MultiTSrowMinST: Two-Stage Minimum Row Test method for the loading vectors.

In feiyoung/SpagFainfer: Estimation and inference on high-dimensional group-sparse factor models

Description

Conduct the simultaneous inference for a set of loading vectors as for the NUll hypothesises H02, where H02 assume there is zero loading vector in the set of loading vectors.

Usage

  MultiTSrowMinST(X, G2,  alpha=0.05, Nsplit= 5, sub.frac=0.5)

Value

return a matrix with class "Min-test", row names 'chiq_test' , and column names 'CriticalValue', 'TesMultiTStatistic', 'reject_status', and 'p-value', including all the information about testing.

Note

nothing

Author(s)

Liu Wei

References

Wei Liu, Huazhen Lin, Jin Liu (2020). Estimation and inference on high-dimensional sparse factor models.

See Also

factor, Factorm,simultestentryX

Examples

  ### Example
  dat <- gendata(n = 300, p = 500)
  res <- Factorm(dat$X)
  X <- dat$X
  # ex1: H01 is false
  G2 <- 1:200; # all are nonzero loading vectors
  MultiTSrowMinST(X, G2=G2, alpha=0.05, sub.frac=0.5)
  # ex2: H01 is true
  G2 <- 1:500 # all are zero loading vectors
  MultiTSrowMinST(X, G2=G2, alpha=0.05, sub.frac=0.5)

feiyoung/SpagFainfer documentation built on April 4, 2020, 5:20 p.m.