bfa.ls.bc {bifurcatingr} | R Documentation |
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).
bfa.ls.bc( z, p, method = "boot1", burn = 5, B1 = 999, B2 = 499, boot.est = TRUE, boot.data = FALSE )
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. |
coef.ls.bc |
bias-corrected least squares estimates of the autoregressive coefficients |
Elbayoumi, T. M. & Mostafa, S. A. (2020). On the estimation bias in bifurcating autoregressive models. Stat, 1-16.
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")