Functional and variables selection in extreme value models for regional flood frequency analysis

The problem of estimating return levels of river discharge, relevant in flood frequency analysis, is tackled by relying on the extreme value theory. The Generalized Extreme Value (GEV) distribution is assumed to model annual maxima values of river discharge registered at multiple gauging stations belonging to the same river basin. The specific features of the data from the Upper Danube basin drive the definition of the proposed statistical model. Firstly, Bayesian P-splines are considered to account for the non-linear effects of station-specific covariates on the GEV parameters. Secondly, the problem of functional and variable selection is addressed by imposing a grouped horseshoe prior on the coefficients, to encourage the shrinkage of non-relevant components to zero. A cross-validation study is organized to compare the proposed modeling solution to other models, showing its potential in reducing the uncertainty of the ungauged predictions without affecting their calibration

Bayesian inference for quantiles and conditional means in log-normal models

The main topic of the thesis is the proper execution of a Bayesian inference if log-normality is assumed for data. In fact, it is known that a particular care is required in this context, since the most common prior distributions for the variance in log scale produce posteriors for the log-normal mean which do not have finite moments. Hence, classical summary measures of the posterior such as expectation and variance cannot be computed for these distributions. The thesis is aimed at proposing solutions to carry out Bayesian inference inside a mathematically coherent framework, focusing on the estimation of two quantities: log-normal quantiles (first part of the thesis) and conditioned expectations under a general log-normal linear mixed model (second part of the thesis). Moreover, in the latter section, a further investigation on a unit-level small area models is presented, considering the problem of estimating the well-known log-transformed Battese, Harter and Fuller model in the hierarchical Bayes context. Once the existence conditions for the moments of the target functionals posterior are proved, new strategies to specify prior distributions are suggested. Then, the frequentist properties of the deduced Bayes estimators and credible intervals are evaluated through accurate simulations studies: it resulted that the proposed methodologies improve the Bayesian estimates under naive prior settings and are satisfactorily competitive with the frequentist solutions available in the literature. To conclude, applications of the developed inferential strategies are illustrated on real datasets. The work is completed by the implementation of an R package named BayesLN which allows the users to easily carry out Bayesian inference for log-normal data

Mapping poverty at multiple geographical scales

Poverty mapping is a powerful tool to study the geography of poverty. The choice of the spatial resolution is central as poverty measures defined at a coarser level may mask their heterogeneity at finer levels. We introduce a small area multi-scale approach integrating survey and remote sensing data that leverages information at different spatial resolutions and accounts for hierarchical dependencies, preserving estimates coherence. We map poverty rates by proposing a Bayesian Beta-based model equipped with a new benchmarking algorithm that accounts for the double-bounded support. A simulation study shows the effectiveness of our proposal and an application on Bangladesh is discussed.Comment: 22 pages, 7 figure

The R package tipsae: tools for mapping proportions and indicators on the unit interval

The tipsae package implements a set of small area estimation tools for mapping proportions and indicators defined on the unit interval. It provides for small area models defined at area level, including the classical Beta regression, Zero and/or One Inflated Beta and Flexible Beta ones, possibly accounting for spatial and/or temporal dependency structures. The models, developed within a Bayesian framework, are estimated through Stan language, allowing fast estimation and customized parallel computing. The additional features of the tipsae package, such as diagnostics, visualization and exporting functions as well as variance smoothing and benchmarking functions, improve the user experience through the entire process of estimation, validation and outcome presentation. A Shiny application with a user-friendly interface further eases the implementation of Bayesian models for small area analysis

Extended beta models for poverty mapping. An application integrating survey and remote sensing data in Bangladesh

The paper targets the estimation of the poverty rate at the Upazila level in Bangladesh through the use of Demographic and Health Survey (DHS) data. Upazilas are administrative regions equivalent to counties or boroughs whose sample sizes are not large enough to provide reliable estimates or are even absent. We tackle this issue by proposing a small area estimation model complementing survey data with remote sensing information at the area level. We specify an Extended Beta mixed regression model within the Bayesian framework, allowing it to accommodate the peculiarities of sample data and to predict out-of-sample rates. In particular, it enables to include estimates equal to either 0 or 1 and to model the strong intra-cluster correlation. We aim at proposing a method that can be implemented by statistical offices as a routine. In this spirit, we consider a regularizing prior for coefficients rather than a model selection approach, to deal with a large number of auxiliary variables. We compare our methods with existing alternatives using a design-based simulation exercise and illustrate its potential with the motivating application

Critical evaluation of an intercalibration project focused on the definition of new multi-element soil reference materials (AMS-MO1 and AMS-ML1)

