R: Two-Directional Simultaneous Inference for High-Dimensional Models

# Two-Directional Simultaneous Inference for High-Dimensional Models

## Documentation for package ‘TOSI’ version 0.3.0

- DESCRIPTION file
- Package README

## Help Pages

assessBsFun | Assess the performance of group-sparse loading estimate
bic.spfac | Modified BIC criteria for selecting penalty parameters
ccorFun | Evaluate the smallest canonical correlation for two set of variables
cv.spfac | Cross validation for selecting penalty parameters
FacRowMaxST | Data splitting-based two-stage maximum testing method for a group of loading vectors in factor models.
FacRowMinST | Data splitting-based two-stage minimum testing method for a group of loading vectors in factor models.
Factorm | Factor Analysis Model
gendata_Fac | Generate simulated data
gendata_Mean | Generate simulated data
gendata_Reg | Generate simulated data
gsspFactorm | High Dimensional Sparse Factor Model
MeanMax | Data splitting-based two-stage maximum mean testing method for the mean vector.
MeanMin | Data splitting-based two-stage minimum mean testing method for the mean vector.
RegMax | Data splitting-based two-stage maximum testing method for the regression coefficients in linear regression models
RegMin | Data splitting-based two-Stage minimum testing method for the regression coefficients in linear regression models.