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) and Duttilo et al (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.

Bootstrapping the ARDL Tests for Cointegration

The bootstrap ARDL tests for cointegration is the main functionality of this package. It also acts as a wrapper of the most commond ARDL testing procedures for cointegration: the bound tests of Pesaran, Shin and Smith (PSS; 2001 - ) and the asymptotic test on the independent variables of Sam, McNown and Goh (SMG: 2019 - ). Bootstrap and bound tests are performed under both the conditional and unconditional ARDL models.

Interface to the ITALIC Database of Lichen Biodiversity

A programmatic interface to the Web Service methods provided by ITALIC (< https://italic.units.it>). ITALIC is a database of lichen data in Italy and bordering European countries. 'ritalic' includes functions for retrieving information about lichen scientific names, geographic distribution, ecological data, morpho-functional traits and identification keys. More information about the data is available at < https://italic.units.it/?procedure=base&t=59&c=60>. The API documentation is available at < https://italic.units.it/?procedure=api>.

Interactive Processing and Segmentation of Forest TLS Point-Cloud Data

Tools for the processing, segmentation, and analysis of terrestrial laser scanning (TLS and MLS) forest point-cloud data. The package provides fast voxel-based processing, classification of point clouds into forest floor, understory, canopy, and woody components, and algorithms for single-tree analysis and structural characterization. Methods are designed to handle large and dense point-cloud datasets efficiently, supporting applications in forest structure assessment, connectivity analysis, and fire-risk evaluation. Input data are provided as '.xyz', '.txt', '.las', or '.laz' point-cloud files. The circle-fitting routines used for diameter estimation are adapted, in base R, from the 'conicfit' package (GPL-3) by Jose Gama, based on the original algorithms and code by Nikolai Chernov. For methodological details, see Ferrara and Arrizza (2025) < https://hdl.handle.net/20.500.14243/533471> and Ferrara et al. (2018) .

Carbon-Related Assessment of Silvicultural Concepts

A simulation model and accompanying functions that support assessing silvicultural concepts on the forest estate level with a focus on the CO2 uptake by wood growth and CO2 emissions by forest operations. For achieving this, a virtual forest estate area is split into the areas covered by typical phases of the silvicultural concept of interest. Given initial area shares of these phases, the dynamics of these areas is simulated. The typical carbon stocks and flows which are known for all phases are attributed post-hoc to the areas and upscaled to the estate level. CO2 emissions by forest operations are estimated based on the amounts and dimensions of the harvested timber. Probabilities of damage events are taken into account.

Incidence Estimation Tools

Tools for estimating incidence from biomarker data in cross- sectional surveys, and for calibrating tests for recent infection. Implements and extends the method of Kassanjee et al. (2012) .

The Maraca Plot: Visualizing Hierarchical Composite Endpoints

Supports visual interpretation of hierarchical composite endpoints (HCEs). HCEs are complex constructs used as primary endpoints in clinical trials, combining outcomes of different types into ordinal endpoints, in which each patient contributes the most clinically important event (one and only one) to the analysis. See Karpefors M et al. (2022) .

Discriminant Non-Negative Matrix Factorization

Discriminant Non-Negative Matrix Factorization aims to extend the Non-negative Matrix Factorization algorithm in order to extract features that enforce not only the spatial locality, but also the separability between classes in a discriminant manner. It refers to three article, Zafeiriou, Stefanos, et al. "Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification." Neural Networks, IEEE Transactions on 17.3 (2006): 683-695. Kim, Bo-Kyeong, and Soo-Young Lee. "Spectral Feature Extraction Using dNMF for Emotion Recognition in Vowel Sounds." Neural Information Processing. Springer Berlin Heidelberg, 2013. and Lee, Soo-Young, Hyun-Ah Song, and Shun-ichi Amari. "A new discriminant NMF algorithm and its application to the extraction of subtle emotional differences in speech." Cognitive neurodynamics 6.6 (2012): 525-535.