confintMSmix {MSmix} | R Documentation |
Hessian-based confidence intervals for mixtures of Mallows models with Spearman distance
Description
Return the Hessian-based confidence intervals of the continuous parameters of a mixture of Mallow models with Spearman distance fitted to full rankings, namely the component-specific precisions and weights.
Usage
confintMSmix(object, conf_level = 0.95)
Arguments
object |
An object of class |
conf_level |
Value in the interval (0,1] indicating the desired confidence level of the interval estimates. Defaults to 0.95. |
Details
The current implementation of the hessian-based confidence intervals assumes that the observed rankings are complete.
Value
A list with the following named components:
ci_theta |
The confidence intervals for the precision parameters. |
ci_weights |
The confidence intervals for the mixture weights. Returned when |
References
Crispino M, Mollica C and Modugno L (2024+). MSmix: An R Package for clustering partial rankings via mixtures of Mallows Models with Spearman distance. (submitted)
Marden JI (1995). Analyzing and modeling rank data. Monographs on Statistics and Applied Probability (64). Chapman & Hall, ISSN: 0-412-99521-2. London.
Mclachlan G and Peel D (2000). Finite Mixture Models. Vol. 299. New York: Wiley.
Examples
## Example 1. Simulate rankings from a 2-component mixture of Mallow models
## with Spearman distance.
set.seed(123)
d_sim <- rMSmix(sample_size = 75, n_items = 8, n_clust = 2)
rankings <- d_sim$samples
# Fit the basic Mallows model with Spearman distance.
set.seed(123)
fit1 <- fitMSmix(rankings = rankings, n_clust = 1, n_start = 10)
# Compute the hessian-based confidence intervals for the MLEs of the precision.
confintMSmix(object = fit1)
# Fit the true model.
set.seed(123)
fit2 <- fitMSmix(rankings = rankings, n_clust = 2, n_start = 10)
# Compute the hessian-based confidence intervals for the MLEs of the weights and precisions.
confintMSmix(object = fit2)