MultiTSrowMaxST: Multi-split-based Two-Stage Maximum Row Test method for the...

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 H01, where H01 assume the set of loading vectors are all zeroes.

Usage

  MultiTSrowMaxST(X, G1,  alpha=0.05, Nsplit= 5, sub.frac=0.5)

Value

return a matrix with class "Max-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
  G1 <- 1:10; # all are nonzero loading vectors
  MultiTSrowMaxST(X, G1=G1, alpha=0.05, sub.frac=0.5)
  # ex2: H01 is true
  G1 <- 481:500 # all are zero loading vectors
  MultiTSrowMaxST(X, G1=G1, alpha=0.05, sub.frac=0.5)

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