3 citations · 7 across the 5 of their papers we have counts for
4 papers · 1 filter
Inference on the Change Point for High Dimensional Dynamic Graphical Models
Abhishek Kaul, Hongjin Zhang, Konstantinos Tsampourakis +1
We develop an estimator for the change point parameter for a dynamically evolving graphical model, and also obtain its asymptotic distribution under high dimensional scaling. To pr…
Inference on the change point with the jump size near the boundary of the region of detectability in high dimensional time series models
Abhishek Kaul, Venkata K Jandhyala, Stergios B Fotopoulos
We develop a projected least squares estimator for the change point parameter in a high dimensional time series model with a potential change point. Importantly we work under the s…
Detection and estimation of parameters in high dimensional multiple change point regression models via regularization and discrete optimization
Abhishek Kaul, Venkata K Jandhyala, Stergios B Fotopoulos
Binary segmentation, which is sequential in nature is thus far the most widely used method for identifying multiple change points in statistical models. Here we propose a top down…
Confidence Bands for Coefficients in High Dimensional Linear Models with Error-in-variables
Alexandre Belloni, Victor Chernozhukov, Abhishek Kaul
We study high-dimensional linear models with error-in-variables. Such models are motivated by various applications in econometrics, finance and genetics. These models are challengi…