| loglogistic6_gradient_2 {drda} | R Documentation | 
6-parameter log-logistic function gradient and Hessian
Description
Evaluate at a particular set of parameters the gradient and Hessian of the 6-parameter log-logistic function.
Usage
loglogistic6_gradient_2(x, theta)
loglogistic6_hessian_2(x, theta)
loglogistic6_gradient_hessian_2(x, theta)
Arguments
x | 
 numeric vector at which the function is to be evaluated.  | 
theta | 
 numeric vector with the six parameters in the form
  | 
Details
The 6-parameter log-logistic function f(x; theta) is defined here as
g(x; theta) = (x^eta / (xi * x^eta + nu * phi^eta))^(1 / nu)
f(x; theta) = alpha + delta g(x; theta)
where x >= 0, theta = c(alpha, delta, eta, phi, nu, xi), eta > 0,
phi > 0, nu > 0, and xi > 0.
This set of functions use a different parameterization from
link[drda]{loglogistic6_gradient}. To avoid the non-negative
constraints of parameters, the gradient and Hessian computed here are for
the function with eta2 = log(eta), phi2 = log(phi), nu2 = log(nu), and
xi2 = log(xi).
Note that argument theta is on the original scale and not on the log scale.
Note: The 6-parameter log-logistic function is over-parameterized and non-identifiable from data. It is available only for theoretical research.
Value
Gradient or Hessian of the alternative parameterization evaluated at the specified point.