RII.CVplot {RII}R Documentation

RII Cross Validation Plots

Description

Evaluates and plots a cross validation score over a specified range of values of the smoothing parameter.

Usage

RII.CVplot(count, pop, loglambda, ...)

Arguments

count A matrix of outcome counts with number of rows equal to the number of classes and number of columns equal to the number of standardizing groups. The outcome might be death, or disease incidence, for example.
pop A matrix of amounts of exposure, with dimension the same as that of count. The amount of exposure could be, for example, the number of person-years at risk, the mid-study period population or the number of individuals at risk at the start of the study period.
loglambda A vector of values of the smoothing parameter (on log scale)
... Graphical parameters

Details

RII.CVplot is designed to be used for exploratory purposes before estimating a relative index of inequality using RII. The cross validation score is computed taking each element of loglambda in turn to be the value of the smoothing parameter and the results are plotted. Using RII.CVplot (with perhaps several different values of loglambda) should allow the user to choose a suitable argument grid for use in RII, or select a single value of the smoothing parameter that is close to being optimal.

Author(s)

Jamie Sergeant, jamie.sergeant@nuffield.oxford.ac.uk

References

Sergeant, J. C. and Firth D. (2004) Relative index of inequality: definition, estimation and inference. In preparation.

See Also

RII, plot.RII.

Examples

## Plot the cross validation score over a range
## of smoothing parameter values for the LSDeaths data
data(LSDeaths)
LSdead <- xtabs(Deaths ~ class + age, data = LSDeaths)
LSatrisk <- xtabs(AtRisk ~ class + age, data = LSDeaths)
RII.CVplot(LSdead, LSatrisk, loglambda = seq(-2,18,len=21))

[Package RII version 0.4-1 Index]