assessBsFun: Assess the performance of group-sparse loading estimate
In TOSI: Two-Directional Simultaneous Inference for High-Dimensional Models

assessBsFun

R Documentation

Assess the performance of group-sparse loading estimate

Description

Evaluate the model selection consistency rate (SCR), F-measure and the smallest canonical correlation and the larger values mean better peformance in model selection and parameter estimation.

Usage

  assessBsFun(hB, B0)

Arguments

`hB`	a `p`-by-`q` matrix, the estimated loading matrix.
`B0`	a `p`-by-`q` matrix, the true loading matrix.

Value

return a vecotor with three compoents whose names are scr,fmea, ccorB.

Note

nothing

Author(s)

Liu Wei

Examples

  dat <- gendata_Fac(n = 300, p = 500)
  res <- gsspFactorm(dat$X)
  assessBsFun(res$sphB, dat$B0)
  n <- nrow(dat$X)
  res <- gsspFactorm(dat$X, lambda1=0.05*n^(1/4), lambda2=9*n^(1/4))
  assessBsFun(res$sphB, dat$B0)

TOSI documentation built on Feb. 16, 2023, 7:46 p.m.