vol. 35, no. 2, pp. 295-359 . https://doi.org/10.1017/S0266466618000087
We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived
Autor:
Haihan Tang, Oliver Linton
We propose a new estimator, the quadratic form estimator, of the Kronecker product model for covariance matrices. We show that this estimator has good properties in the large dimensional case (i.e., the cross-sectional dimension n is large relative t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7c231d4f2a7a8e0d1ca8bc1ebe5ec9b
http://arxiv.org/abs/1906.08908
http://arxiv.org/abs/1906.08908
We propose a Kronecker product model for correlation or covariance matrices in the large dimensional case. The number of parameters of the model increases logarithmically with the dimension of the matrix. We propose a minimum distance (MD) estimator
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5132faf61f7f80f5a721da97162f161b
https://doi.org/10.1920/wp.cem.2016.5216
https://doi.org/10.1920/wp.cem.2016.5216
We consider a Kronecker product structure for large covariance matrices, which has the feature that the number of free parameters increases logarithmically with the dimensions of the matrix. We propose an estimation method of the free parameters base
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a10080d5ec3c5093b543dc5f9d2abdc6
https://doi.org/10.1920/wp.cem.2016.2316
https://doi.org/10.1920/wp.cem.2016.2316
Publikováno v:
SSRN Electronic Journal.
We consider a Kronecker product structure for large covariance matrices, which has the feature that the number of free parameters increases logarithmically with the dimensions of the matrix. We propose an estimation method of the free parameters base