MV_critical_cp {mlrv}

Statistics-adapted values for extended minimum volatility selection.

Description

Smoothing parameter selection for bootstrap tests for change point tests

Usage

MV_critical_cp(
  y,
  X,
  t,
  gridm,
  gridtau,
  cvalue = 0.1,
  B = 100L,
  lrvmethod = 1L,
  ind = 2L,
  rescale = 0L
)

Arguments

y

vector, as used in the Heter_LRV

X

matrix, covariates

t

vector, time points.

gridm

vector, a grid of candidate m's.

gridtau

vector, a grid of candidate tau's.

cvalue

double, 1-quantile for the calculation of bootstrap variance, default 0.1.

B

integer, number of iterations for the calculation of bootstrap variance

lrvmethod

integer, see also Heter_LRV

ind

integer, the type of kernel, see also Heter_LRV

rescale

bool, whether to rescale when positiveness of the matrix is not obtained. default 0

Value

a matrix of critical values

References

Bai, L., and Wu, W. (2023). Detecting long-range dependence for time-varying linear models. To appear in Bernoulli

Examples

n = 300
t = (1:n)/n
data = bregress2(n, 2, 1) # time series regression model with 2 changes points
critical = MV_critical_cp(data$y, data$x,t,  c(3,4,5), c(0.2,0.25, 0.3))