make_staninput_deprecated: DEPRECATED: make_staninput

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

DEPRECATED: make_staninput

Description

DEPRECATED: make_staninput

Usage

make_staninput_deprecated(
  exposure,
  test,
  cues,
  category = "category",
  response = "response",
  group = "group",
  group.unique = NULL,
  center.observations = T,
  scale.observations = F,
  pca.observations = F,
  pca.cutoff = 1,
  lapse_rate = NULL,
  mu_0 = NULL,
  Sigma_0 = NULL,
  tau_scale = NULL,
  L_omega_eta = 1,
  split_loglik_per_observation = 0,
  use_univariate_updating = FALSE,
  verbose = F
)

Arguments

center.observations	Should the data be centered based on cues' means during exposure? Note that the cues' means used for centering are calculated after aggregating the data to all unique combinations specified by group.unique. These means are only expected to be the same as the standard deviations over the entire exposure data if the exposure data are perfectly balanced with regard to group.unique. Centering will not affect the inferred correlation or covariance matrices but it will affect the absolute position of the inferred means. The relative position of the inferred means remains unaffected. If TRUE and mu_0 is specified, mu_0 will also be centered (Sigma_0 is not affected by centering and thus not changed). (default: TRUE)
scale.observations	Should the data be standardized based on cues' standard deviation during exposure? Note that the cues' standard deviations used for scaling are calculated after aggregating the data to all unique combinations specified by group.unique. These standard deviations are only expected to be the same as the standard deviations over the entire exposure data if the exposure data are perfectly balanced with regard to group.unique. Scaling will not affect the inferred correlation matrix, but it will affect the inferred covariance matrix because it affects the inferred standard deviations. It will also affect the absolute position of the inferred means. The relative position of the inferred means remains unaffected. If TRUE and mu_0 and Sigma_0 are specified, mu_0 and Sigma_0 will also be scaled. (default: 'FALSE')
pca.observations	Should the data be transformed into orthogonal principal components? (default: FALSE)
pca.cutoff	Determines which principal components are handed to the MVBeliefUpdatr Stan program: all components necessary to explain at least the pca.cutoff of the total variance. (default: .95) Ignored if pca.observation = FALSE. (default: 1)

hlplab/MVBeliefUpdatr documentation built on July 5, 2025, 6:42 a.m.