newton_x computes optimization algorithms to find the mode of the
posterior. Line search strategy with Armijo conditions is implemented
Arguments
- A
Matrix which links eta with the latent field, i.e., eta = A x
- x_hat
Vector with the elements of the latent field, i.e., eta_hat = A x_hat
- gk
Gradient in eta.
- Hk
Hessian in eta.
- a
Step length.
- Qx
Precision matrix for the prior of the latent field.
- strategy
Strategy to use to optimize. Now, line search strategy with quasi-newton algorithm is the only one avaliable.
- y
Vector with the response variable
- d
Number of categories.
Value
g0 : Gradient in x_hat_new. A numeric vector with the gradient in x_hat_new.
x_hat_new: New value of x after apply one iteration.
Author
Joaquín Martínez-Minaya jomarminaya@gmail.com