The Rank-ordered Logit (ROL) Models for ranking data. ROL models are extensions of the Luce models by incorporating covariates.
Usage
rol(dset, covariate)
Arguments
dset
a ranking dataset
covariate
the covariates of the ranking dataset
Details
Fit the rank-ordered logit models for the dataset and return a mle object. Standard methods on mle (e.g., @coef, @vcov) apply. By default, the intercept term is included.
References
Beggs, S., Cardell, S., and Hausman, J. (1981) Assessing the potential demand for electric cars. Journal of Econometrics, 16: 1-19.
Chapman, R. G., and Staelin, R. (1982) Exploiting rank ordered choice set data within the stochastic utility model. Journal of Market Research, 19:288-301.
Hausman, J., and Ruud, P. A. (1987) Specifying and testing econometric models for rank-ordered data. Journal of Econometrics, 34:83-104.
## create an artificial datasetX1 <- c(1,1,2,2,3,3)
X2 <- c(2,3,1,3,1,2)
X3 <- c(3,2,3,1,2,1)
X4 <- c(6,5,4,3,2,1)
test <- data.frame(X1,X2,X3)
## fit the Luce model## rol(test,X4)