NewtRaph: Newton-Raphson Method
In fblues/Test: Prediction region based on over-dispersed Poisson Regression

Description Usage Arguments Details Value Author(s) Examples

View source: R/NewtRaph.R

Function for Newton-Raphson method

1	NewtRaph(thseed, xiseed, Y, X, tol = 10^(-5))

`thseed`	Initial value for theta
`xiseed`	Initial value for xi
`Y`	data
`X`	data
`tol`	approximation tolerance

Okay

list

E. A. Pena

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (thseed, xiseed, Y, X, tol = 10^(-5)) 
{
    p = length(thseed)
    kiter = 0
    th0 = thseed
    xi0 = xiseed
    OK = FALSE
    while (!OK) {
        kiter = kiter + 1
        est0 = c(th0, xi0)
        out = UHFuncs(th0, xi0, Y, X)
        U = out$U
        H = out$H
        UUt = out$UUt
        Hinv = solve(H)
        est1 = est0 - Hinv %*% U
        th0 = est1[-(p + 1)]
        xi0 = est1[(p + 1)]
        dist = sqrt(sum((est1 - est0)^2))
        if (dist < tol) {
            OK = TRUE
        }
    }
    XiCov = Hinv %*% UUt %*% t(Hinv)
    return(list(kiter = kiter, th = th0, xi = xi0, U = U, H = H, 
        Hinv = Hinv, UUt = UUt, XiCov = XiCov))
  }