Generate Burr dependent data
Random generation function for the dependent Burr with a, b two shapes parameters and alpha the dependence parameter.
rburr.dependent(n, a, b, alpha)
n |
the number of observations. If length(n) > 1, the length is taken to be the number required. |
a |
a parameter of the function. |
b |
a parameter of the function. |
alpha |
the dependence parameter. It is defined by a single value between 0 and 1. The value 1 corresponds to the full independence. The closer to 0 the value of alpha is, the stronger is the dependence. alpha cannot take the value 0. |
The description of the dependence is described in Fawcett and Walshaw (2007). The Burr distribution is : F(x) = 1 - ( 1 + (x ^ a) ) ^ { - b }, x > 0, a > 0, b > 0 where a and b are shapes of the distribution.
Generates a vector of random deviates. The length of the result is determined by n.
Fawcett, D. and Walshaw, D. (2007). Improved estimation for temporally clustered extremes. Environmetrics, 18.2, 173-188.
theta <- function(t){
1/2*(1/10+sin(pi*t))*(11/10-1/2*exp(-64*(t-1/2)^2))
}
n <- 200
t <- 1:n/n
Theta <- theta(t)
plot(theta)
alpha <- 0.6
Burr.dependent <- rburr.dependent(n, 1/Theta, 1, alpha)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.