Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Shuva Gupta"'
Publikováno v:
Frontiers in Genetics, Vol 10 (2019)
Quantitative high throughput screening (qHTS) experiments can generate 1000s of concentration-response profiles to screen compounds for potentially adverse effects. However, potency estimates for a single compound can vary considerably in study desig
Externí odkaz:
https://doaj.org/article/1a2b0502db7248b890af375cee7743bb
Publikováno v:
Frontiers in Genetics, Vol 10 (2019)
Frontiers in Genetics
Frontiers in Genetics
Quantitative high throughput screening (qHTS) experiments can generate 1000s of concentration-response profiles to screen compounds for potentially adverse effects. However, potency estimates for a single compound can vary considerably in study desig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::457488faea52e9d51cb60f1606a113d5
https://www.frontiersin.org/article/10.3389/fgene.2019.00387/full
https://www.frontiersin.org/article/10.3389/fgene.2019.00387/full
Publikováno v:
Computational Statistics & Data Analysis. 77:223-232
Identification of active factors in supersaturated designs (SSDs) has been the subject of much recent study. Although several methods have been previously proposed, a solution to the problem beyond one or two active factors still seems to be unsatisf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8e45b0eebfeebe123147c009c7d997c
https://doi.org/10.1016/j.csda.2014.02.023
https://doi.org/10.1016/j.csda.2014.02.023
Autor:
Shuva Gupta
Publikováno v:
Sankhya A. 74:10-28
The asymptotic distribution of the Lasso estimator for regression models with independent errors has been investigated by Knight and Fu (2000). In this note we extend these results to regression models with a general weak dependence structure. We det
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57899ffd4e1a28f14852f1e19b9149b7
https://doi.org/10.1007/s13171-012-0006-8
https://doi.org/10.1007/s13171-012-0006-8
Autor:
Shuva Gupta, S. N. Lahiri
Publikováno v:
Journal of the American Statistical Association. 109:1013-1015
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0db20f776bf99361a4281ab7f656d86
https://doi.org/10.1080/01621459.2014.905789
https://doi.org/10.1080/01621459.2014.905789
Autor:
Shockley, Keith R., Gupta, Shuva, Harris, Shawn F., Lahiri, Soumendra N., Peddada, Shyamal D.
Publikováno v:
Frontiers in Genetics; 5/9/2019, pN.PAG-N.PAG, 12p
Autor:
Gupta, Shuva, Lahiri, S. N.
Publikováno v:
Journal of the American Statistical Association; Sep2014, Vol. 109 Issue 507, p1013-1015, 3p
Publikováno v:
American Statistician; Nov2012, Vol. 66 Issue 4, p246-247, 2p
Autor:
Mohsen Pourahmadi
Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health ca
