A function that use the arguments of a glm.cmp call to generate a better initial nu estimate.

getnu(
  param,
  y,
  xx,
  offset,
  llstart,
  fsscale = 1,
  lambdalb = 1e-10,
  lambdaub = 1000,
  maxlambdaiter = 1000,
  tol = 1e-06,
  summax = 100
)

Arguments

param

numeric vector: the model coefficients & the current value of nu. It is assumed that nu is in the last position of param.

y

numeric vector: response variable

xx

numeric matrix: the explanatory variables

offset

numeric vector: a vector of length equal to the number of cases

llstart

numeric: current log-likelihood value

fsscale

numeric: a scaling factor (generally >1) for the relaxed fisher scoring algorithm

lambdalb, lambdaub

numeric: the lower and upper end points for the interval to be searched for lambda(s).

maxlambdaiter

numeric: the maximum number of iterations allowed to solve for lambda(s).

tol

numeric: the convergence threshold. A lambda is said to satisfy the mean constraint if the absolute difference between the calculated mean and a fitted values is less than tol.

summax

maximum number of terms to be considered in the truncated sum

Value

List containing the following:

param

the model coefficients & the updated nu

maxl

the updated log-likelihood

fsscale

the final scaling factor used

Details

From version 0.3.4, this function is no longer being used as part of the estimation algorithm and this function will be defunct in our next update.