35 citations · 40 across the 11 of their papers we have counts for
11 papers
Finite mixtures in capture-recapture surveys for modelling residency patterns in marine wildlife populations
Gianmarco Caruso, Pierfrancesco Alaimo Di Loro, Marco Mingione +3
In this work, the goal is to estimate the abundance of an animal population using data coming from capture-recapture surveys. We leverage the prior knowledge about the population's…
Efficient and accurate inference for mixtures of Mallows models with Spearman distance
Marta Crispino, Cristina Mollica, Valerio Astuti +1
The Mallows model occupies a central role in parametric modelling of ranking data to learn preferences of a population of judges. Despite the wide range of metrics for rankings tha…
New algorithms and goodness-of-fit diagnostics from remarkable properties of ranking models
Cristina Mollica, Luca Tardella
The forward order assumption postulates that the ranking process of the items is carried out by sequentially assigning the positions from the top (most-liked) to the bottom (least-…
Bayesian analysis of ranking data with the constrained Extended Plackett-Luce model
Cristina Mollica, Luca Tardella
Multistage ranking models, including the popular Plackett-Luce distribution (PL), rely on the assumption that the ranking process is performed sequentially, by assigning the positi…
Moment-based Bayesian Poisson Mixtures for inferring unobserved units
Danilo Alunni Fegatelli, Luca Tardella
We exploit a suitable moment-based characterization of the mixture of Poisson distribution for developing Bayesian inference for the unknown size of a finite population whose units…
Algorithms and diagnostics for the analysis of preference rankings with the Extended Plackett-Luce model
Cristina Mollica, Luca Tardella
Choice behavior and preferences typically involve numerous and subjective aspects that are difficult to be identified and quantified. For this reason, their exploration is frequent…
PLMIX: An R package for modeling and clustering partially ranked data
Cristina Mollica, Luca Tardella
Ranking data represent a peculiar form of multivariate ordinal data taking values in the set of permutations. Despite the numerous methodological contributions to increase the flex…
Bayesian mixture of Plackett-Luce models for partially ranked data
Cristina Mollica, Luca Tardella
The elicitation of an ordinal judgment on multiple alternatives is often required in many psychological and behavioral experiments to investigate preference/choice orientation of a…
Flexible behavioral capture-recapture modelling
Danilo Alunni Fegatelli, Luca Tardella
We develop some new strategies for building and fitting new flexible classes of parametric capture-recapture models for closed populations which can be used to address a better und…
Epitope profiling via mixture modeling of ranked data
Cristina Mollica, Luca Tardella
We propose the use of probability models for ranked data as a useful alternative to a quantitative data analysis to investigate the outcome of bioassay experiments, when the prelim…
An alternative marginal likelihood estimator for phylogenetic models
Serena Arima, Luca Tardella
Bayesian phylogenetic methods are generating noticeable enthusiasm in the field of molecular systematics. Many phylogenetic models are often at stake and different approaches are u…