Learn R Programming
TestDesign (version 1.0.2)

MLE: Generate maximum likelihood estimates of theta

Description

Generate maximum likelihood estimates of theta.

Usage

MLE(
  object,
  start_theta = NULL,
  max_iter = 100,
  crit = 0.001,
  select = NULL,
  theta_range = c(-4, 4),
  truncate = FALSE,
  max_change = 1,
  do_Fisher = TRUE
)
# S4 method for test
MLE(
  object,
  start_theta = NULL,
  max_iter = 100,
  crit = 0.001,
  select = NULL,
  theta_range = c(-4, 4),
  truncate = FALSE,
  max_change = 1,
  do_Fisher = TRUE
)
# S4 method for test_cluster
MLE(object, start_theta = NULL, max_iter = 100, crit = 0.001, select = NULL)

Arguments

object

A '>test object.

start_theta

An optional vector of start theta values.

max_iter

Maximum number of iterations.

crit

Convergence criterion.

select

A vector of indices identifying the items to subset.

theta_range

A range of theta values: c(minTheta, maxTheta).

truncate

Set TRUE to bound MLE to theta_range.

max_change

Maximum change between iterations.

do_Fisher

Set TRUE to use Fisher's method of scoring.