effTransform: Transform effectiveness distributions towards a expected...

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

Description

Transforms the given effectiveness distribution such that its expected value matches a predefined value. For details, please refer to section 3.4 of (Urbano and Nagler, 2018).

Usage

effTransform(eff, mean, abs.tol = 1e-05)

effTransformAll(effs, means, abs.tol = 1e-05, silent = TRUE)

Arguments

eff	the distribution to transform.
mean	the target expected value to transform to. If missing, defaults to the mean in the data used to fit eff, if any.
abs.tol	the absolute tolerance of the transformation.
effs	the list of distributions to transform.
means	the vector of target expected values to transform to. If missing, defaults to the means in the data used to fit effs, if any.
silent	logical: should the report of error messages be suppressed?

Details

effTransformAll does the same but for a list of distributions and target means.

Value

an effectiveness distribution of class eff.cont.trans or eff.disc.trans, depending on the type of distribution.

References

J. Urbano and T. Nagler. (2018). Stochastic Simulation of Test Collections: Evaluation Scores. ACM SIGIR.

Examples

e <- effCont_beta(web2010ap[,1])
e2 <- effTransform(e, 0.12)
c(e$mean, e2$mean)
plot(e)
plot(e2)


# transform a list of distributions to the observed means
ee <- effContFitAndSelect(web2010ap[,1:5])
ee2 <- effTransformAll(ee)
obsmeans <- colMeans(web2010ap[,1:5])
sapply(ee, function(e)e$mean) - obsmeans
sapply(ee2, function(e)e$mean) - obsmeans

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