bfa_tree_gen {bifurcatingr}

Bifurcating Autoregressive Tree generator

Description

This function generate bifurcating autoregressive (BFA) trees of any size based on a BFA model of any order.

Usage

bfa_tree_gen(n, p, s1, s2, r1, r2, g, intercept, ar_coef, dist = "cnorm", a)

Arguments

n

tree size (integer)

p

an integer determining the order of bifurcating autoregressive model

s1

standard deviation of the errors distribution

s2

standard deviation of the second component of the mixture normal distribution generating contaminated errors. s2 should be greater than s1. s2 is only effective when g>0.

r1

correlation between pairs of errors

r2

is used in combination with r1 to compute the correlation between pairs of errors in the second component of the mixture normal distribution generating the contaminated errors. r2 is only effective when g>0.

g

proportion of contamination when contaminated normal distribution is selected, or a positive value representing the degrees of freedom when skew t-student distribution is selected. Defaults to zero producing non-contaminated multivariate normal errors.

intercept

the intercept in the BAR model generating the tree

ar_coef

a vector of length p giving the autoregressive coefficients in the BAR model generating the tree

dist

determine the distribution of the error. Three distributions are available; Contaminated normal distribution "cnorm", Skew normal distribution "snorm", and Skew t-student distribution "st".

a

an integer which regulates the the slant of the density when skew normal distribution or skew t-student distribution is selected. Defaults to zero producing non-skewed multivariate normal errors, and non-skewed multivariate t-student errors for the tree generation.

Value

A numeric vector representing a bifurcating autoregressive (BAR) tree with n observations.

Examples

# Non-contaminated normal BAR(1) tree:
bfa_tree_gen(127, 1, 1, 1, 0.5, 0.5, 0, 10, c(0.7))
# Non-contaminated normal BAR(2) tree:
bfa_tree_gen(127, 2, 1, 1, 0.5, 0.5, 0, 10, c(0.5, 0.3))
# Contaminated normal BAR(1) tree:
bfa_tree_gen(127, 1, 1, 2, 0.5, 0.5, 0.2, 10, c(0.7))
# BAR(1) tree with error generated from skewed normal distribution with skewness equals to -3:
bfa_tree_gen(127, 1, 1, 2, 0.5, 0.5, 0, 10, c(0.7),dist="snorm",-3)
# BAR(2) tree with error generated from skewed normal distribution with skewness equals to 3:
bfa_tree_gen(127, 2, 1, 2, 0.5, 0.5, 0, 10, c(0.7,0.5),dist="snorm",3)
# BAR(1) tree with error generated from skewed-t distribution with skewness equals
# to -3 and df equals to 10:
bfa_tree_gen(127, 1, 1, 2, 0.5, 0.5, 10, 10, c(0.7),dist="st",-3)
# BAR(2) tree with error generated from skewed-t distribution with skewness equals
# to 3 and df equals to 1:
bfa_tree_gen(127, 2, 1, 2, 0.5, 0.5, 10, 10, c(0.7,0.5),dist="st",3)