lift_likelihood_to_model: Turn an MVG/NIW_belief object into an ideal observer/adaptor

In hlplab/MVBeliefUpdatr: Fitting, Summarizing, and Visualizing of Multivariate Gaussian Ideal Observers and Adaptors

Turn an MVG/NIW_belief object into an ideal observer/adaptor

Description

Make an ideal observer or adaptor out of an MVG or NIW_belief object, respectively, by providing the missing information about the prior, lapse rate, bias, and perceptual noise (if any).

Usage

lift_likelihood_to_model(
  x,
  group = NULL,
  prior = rep(1/get_nlevels_of_category_labels_from_model(x),
    get_nlevels_of_category_labels_from_model(x)),
  lapse_rate = 0,
  lapse_bias = rep(1/get_nlevels_of_category_labels_from_model(x),
    get_nlevels_of_category_labels_from_model(x)),
  Sigma_noise = NULL,
  verbose = F
)

lift_exemplars_to_exemplar_model(
  x,
  group = NULL,
  prior = rep(1/(n.cat <- get_nlevels_of_category_labels_from_model(x)), n.cat),
  lapse_rate = 0,
  lapse_bias = rep(1/(n.cat <- get_nlevels_of_category_labels_from_model(x)), n.cat),
  Sigma_noise = NULL,
  verbose = F
)

lift_MVG_to_MVG_ideal_observer(
  x,
  group = NULL,
  prior = rep(1/(n.cat <- get_nlevels_of_category_labels_from_model(x)), n.cat),
  lapse_rate = 0,
  lapse_bias = rep(1/(n.cat <- get_nlevels_of_category_labels_from_model(x)), n.cat),
  Sigma_noise = NULL,
  verbose = F
)

lift_NIW_belief_to_NIW_ideal_adaptor(
  x,
  group = NULL,
  prior = rep(1/(n.cat <- get_nlevels_of_category_labels_from_model(x)), n.cat),
  lapse_rate = 0,
  lapse_bias = rep(1/(n.cat <- get_nlevels_of_category_labels_from_model(x)), n.cat),
  Sigma_noise = NULL,
  verbose = F
)

lift_MVG_ideal_observer_to_NIW_ideal_adaptor(
  x,
  group = NULL,
  kappa,
  nu,
  verbose = F
)

Arguments

x	Either an MVG or NIW_belief object.
group	Optionally, a grouping structure can be specified. If group structure is not NULL, one NIW belief or ideal adaptor will be derived for each level of group_structure. (default: NULL)
prior	Optionally specify a prior probability for each category (in each group). (default: a uniform prior over all categories).
lapse_rate	Optionally specify a lapse rate. (default: 0)
lapse_bias	Optionally specify a lapse bias for each category. (default: uniform bias for all categories)
Sigma_noise	Optionally specify a (multivariate Gaussian) covariance matrix of perceptual noise. This argument will be ignored if NULL. (default: NULL)
verbose	If true provides more information. (default: FALSE)
kappa	The strength of the beliefs over the category mean (pseudocounts). (default: same as nu)
nu	The strength of the beliefs over the category covariance matrix (pseudocounts). (default: number of cues + 2)
keep.category_parameters	Should categories' mu and Sigma be included in the output (in addition to m and S of the prior)? (default: FALSE)

Value

A tibble that is an NIW_belief or NIW_ideal_adaptor object.

See Also

TBD

hlplab/MVBeliefUpdatr documentation built on March 29, 2025, 10:42 p.m.