NMLmulti-package: Compute Normalized Maximum Likelihood (NML) penalties for...

In davidkellen/NMLmulti: Computing Normalized Maximum Likelihood Penalties for Multinomial Models

Compute Normalized Maximum Likelihood (NML) penalties for multinomial models

Description

Computes NML penalties for models of joint multinomial data using Monte Carlo integration.

Author(s)

David Kellen, Karl Christoph Klauer, and Constantin Meyer-Grant

Maintainer: David Kellen <[e-mail]>

References

Klauer, K. C., & Kellen, D. (2011). The flexibility of models of recognition memory: An analysis by the minimum-description length principle. Journal of Mathematical Psychology, 55, 430-450.

Klauer, K. C. & Kellen, D. (2015). The Flexibility of Models of Recognition Memory: The Case of Confidence Ratings. Journal of Mathematical Psychology, 67, 8-25.

Examples

  ## Not run: 
# computes NML penalty for the SCR model
nml_scr <- run_nml(fun=NMLmulti::SCR, parl=10, ks=rep(3,5), 
            Ns=c(rep(100,4),200), fits = 1, cores=6, batchsize=5000,
            burn=10000, precision=0.1)

# computes NML penalty for the LT model
nml_lt  <- run_nml(fun=NMLmulti::LT, parl=10, ks=rep(3,5), 
            Ns=c(rep(100,4),200), fits = 1, cores=6, batchsize=5000,
            burn=10000, precision=0.1) 
  
## End(Not run)

davidkellen/NMLmulti documentation built on Oct. 15, 2024, 6:14 a.m.