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pro vyhledávání: '"Bhattacharyya, Sharmodeep"'
The central problem we address in this work is estimation of the parameter support set S, the set of indices corresponding to nonzero parameters, in the context of a sparse parametric likelihood model for count-valued multivariate time series. We dev
Externí odkaz:
http://arxiv.org/abs/2307.09684
Autor:
Chatterjee, Sayak, Chatterjee, Shirshendu, Mukherjee, Soumendu Sundar, Nath, Anirban, Bhattacharyya, Sharmodeep
Network-valued time series are currently a common form of network data. However, the study of the aggregate behavior of network sequences generated from network-valued stochastic processes is relatively rare. Most of the existing research focuses on
Externí odkaz:
http://arxiv.org/abs/2208.01365
Sparse regression is frequently employed in diverse scientific settings as a feature selection method. A pervasive aspect of scientific data that hampers both feature selection and estimation is the presence of strong correlations between predictive
Externí odkaz:
http://arxiv.org/abs/2103.12802
We investigate the treatment effect of the juvenile stay-at-home order (JSAHO) adopted in Saline County, Arkansas, from April 6 to May 7, in mitigating the growth of SARS-CoV-2 infection rates. To estimate the counterfactual control outcome for Salin
Externí odkaz:
http://arxiv.org/abs/2009.08691
We consider the offline change point detection and localization problem in the context of piecewise stationary networks, where the observable is a finite sequence of networks. We develop algorithms involving some suitably modified CUSUM statistics ba
Externí odkaz:
http://arxiv.org/abs/2009.02112
Multilayer and multiplex networks are becoming common network data sets in recent times. We consider the problem of identifying the common community structure for a special type of multilayer networks called multi-relational networks. We consider ext
Externí odkaz:
http://arxiv.org/abs/2004.03480
Akademický článek
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Vector autoregressive (VAR) models are widely used for causal discovery and forecasting in multivariate time series analyses in fields as diverse as neuroscience, environmental science, and econometrics. In the high-dimensional setting, model paramet
Externí odkaz:
http://arxiv.org/abs/1908.11464
Akademický článek
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Autor:
Li, Tianxi, Lei, Lihua, Bhattacharyya, Sharmodeep, Berge, Koen Van den, Sarkar, Purnamrita, Bickel, Peter J., Levina, Elizaveta
The problem of community detection in networks is usually formulated as finding a single partition of the network into some "correct" number of communities. We argue that it is more interpretable and in some regimes more accurate to construct a hiera
Externí odkaz:
http://arxiv.org/abs/1810.01509