bfa_boot_ls_bc: 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).
a matrix containing the bootstrapped bias-correction
least squares estimates of the autoregressive coefficients
boot_data
a matrix
containing the bootstrap samples used
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.
References
Elbayoumi, T. M. & Mostafa, S. A. (2020). On the estimation bias
in bifurcating autoregressive models. Stat, 1-16.