Package: SIHR 2.1.0

Zijian Guo

SIHR: Statistical Inference in High Dimensional Regression

The goal of SIHR is to provide inference procedures in the high-dimensional generalized linear regression setting for: (1) linear functionals <doi:10.48550/arXiv.1904.12891> <doi:10.48550/arXiv.2012.07133>, (2) conditional average treatment effects, (3) quadratic functionals <doi:10.48550/arXiv.1909.01503>, (4) inner product, (5) distance.

Authors:Zhenyu Wang [aut], Prabrisha Rakshit [aut], Tony Cai [aut], Zijian Guo [aut, cre]

# Install 'SIHR' in R:

install.packages('SIHR', repos = c('https://zywang0701.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Last updated 7 months agofrom:f7e6b78586. Checks:OK: 7. Indexed: yes.

Last update: 2024-04-11
Started: 2024-04-11

Last update: 2024-04-11
Started: 2024-04-11

Last update: 2024-04-12
Started: 2024-04-11

Help page	Topics
Inference for difference of linear combinations of the regression vectors in high dimensional generalized linear regressions	CATE
Inference for weighted quadratic functional of difference of the regression vectors (excluding the intercept term) in high dimensional generalized linear regressions.	Dist
Inference for weighted inner product of the regression vectors in high dimensional generalized linear regressions	InnProd
Inference for linear combination of the regression vector in high dimensional generalized linear regression	LF
Inference for quadratic forms of the regression vector in high dimensional generalized linear regressions	QF