getf0: f0 optimization routine
In gldrm: Generalized Linear Density Ratio Models

getf0

R Documentation

f0 optimization routine

Description

f0 optimization routine

Usage

getf0(
  y,
  spt,
  ySptIndex,
  sptFreq,
  sampprobs,
  mu,
  mu0,
  f0Start,
  thStart,
  thetaControl = theta.control(),
  f0Control = f0.control(),
  trace = FALSE
)

Arguments

`y`	Vector of response values.
`spt`	Vector of unique observed support points in the response.
`ySptIndex`	Index of each `y` value within `spt`.
`sptFreq`	Vector containing frequency of each `spt` value.
`sampprobs`	Optional matrix of sampling probabilities.
`mu`	Fitted mean for each observation. Only used if `sampprobs=NULL`.
`mu0`	Mean constraing for f0.
`f0Start`	Starting f0 values. (Typically the estimate from the previous iteration.)
`thStart`	Starting theta values. Needs to be a list of values matching the output of the `getTheta` function.
`thetaControl`	A "thetaControl" object returned from the `theta.control` function.
`f0Control`	An "f0Control" object returned from the `f0.control` function. trace Logical. If TRUE, then progress is printed to terminal at each iteration.

Value

A list containing the following:

f0 Updated values.
llik Updated log-likelihood.
th Updated list returned from the getTheta function.
conv Convergence indicator.
iter Number of iterations until convergence.
nhalf The number of half steps taken on the last iteration if the initial BFGS update did not improve the log-likelihood.
score.log Score function with respect to log(f0) at convergence.
info.log Information matrix with respect to log(f0) at convergence.