39 citations · 140 across the 29 of their papers we have counts for
7 papers · 1 filter
From Past to Future: Digital Methods Towards Artefact Analysis
Andrew Harris, Andrea Cremaschi, Tse Siang Lim +2
Over the past two decades, Digital Humanities has transformed the landscape of humanities and social sciences, enabling advanced computational analysis and interpretation of extens…
Bayesian modelling of response to therapy and drug-sensitivity in acute lymphoblastic leukemia
Andrea Cremaschi, Wenjian Yang, Maria De Iorio +3
Acute lymphoblastic leukemia (ALL) is a heterogeneous hematologic malignancy involving the abnormal proliferation of immature lymphocytes, accounting for most pediatric cancer case…
Dynamic degree-corrected blockmodels for social networks: a nonparametric approach
Linda S. L. Tan, Maria De Iorio
A nonparametric approach to the modeling of social networks using degree-corrected stochastic blockmodels is proposed. The model for static network consists of a stochastic blockmo…
Bayesian Nonparametric Modelling of Joint Gap Time Distributions for Recurrent Event Data
Marta Tallarita, Maria De Iorio, Alessandra Guglielmi +1
We propose autoregressive Bayesian semi-parametric models for waiting times between recurrent events. The aim is two-fold: inference on the effect of possibly time-varying covariat…
A comparative review of variable selection techniques for covariate dependent Dirichlet process mixture models
William Barcella, Maria De Iorio, Gianluca Baio
Dirichlet Process Mixture (DPM) models have been increasingly employed to specify random partition models that take into account possible patterns within the covariates. Furthermor…
Variable Selection in Covariate Dependent Random Partition Models: an Application to Urinary Tract Infection
William Barcella, Maria De Iorio, Gianluca Baio +1
Lower urinary tract symptoms (LUTS) can indicate the presence of urinary tract infection (UTI), a condition that if it becomes chronic requires expensive and time consuming care as…
A semi-automatic method to guide the choice of ridge parameter in ridge regression
Erika Cule, Maria De Iorio
We consider the application of a popular penalised regression method, Ridge Regression, to data with very high dimensions and many more covariates than observations. Our motivation…