tests/testthat/_snaps/model_selection.md

In loelschlaeger/RprobitB: Bayesian Probit Choice Modeling

computing model selection criteria works

Code
  model_selection(model_train, criteria = criteria)
Output
           model_train
  npar               4
  LL          -1728.59
  AIC          3465.18
  BIC          3489.10
  WAIC         3461.27
  se(WAIC)        0.07
  pWAIC           2.10
  MMLL        -1730.35
  pred_acc      69.10%

Code
  AIC(model_train)
Output
  [1] 3465.175

Code
  BIC(model_train)
Output
  [1] 3489.105

Code
  WAIC(model_train)
Output
  3461.27 (0.07)

Code
  nobs(model_train)
Output
  [1] 2929

Code
  logLik(model_train, recompute = TRUE)
Output
  'log Lik.' -1728.588 (df=4)

Code
  npar(model_train)
Output
  [1] 4

loelschlaeger/RprobitB documentation built on Oct. 15, 2024, 11:08 a.m.