BSciCoverfun: Compute CI for bootstrap-calibrated methods
In WaverlyWei/subDebiased: Sharp Inference on Selected Subgroup in Observational Studies
BSciCoverfun R Documentation
Compute CI for bootstrap-calibrated methods
Description
Compute CI for bootstrap-calibrated methods
Usage
BSciCoverfun(beta, TB = NULL, G = NULL, alpha = 0.95)
Arguments
beta
estimated betas
TB
recalibrated bootstrap statistics
G
indices of subgroups
alpha
confidence level
Value
LowerBound
Lower confidence bound
UpperBound
Upper confidence bound
betaMax
debiased maximum beta estimate
WaverlyWei/subDebiased documentation built on June 30, 2022, 10:50 a.m.
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| BSciCoverfun | R Documentation |
Compute CI for bootstrap-calibrated methods
Description
Compute CI for bootstrap-calibrated methods
Usage
BSciCoverfun(beta, TB = NULL, G = NULL, alpha = 0.95)
Arguments
beta |
estimated betas |
TB |
recalibrated bootstrap statistics |
G |
indices of subgroups |
alpha |
confidence level |
Value
LowerBound |
Lower confidence bound |
UpperBound |
Upper confidence bound |
betaMax |
debiased maximum beta estimate |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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