Statistical Inference in High Dimensional Regression
Inference procedures in the high-dimensional setting for (1) linear functionals and quadratic functionals in linear regression ('Cai et al.' (2019) <arXiv:1904.12891>, 'Guo et al.' (2019) <arXiv:1909.01503>), (2) linear functional in logistic regression ('Guo et al.' <arXiv:2012.07133>), (3) individual treatment effects in linear and logistic regression.
CVXR, Matrix, glmnet, Rdpack, scalreg, qpdf
c(person("Prabrisha Rakshit", role = c("aut", "cre"), email = "prabrisha.rakshit@rutgers.edu"),person("Tony Cai", role = "aut", email = "tcai@wharton.upenn.edu"),person("Zijian Guo", role = "aut", email = "zijguo@stat.rutgers.edu"))
2021-06-11 17:48:54 UTC; PRABRISHA RAKSHIT
Prabrisha Rakshit [aut, cre],
Tony Cai [aut],
Zijian Guo [aut]

Inference procedures in the high-dimensional setting for (1) linear functionals and quadratic functionals in linear regression ('Cai et al.' (2019) <arXiv:1904.12891>, 'Guo et al.' (2019) <arXiv:1909.01503>), (2) linear functional in logistic regression ('Guo et al.' <arXiv:2012.07133>), (3) individual treatment effects in linear and logistic regression, (4) single regression coefficient in binary outcome regression.
2021-10-05 02:02:03 UTC; PRABRISHA RAKSHIT

Prabrisha Rakshit, Zhenyu Wang, Tony Cai, Zijian Guo
Inference procedures in the high-dimensional setting for
(1) linear functionals in generalized linear regression ('Cai et al.' (2019) <arXiv:1904.12891>, 'Guo et al.' (2020) <arXiv:2012.07133>, 'Cai et al.' (2021)),
(2) individual treatment effects in generalized linear regression,
(3) quadratic functionals in linear regression ('Guo et al.' (2019) <arXiv:1909.01503>).

Prabrisha Rakshit, Zhenyu Wang, Zijian Guo, Tony Cai

Inference procedures in the high-dimensional setting for
(1) linear functionals in generalized linear regression ('Cai et al.' (2019) <arXiv:1904.12891>, 'Guo et al.' (2020) <arXiv:2012.07133>, 'Cai et al.' (2021)),
(2) individual treatment effects in generalized linear regression,
(3) quadratic functionals in generalized linear regression ('Guo et al.' (2019) <arXiv:1909.01503>).