A Software Tool for the Exponential Power Distribution: The normalp Package

In this paper we present the normalp package, a package for the statistical environment R that has a set of tools for dealing with the exponential power distribution. In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo-random numbers from the same distribution. Moreover, methods concerning the estimation of the distribution parameters are described and implemented. It is also possible to estimate linear regression models when we assume the random errors distributed according to an exponential power distribution. A set of functions is designed to perform simulation studies to see the suitability of the estimators used. Some examples of use of this package are provided.

Extending Functional kriging to a multivariate context

Environmental data usually have a spatio-temporal structure; pollutant concentrations, for example, are recorded along time and space. Generalized Additive Models (GAMs) represent a suitable tool to model spatial and/or temporal trends of this kind of data, that can be treated as functional, although they are collected as discrete observations. Frequently, the attention is focused on the prediction of a single pollutant at an unmonitored site and, at this aim, we extend kriging for functional data to a multivariate context by exploiting the correlation with the other pollutants. In particular, we propose two procedures: the first one (FKED) combines the regression of a variable (pollutant), of primary interest on the other variables, with functional kriging of the regression residuals; the second one (FCK) is based on linear unbiased prediction of spatially correlated multivariate random processes. The performance of the two proposed procedures is assessed by cross validation; data recorded during a year (2011) from the monitoring network of the state of California (USA) are considered

A Software Tool for the Exponential Power Distribution: The normalp Package

In this paper we present the normalp package, a package for the statistical environment R that has a set of tools for dealing with the exponential power distribution. In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo\u2013random numbers from the same distribution. Moreover, methods concerning the estimation of the distribution parameters are described and implemented. It is also possible to estimate linear regression models when we assume the random errors distributed according to an exponential power distribution. A set of functions is designed to perform simulation studies to see the suitability of the estimators used. Some examples of use of this package are provided

GAMs and functional kriging for air quality data

Data having spatio-temporal structure are often observed in environmental sciences. They may be considered as discrete observations from curves along time and/or space and treated as functional. Generalized Additive Models (GAMs) represent a useful tool for modelling, for example, as pollutant concentrations describing their spatial and/or temporal trends.Usually, the prediction of a curve at an unmonitored site is necessary and, with this aim, we extend kriging for functional data to a multivariate context. Moreover, even if we are interested only in predicting a single pollutant, such as PM10, the estimation can be improved exploiting its correlation with the other pollutants. Cross validation is used to test the performance of the proposed procedure

Eteroscedasticita' e non normalita' degli errori nell'analisi della regressione

Dottorato di ricerca in statistica computazionale ed applicazioniConsiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro,7, Rome; Biblioteca Nazionale Centrale - P.za Cavalleggeri, 1, Florence / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

AN ASSOCIATION INDEX FOR RECTANGULAR CONTINGENCY TABLES WITH ORDERED/UNORDERED VARIABLES

In a previous work, Mineo and Ruggieri (2005) introduce a new index to measure the association in square contingency tables; in this paper such an index is extended to rectangular tables, preserving the same properties. The considered domain includes all the contingency tables with equal n (the total number of observations), since the tables of maximum dependence, useful for computing the denominator of the proposed index, belong to it. The main findings, which prove the effectiveness of the proposed measure, are presented. In particular, the new measure assumes values in the range [-1,+1], taking value zero in tables with distributive independence and positive/negative values if association/dissociation occurs. The importance of the sign for an association index computed on rectangular contingency tables and the need to recognize association from dissociation is explained. It is also shown as the absolute value of the new measure is invariant to permutation of rows and/or columns of the observed table. Finally, some relevant examples and case studies are reported

Air quality indices: A review

National directives on air quality oblige nations to monitor and report on their air quality, allowing the public to be informed on the ambient pollution levels. The last is the reason for the always increasing interest, demonstrated by the number of publications on this topic in recent years, in air quality/pollution indices: since the concentration of individual pollutants can be confusing, concentration measurements are conveniently transformed in terms of an air quality index. In this way, complex situations are summarized in a single figure, letting comparisons in time and space be possible. In this paper we will give an overview about the Air Quality/Pollution Indices proposed in literature and/or adopted by countries, trying also to categorize them into homogeneous groups. For the classification different approaches can be followed. Since in real life exposure to mixtures of chemicals occurs, with additive, synergistic or antagonistic effects, here we will distinguish between indices that consider the conjoint effect of pollutants and indices only based on the actual most dangerous pollutant. This brief review on air pollution indices shows, on one side, the wide interest in the problem, on the other, the lack of a common strategy which allows to compare the state of the air for cities that follow different directives. The main differences between the indices will be also described. © 2010 Springer Science+Business Media B.V

A new index to measure association between categorical and ordinal variables

In this paper a new index to analyse the dependence between categorical variables is presented and is compared to other measures of association, mainly based on the X2 Pearson’s statistic. The new index is compared to well-known measures of cograduation, as well. To restrict our comparisons, the domain we consider includes all the square contingency tables belonging to the same Fréchet class, that is all the contingency tables in which the marginal frequencies are given as fixed in both characters. Anyway, the new index is good even if there are no constrain on the marginal distributions, but only a constrain on n, the total of the observations

Comparing air quality indices aggregated by pollutant

In this paper a new aggregate Air Quality Index (AQI) useful for describing the global air pollution situation for a given area is proposed. The index, unlike most of currently used AQIs, takes into account the combined effects of all the considered pollutants to human health. Its good performance, tested by means of a simulation plan, is confirmed by a comparison with two other indices proposed in the literature, one of which is based on the Relative Risk of daily mortality, considering an application to real data

A BoD Composite Indicator to Measure the Italian “Sole 24 Ore” Quality of Life

The measure of Quality of Life (QoL) is still a topic widely discussed in literature. In Italy, the newspaper “Il Sole 24 Ore” publishes a famous ranking that highlights strong disparities among provinces. In this paper, “Il Sole 24 Ore” and BoD-DEA methods are compared in order to show how different types of normaliza- tion and aggregation significantly influence the results making these rankings very fragile and questionable