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Optimal Graph Partition using the Persistence
Calculate the optimal vertex partition of a graph using the persistence as objective function.
These subroutines have been used in Avellone et al.
The GiViTI Calibration Test and Belt
Functions to assess the calibration of logistic regression models with the GiViTI (Gruppo Italiano per la Valutazione degli interventi in Terapia Intensiva, Italian Group for the Evaluation of the Interventions in Intensive Care Units - see < http://www.giviti.marionegri.it/>) approach. The approach consists in a graphical tool, namely the GiViTI calibration belt, and in the associated statistical test. These tools can be used both to evaluate the internal calibration (i.e. the goodness of fit) and to assess the validity of an externally developed model.
Intervention in Prediction Measure for Random Forests
Computes intervention in prediction measure for assessing variable importance for random forests. See details at I. Epifanio (2017)
Biodiversity Assessment Tools
Includes algorithms to assess alpha and beta diversity
in all their dimensions (taxonomic, phylogenetic and functional).
It allows performing a number of analyses based on species
identities/abundances, phylogenetic/functional distances, trees,
convex-hulls or kernel density n-dimensional hypervolumes
depicting species relationships.
Cardoso et al. (2015)
Environmental Noise Pollution Data Analysis
Provides analyse, interpret and understand noise pollution data. Data are typically regular time series measured with sound meter. The package is partially described in Fogola, Grasso, Masera and Scordino (2023,
Pointcloud Interactive Computation
Provides advanced algorithms for analyzing pointcloud data from terrestrial laser scanner in
forestry applications. Key features include fast voxelization of
large datasets; segmentation of point clouds into forest floor,
understorey, canopy, and wood components. The package enables
efficient processing of large-scale forest pointcloud data, offering
insights into forest structure, connectivity, and fire risk
assessment. Algorithms to analyze pointcloud data (.xyz input file).
For more details, see Ferrara & Arrizza (2025) < https://hdl.handle.net/20.500.14243/533471>.
For single tree segmentation details, see Ferrara et al. (2018)
Interactively Gate Points
Interactively gate points on a scatter plot. Interactively drawn gates are recorded and can be applied programmatically to reproduce results exactly. Programmatic gating is based on the package gatepoints by Wajid Jawaid.
Cointegrated ICU Forecasting
Set of forecasting tools to predict ICU beds using a Vector Error Correction model with a single cointegrating vector. Method described in Berta, P. Lovaglio, P.G. Paruolo, P. Verzillo, S., 2020. "Real Time Forecasting of Covid-19 Intensive Care Units demand" Health, Econometrics and Data Group (HEDG) Working Papers 20/16, HEDG, Department of Economics, University of York, < https://www.york.ac.uk/media/economics/documents/hedg/workingpapers/2020/2016.pdf>.
Constrained Mixture of Generalized Normal Distributions
The 'cmgnd' implements the constrained mixture of generalized normal distributions model, a flexible statistical framework for modelling univariate data exhibiting non-normal features such as skewness, multi-modality, and heavy tails. By imposing constraints on model parameters, the 'cmgnd' reduces estimation complexity while maintaining high descriptive power, offering an efficient solution in the presence of distributional irregularities. For more details see Duttilo and Gattone (2025)
Cancer RADAR Project Tool
Cancer RADAR is a project which aim is to develop an infrastructure that allows quantifying the risk of cancer by migration background across Europe. This package contains a set of functions cancer registries partners should use to reshape 5 year-age group cancer incidence data into a set of summary statistics (see Boyle & Parkin (1991, ISBN:978-92-832-1195-2)) in lines with Cancer RADAR data protections rules.