phicom: phi-component Models

In pmr: Probability Models for Ranking Data

phi-component Models

Description

phi-component Models for ranking data. The distance-based models assume that rankings closer to the modal ranking are more likely to be observed. Phi-component models are extensions of distance-based models with Kendall's distance by allowing weights at different stages.

Usage

phicom(dset)

Arguments

dset	a ranking dataset (aggregated)

Details

Fit the phi-component models for the dataset and return a mle object. Standard methods on mle (e.g., @coef, @vcov) apply. The modal ranking and the Chi-square residual are given in the output.

Author(s)

Paul H. Lee and Philip L. H. Yu

References

Fligner, M. A., and Verducci, J. S. (1986) Distance based ranking models. Journal of the Royal Statistical Society Series B, 48(3), 359-369.

See Also

dbm

Examples

## create an artificial dataset
X1 <- c(1,1,2,2,3,3)
X2 <- c(2,3,1,3,1,2)
X3 <- c(3,2,3,1,2,1)
n <- c(6,5,4,3,2,1)
test <- data.frame(X1,X2,X3,n)

## fit the phi-component model
## phicom(test)

pmr documentation built on June 24, 2022, 5:06 p.m.