getf0: 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
)

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.

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.