Search results for "Penalized Likelihood"
showing 4 items of 14 documents
Inferential tools in penalized logistic regression for small and sparse data: A comparative study.
2016
This paper focuses on inferential tools in the logistic regression model fitted by the Firth penalized likelihood. In this context, the Likelihood Ratio statistic is often reported to be the preferred choice as compared to the ‘traditional’ Wald statistic. In this work, we consider and discuss a wider range of test statistics, including the robust Wald, the Score, and the recently proposed Gradient statistic. We compare all these asymptotically equivalent statistics in terms of interval estimation and hypothesis testing via simulation experiments and analyses of two real datasets. We find out that the Likelihood Ratio statistic does not appear the best inferential device in the Firth penal…
Selecting the tuning parameter in penalized Gaussian graphical models
2019
Penalized inference of Gaussian graphical models is a way to assess the conditional independence structure in multivariate problems. In this setting, the conditional independence structure, corresponding to a graph, is related to the choice of the tuning parameter, which determines the model complexity or degrees of freedom. There has been little research on the degrees of freedom for penalized Gaussian graphical models. In this paper, we propose an estimator of the degrees of freedom in $$\ell _1$$ -penalized Gaussian graphical models. Specifically, we derive an estimator inspired by the generalized information criterion and propose to use this estimator as the bias term for two informatio…
Bivariate logistic models for the analysis of the students' University "success"
2012
We analyze the students’ success at University by considering their performance in terms of both “qualitative performance”, measured by their grade average, and “quantitative performance”, measured by University Credits accumulated. To jointly model both marginal and association relationships with covariates, the analysis has been carried out by fitting a bivariate ordered logistic model (BOLM), in a nonparametric fashion, by penalized maximum likelihood estimation. The advantages of such model are in terms of parsimony and parameters interpretation, while preserving goodness-of-fit. The application regards an engineering student (ES) cohort from the University of Palermo.
Estimating finite mixtures of semi-Markov chains: an application to the segmentation of temporal sensory data
2019
Summary In food science, it is of great interest to obtain information about the temporal perception of aliments to create new products, to modify existing products or more generally to understand the mechanisms of perception. Temporal dominance of sensations is a technique to measure temporal perception which consists in choosing sequentially attributes describing a food product over tasting. This work introduces new statistical models based on finite mixtures of semi-Markov chains to describe data collected with the temporal dominance of sensations protocol, allowing different temporal perceptions for a same product within a population. The identifiability of the parameters of such mixtur…