bfa_boot_ls_bc {bifurcatingr}

Bootstrap of Bias-Correction Least Squares Estimators of BAR(p) Models

Description

This function performs linear-bias-function bias-correction (LBC), single bootstrap, double bootstrap, fast-double bootstrap of the bias-correction least squares estimators of the autoregressive coefficients in a bifurcating autoregressive (BAR) model of any order p as described in Elbayoumi & Mostafa (2020).

Usage

bfa_boot_ls_bc(
  z,
  p,
  method = "boot1",
  burn = 5,
  B,
  boot_est = TRUE,
  boot_data = FALSE
)

Arguments

z

a numeric vector containing the tree data

p

an integer determining the order of bifurcating autoregressive model to be fit to the data

method

method of bias correction. Currently, "boot1", "boot2", "boot2fast" and "LBC" are supported and they implement single bootstrap, double bootstrap, fast-double bootstrap, and linear-bias-function bias-correction, respectively.

burn

number of tree generations to discard before starting the bootstrap sample (replicate)

B

number of bootstrap samples (replicates)

boot_est

a logical that determines whether the bootstrapped least squares estimates of the autoregressive coefficients should be returned. Defaults to TRUE.

boot_data

a logical that determines whether the bootstrap samples should be returned. Defaults to FALSE.

Value

boot_bcest

a matrix containing the bootstrapped bias-correction least squares estimates of the autoregressive coefficients

boot_data

a matrix containing the bootstrap samples used

References

Elbayoumi, T. M. & Mostafa, S. A. (2020). On the estimation bias in bifurcating autoregressive models. Stat, 1-16.

Examples

z <- bfa_tree_gen(31, 1, 1, 1, 0.5, 0.5, 0, 10, c(0.7))
bfa_boot_ls_bc(z, p=1, method="LBC", B=500)
hist(bfa_boot_ls_bc(z, p=1, method="LBC", B=500)$boot_bcest)