effSelect: Model Selection for Effectiveness Distributions

In julian-urbano/simIReff: Stochastic Simulation for Information Retrieval Evaluation: Effectiveness Scores

Description

Functions to compute the log-likelihood, the Akaike Information Criterion, and the Bayesian Information Criterion for an effectiveness distribution. effSelect and which.effSelect are helper function for automatic selection from a given list of candidates.

Usage

effSelect(effs, method = "AIC", ...)

which.effSelect(effs, method = "AIC", ...)

## S3 method for class 'eff'
logLik(object, ...)

Arguments

effs	the list of candidate distributions to select from.
method	selection method. One of "AIC" (default), "BIC", or "logLik".
...	other parameters to the selection function.
object	an effectiveness distribution.

Value

the selected disttribution (effSelect), or its index within effs (which.effSelect).

See Also

logLik, AIC, BIC for details on model selection.

See effFitAndSelect to fit and select automatically.

Examples

ee <- effContFit(web2010ap[,5])
e <- effSelect(ee, method = "BIC")
e2 <- ee[[which.effSelect(ee, method = "BIC")]] # same as e

logLik(e)
AIC(e, k=4)
BIC(e)

julian-urbano/simIReff documentation built on May 21, 2019, 9:37 a.m.