Create an n2kSpde object — n2k

A new n2kSpde model is created when data is a data.frame.

In case data is an n2kSpde object, then only the model and status are updated. All other slots are unaffected.

Usage

n2k_spde(data, ..., model_fit)

# S4 method for class 'data.frame,ANY'
n2k_spde(
  data,
  status = "new",
  result_datasource_id,
  scheme_id,
  family = "poisson",
  formula,
  species_group_id,
  location_group_id,
  model_type,
  spde,
  first_imported_year,
  last_imported_year,
  duration,
  last_analysed_year,
  analysis_date,
  lin_comb = NULL,
  minimum = "",
  imputation_size,
  parent = character(0),
  seed,
  replicate_name = list(),
  control = list(),
  parent_status = "converged",
  parent_statusfingerprint,
  extra,
  ...,
  model_fit
)

# S4 method for class 'n2kSpde,inla'
n2k_spde(data, status, raw_imputed = NULL, ..., model_fit)

Arguments

data: a data.frame with the data to analyse
...: other arguments. See below
model_fit: The fitted model
status: A single character indicating the status of the model. Defaults to "waiting".
result_datasource_id: A string identifying the data source.
scheme_id: A single integer holding the id of the scheme.
family: the family to use in the INLA model.
formula: A single character identifying the comparison.
species_group_id: A string identifying the species group.
location_group_id: A string identifying the location group.
model_type: The type of the models. Must start with "inla comparison:".
spde: the Spde object. See [spde].
first_imported_year: Oldest year considered in the data.
last_imported_year: Most recent year considered in the data.
duration: The width of the moving window. Defaults to the last_imported_year - first_imported_year + 1.
last_analysed_year: Most recent year in the window. Defaults to last_imported_year.
analysis_date: A POSIXct date indicating the date that the dataset was imported.
lin_comb: A model matrix to calculate linear combinations.
minimum: The name of the variable which holds the minimum counts. Only relevant in case of multiple imputation.
imputation_size: The required number of imputations defaults to 0.
parent: The file fingerprint of the optional parent analysis.
seed: A single integer used as a seed for all calculations. A random seed will be inserted when missing.
replicate_name: A list with the names of replicates. Defaults to an empty list. Used in case of f(X, ..., replicate = Z). Should be a named list like e.g. list(X = c("a", "b", "c")).
control: A named list passed to INLA::inla() when fitting the model.
parent_status: A data.frame with columns parent_analysis (the file fingerprint of the parent), parentstatus_fingerprint (the status fingerprint of the parent), and parent_status (the status of the parent).
parent_statusfingerprint: The status fingerprint of the parent analysis.
extra: a data.frame with extra observations not used in the model. They will be added in subsequent analyses.
raw_imputed: the optional rawImputed object