find_starting_points: Find starting points

In KatarzynaReluga/postcAIC: Post-cAIC selection inference under Linear Mixed Models

Description

Function find_starting_points finds starting points which satisfies derived constrains. The starting points are then used to sample from a truncated normal distribution

Usage

find_starting_points(
  n_starting_points,
  p,
  n_models_to_compare,
  list_constraints,
  scale_mvrnorm = 10
)

Arguments

n_starting_points	Number of initial starting points for sampling from a truncated normal distribution
p	Number of all fixed parameters under consideration (intercept included)
n_models_to_compare	Number of models in a model set to compare with (all models in the model set minus the selected model)
list_constraints	List which describes the constraints imposed on the normal distribution
scale_mvrnorm	Scale parameter for multivariate normal distribution to sample. Default: scale_mvrnorm = 10.

Details

The running time of function find_starting_points is extremely sensitive to the choice of scaling factor scale_mvrnorm. We suggest choosing a larger/smaller value if the running time is longer than 1 minute.

Value

starting_points

n_starting_points different starting points

KatarzynaReluga/postcAIC documentation built on Jan. 25, 2022, 12:33 a.m.