Soils are complex matrices and their geochemical investigation necessarily needs reliable Certified Reference Materials (CRMs), i.e. standards, to support analytical precision and accuracy. In particular, the definition of soil multi-element CRMs is particularly complex and involves an inter-laboratory program that employs numerous analytical techniques. In this study, we present the results of the inter-calibration experiment focused on the certification of two new soil standards named AMS-ML1 and AMS-MO1. The two soils developed on sandstone and serpentinite parent materials, respectively. The experiment involved numerous laboratories and focused on the evaluation of soil physicochemical parameters and geochemical analyses of major and trace elements by X-ray fluorescence (XRF) and Inductive Coupled Plasma techniques (ICP-OES and ICP-MS). The data was statistically elaborated. Three levels of repeatability and accuracy in function of the different analytical methods and instrumentation equipment was observed. The statistical evaluation of the results obtained by ICP-OES on Aqua Regia extracts (i.e., Lilliefors test for normally, Grubbs test for outliers, Cochran test for outliers in variances and ANOVA) allowed to computed some certified values for the two proposed soil standards. This preliminary study will represent the first step of a more thorough intercalibration ring-test involving a higher number of laboratories, in order to propose the investigated matrices as CRMs

The Italian Rare Pancreatic Exocrine Cancer Initiative

INTRODUCTION: Exocrine pancreatic cancers include common type pancreatic ductal adenocarcinoma and cystic neoplasms, which account for 85% and 10% of cases, respectively. The remaining 5% are rare histotypes, comprising adenosquamous carcinoma, acinar cell carcinoma, signet ring cell carcinoma, medullary carcinoma, pancreatoblastoma, hepatoid carcinoma, undifferentiated carcinoma and its variant with osteoclast-like giant cells, solid pseudopapillary carcinoma, and carcinosarcoma. Due to their low incidence, little knowledge is available on their clinical and molecular features as well as on treatment choices. The national initiative presented here aims at the molecular characterization of series of rare histotypes for which therapeutic and follow-up data are available. METHODS: A nationwide Italian Rare Pancreatic Cancer (IRaPaCa) task force whose first initiative is a multicentric retrospective study involving 21 Italian cancer centers to retrieve histologic material and clinical and treatment data of at least 100 patients with rare exocrine pancreatic cancers has been created. After histologic revision by a panel of expert pathologists, DNA and RNA from paraffin tissues will be investigated by next-generation sequencing using molecular pathway-oriented and immune-oriented mutational and expression profiling panels constructed availing of the information from the International Cancer Genome Consortium. Bioinformatic analysis of data will drive validation studies by immunohistochemistry and in situ hybridization, as well as nanostring assays. CONCLUSIONS: We expect to gather novel data on rare pancreatic cancer types that will be useful to inform the design of therapeutic choices

The Italian Legal Order and the Making of a National Cultural Identity

The chapter explores the variety of regulatory techniques and processes through which Italian law has tried to shape Italian cultural identity. Although the chapter aims to provide an account of the evolution of such techniques and processes, the historical perspective is also used to understand the current situation and to reflect on possible future developments. The underlying thesis of this research is that the shaping of Italian cultural identity over the last 50 years encapsulates a dialectic between unity and pluralism. Within such overall framework, the investigation discusses the political and administrative measures adopted in three different groups according to sector: (1) art, cultural heritage, and media; (2) education; and (3) language. Study of these sectors shows that the Italian legal order has not always been successful in guiding cultural processes. More often than not it has been content to support them or to attempt to contain them, leaving it to developments in society to limit the scope of regulation and not the revers

L'ordinamento giuridico e la costruzione dell'identità culturale italiana

Sommario: 1. Le domande e il metodo dell’indagine. 2. L’arte, il patrimonio culturale e i media. 2.1 L’arte e il patrimonio culturale. 2.2 La dialettica tra omologazione e diversità culturale. 2.3 La dialettica centro-autonomie. 2.4 I mass media. 3. La lingua. 3.1 La rilevanza giuridica della lingua. 3.2 Un insieme di tensioni. 3.3 La lingua come fattore di integrazione. 3.4 La posizione giuridica delle comunità linguistiche minoritarie. 3.5. L’apertura europea e globale del sistema amministrativo. 3.6 Le trasformazioni del linguaggio delle pubbliche amministrazioni. 4. L’istruzione. 4.1 L’istruzione come pilastro dell’identità nazionale. 4.2 Le tendenze recenti. 4.3 L’istruzione e il mercato. 4.4 La dimensione europea. 5. Conclusioni