High-dimensional inference for linear model with correlated errors

Metrika ◽  
2021 ◽  
Author(s):  
Panxu Yuan ◽  
Xiao Guo
Statistics ◽  
2019 ◽  
Vol 54 (1) ◽  
pp. 152-166
Author(s):  
Konrad Furmańczyk ◽  
Wojciech Rejchel

2019 ◽  
Vol 65 (10) ◽  
pp. 6539-6560 ◽  
Author(s):  
Tamir Hazan ◽  
Francesco Orabona ◽  
Anand D. Sarwate ◽  
Subhransu Maji ◽  
Tommi S. Jaakkola

2019 ◽  
Vol 09 (04) ◽  
pp. 2050017
Author(s):  
Zhiqiang Jiang ◽  
Zhensheng Huang ◽  
Guoliang Fan

This paper considers empirical likelihood inference for a high-dimensional partially functional linear model. An empirical log-likelihood ratio statistic is constructed for the regression coefficients of non-functional predictors and proved to be asymptotically normally distributed under some regularity conditions. Moreover, maximum empirical likelihood estimators of the regression coefficients of non-functional predictors are proposed and their asymptotic properties are obtained. Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real data set is analyzed for illustration.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Stefano Sarao Mannelli ◽  
Giulio Biroli ◽  
Chiara Cammarota ◽  
Florent Krzakala ◽  
Pierfrancesco Urbani ◽  
...  

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