bfa.ls.bc {bifurcatingr}R Documentation

Bias-Corrected Least Squares Estimators for Bifurcating Autoregressive Models

Description

This function performs bias correction on the least squares estimators of the autoregressive coefficients in a BAR(p) model using single, double and fast-double bootstrapping, and the linear-bias-function approach as described in Elbayoumi & Mostafa (2020).

Usage

bfa.ls.bc(
  z,
  p,
  method = "boot1",
  burn = 5,
  B1 = 999,
  B2 = 499,
  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)

B1

number of bootstrap samples (replicates) used in first round of bootstrapping

B2

number of bootstrap samples (replicates) used in second round of bootstrapping

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

coef.ls.bc

bias-corrected least squares estimates of the autoregressive coefficients

References

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

Examples

z <- bfa.tree.gen(63, 1, 1, 1, 0.5, 0.5, 0, 10, c(0.7))
bfa.ls.bc(z, p=1, method="boot1")
z <- bfa.tree.gen(63, 2, 1, 1, 0.5, 0.5, 0, 10, c(0.5, 0.3))
bfa.ls.bc(z, p=2, method="LBC")

[Package bifurcatingr version 1.0.0 Index]