An Extension of the DgLARS Method to High-Dimensional Relative Risk Regression Models

In recent years, clinical studies, where patients are routinely screened for many genomic features, are becoming more common. The general aim of such studies is to find genomic signatures useful for treatment decisions and the development of new treatments. However, genomic data are typically noisy and high dimensional, not rarely outstripping the number of patients included in the study. For this reason, sparse estimators are usually used in the study of high-dimensional survival data. In this paper, we propose an extension of the differential geometric least angle regression method to high-dimensional relative risk regression models.

Locomotor and antidepressant-like effects of 5-HT(1A) agonist LY 228729 in prenatally benzodiazepine-exposed rats.

Locomotor activity and antidepressant-like effect in the forced swim test (FST) of 5-HT(1A) agonist LY 228729 were investigated in adult rats prenatally exposed at doses of diazepam (DZ) and alprazolam (ALP) which induce persistent downregulation of GABA/ benzodiazepine (BZ) receptors. Prenatal exposure to ALP and DZ did not modify the efficacy of subchronic LY 228729 to decrease immobility time in the FST. Prenatal DZ and ALP potentiated the facilitatory effect of subchronic LY 228729 on locomotor activity; prenatal DZ was more effective than prenatal ALP. Moreover, prenatal DZ increased stereotypic movements induced by LY 228729. These data suggest that the persistent downregulation of GA…

Genetic Network construction in CML gene expression profile data analysis

Aim of this paper is to define a new statistical framework to identify central modules in Gaussian Graphical Models (GGMs) estimated by gene expression data measured on a sample of patients with negative molecular response to imatinib. A central module is defined as a module of a GGM which contains genes that are defined differentially expressed.

Using R via PHP for Teaching Purposes: R-php

This paper deals with the R-php statistical software, that is an environment for statistical analysis, freely accessible and attainable through the World Wide Web, based on R. Indeed, this software uses, as "engine" for statistical analyses, R via PHP and its design has been inspired by a paper of de Leeuw (1997). R-php is based on two modules: a base module and a point-and-click module. R-php base allows the simple editing of R code in a form. R-php point-and-click allows some statistical analyses by means of a graphical user interface (GUI): then, to use this module it is not necessary for the user to know the R environment, but all the allowed analyses can be performed by using the compu…

Long-lasting handling affects behavioural reactivity in adult rats of both sexes prenatally exposed to diazepam

Environmental stressors can substantially affect the adaptive response of rats to novelty in a sexually dimorphic manner. Gender-related differences are also observed in neurochemical and behavioural patterns of adult rats following prenatal exposure to diazepam (DZ). In the present study the behavioural reactivity to novelty is investigated in open field (OF) and in acoustic startle reflex (ASR) tests, in non handled (NH), short-lasting handled (SLH) and long-lasting handled (LLH) adult male and female rats prenatally exposed to DZ. A single daily s.c. injection of DZ (1.5 mg/kg) over gestation days 14-20 decreases GABA/BDZ receptor function in both sexes, as shown by the decreased electro…

On the accuracy of three statistical softwares

In this paper we compare the accuracy of three packages that are commonly used for statistical calculations: Excel of Microsoft, version XP Edition 2003, Statistica of Statsoft, version 6, and R, an open-source free software, available on the web, version 1.9.0. To assess the accuracy of each software in different statistical areas, we are going to use benchmarks expressly developed for this aim. The obtained results show a superiority of R in comparison with the other two softwares.

An efficient algorithm to estimate the sparse group structure of an high-dimensional generalized linear model

Massive regression is one of the new frontiers of computational statistics. In this paper we propose a generalization of the group least angle regression method based on the differential geometrical structure of a generalized linear model specified by a fixed and known group structure of the predictors. An efficient algorithm is also proposed to compute the proposed solution curve.

Di un nuovo coefficiente per la corretta misura dell'associazione in tabelle dicotomiche e in tabelle di contingenza

A new index for measuring association between categorized variables

The Analysis of Auxological Data by Means of Nonlinear Multivariate Growth Curves

In this paper we treat the problem to analyse a data set constituted by multivariate growth curves for different subjects; thus in this context we deal with 3-way data tables. Nevertheless, it is not possible using factorial techniques proposed to deal with 3-way data matrices, because the observations are generally not equally spaced; moreover a multilevel approach founded on polynomial models is not suitable to deal with intrinsic nonlinear models. We propose a non-factorial technique to analyse auxological data sets using an intrinsic nonlinear multivariate growth model with autocorrelated errors. The application to a real data set of growing children gave easily interpretable results.

