graph_starting_values {MetricGraph}

Starting values for random field models on metric graphs

Description

Computes appropriate starting values for optimization of Gaussian random field models on metric graphs.

Usage

graph_starting_values(
  graph,
  model = c("alpha1", "alpha2", "isoExp", "GL1", "GL2"),
  data = TRUE,
  data_name = NULL,
  range_par = FALSE,
  nu = FALSE,
  manual_data = NULL,
  like_format = FALSE,
  log_scale = FALSE,
  model_options = list(),
  rec_tau = TRUE
)

Arguments

graph

A metric_graph object.

model

Type of model, "alpha1", "alpha2", "isoExp", "GL1", and "GL2" are supported.

data

Should the data be used to obtain improved starting values?

data_name

The name of the response variable in graph$data.

range_par

Should an initial value for range parameter be returned instead of for kappa?

nu

Should an initial value for nu be returned?

manual_data

A vector (or matrix) of response variables.

like_format

Should the starting values be returned with sigma.e as the last element? This is the format for the likelihood constructor from the 'rSPDE' package.

log_scale

Should the initial values be returned in log scale?

model_options

List object containing the model options.

rec_tau

Should a starting value for the reciprocal of tau be given?

Value

A vector, c(start_sigma_e, start_sigma, start_kappa)