bfa_ls_bc: 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 and Mostafa (2021).
bias-corrected least squares estimates of the
autoregressive coefficients
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.
References
Elbayoumi, T. M. & Mostafa, S. A. (2021). On the estimation bias
in bifurcating autoregressive models. Stat, e342.