A differential-geometric approach to generalized linear models with grouped predictors

We propose an extension of the differential-geometric least angle regression method to perform sparse group inference in a generalized linear model. An efficient algorithm is proposed to compute the solution curve. The proposed group differential-geometric least angle regression method has important properties that distinguish it from the group lasso. First, its solution curve is based on the invariance properties of a generalized linear model. Second, it adds groups of variables based on a group equiangularity condition, which is shown to be related to score statistics. An adaptive version, which includes weights based on the Kullback-Leibler divergence, improves its variable selection fea…

Differential geometric least angle regression: a differential geometric approach to sparse generalized linear models

Summary Sparsity is an essential feature of many contemporary data problems. Remote sensing, various forms of automated screening and other high throughput measurement devices collect a large amount of information, typically about few independent statistical subjects or units. In certain cases it is reasonable to assume that the underlying process generating the data is itself sparse, in the sense that only a few of the measured variables are involved in the process. We propose an explicit method of monotonically decreasing sparsity for outcomes that can be modelled by an exponential family. In our approach we generalize the equiangular condition in a generalized linear model. Although the …

Modelli lineari e non lineari in R

A Statistical Calibration Method based on Non-Linear Mixed Model for Affymetrix Probe Level Data

Gene expression microarrays allow a researcher to measure the simultaneous response of thousands of genes to external conditions. Affymetrix GeneChipr expression array technology has become a standard tool in medical research. Anyway, a preprocessing step is usually necessary in order to obtain a gene expression measure. Aim of this paper is to propose a calibration method to estimate the nominal concentration based on a non-linear mixed model. This method is an enhancement of a method proposed in Mineo et al. (2006). The relationship between raw intensities and concentration is obtained by using the Langmuir isotherm theory.

Estimation of sparse generalized linear models: the dglars package

dglars is a public available R package that implements the method proposed in Augugliaro, Mineo and Wit (2013) developed to study the sparse structure of a generalized linear model. This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method (LARS). The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve; specifically a predictor-corrector algorithm and a cyclic coordinate descent algorithm.

Multidimensional scaling and stock location assignment in a warehouse: an application

By means of an application, in the present paper, the suitability of a multivariate statistical methodology, as multidimensional scaling (MDS), to solve an optimization problem is shown. In particular, considering the stock location assignment problem in the warehouse of a supermarket chain, the solution gained by applying MDS to a set of seven variables is compared with the one obtainable by considering the usual techniques applied in this context. A wide discussion of results is reported. Copyright © 1999 John Wiley & Sons, Ltd.

Differential expression of specific microRNA and their targets in acute myeloid leukemia

Acute myeloid leukemia (AML) the most common acute leukemia in adults is characterized by various cytogenetic and molecular abnormalities. However, the genetic etiology of the disease is not yet fully understood. MicroRNAs (miRNA) are small noncoding RNAs which regulate the expression of target mRNAs both at transcriptional and translational level. In recent years, miRNAs have been identified as a novel mechanism in gene regulation, which show variable expression during myeloid differentiation. We studied miRNA expression of leukemic blasts of 29 cases of newly diagnosed and genetically defined AML using quantitative reverse transcription polymerase chain reaction (RT-PCR) for 365 human miR…

Organic farming: Territorial analysis and economic revival of organic agriculture – Analysis of select farms in sicily

All rights reserved.Organic farming represents one of the most distinctive phenomena among those characterizing the evolution of the Italian primary sector over the past two decades, especially in Sicily. In recent years, the Sicilian organic sector has come to prominence for the increase in both size and number of organic farms, which has allowed our country to rank among the foremost in this category at the international scale. The aim of this paper is to demonstrate how organic farming may contribute to the economic revival of Sicilian agriculture, not only from an exquisitely economic standpoint, but also in terms of sustainable development and environmental protection. The latter two p…

A new proposal for microarray background correction by means of a GLMM

La tecnologia microarray ha il grosso pregio di misurare simultaneamente il livello di espressione di migliaia di geni. All’elevata quantità d’informazione fornita da un singolo chip si contrappone la necessità di un adeguato pretrattamento dei dati grezzi al fine di ottenere una misura “affidabile” del livello di espressione genetico. Scopo del lavoro è analizzare, attraverso un modello lineare generalizzato misto, il legame esistente fra il livello d’intensità osservato ed il livello di concentrazione, attraverso l’utilizzo degli esperimenti Spike-In forniti dall’Affymetrix. Si propone, quindi, un nuovo metodo per la correzione del background.

Effects of 8-OH-DPAT on open field performance of young and aged rats prenatally exposed to diazepam: a tool to rveal 5-HT1a receptor function

Central GABAergic and serotoninergic systems interact with one another and are implicated in controlling different behaviours. A gentle early long-lasting handling can prevent the deficits in locomotion and exploration in open field (O.F.) in 3-month-old male rats prenatally exposed to diazepam (DZ). Purpose of this study was to extend the research to older handled rats prenatally exposed to DZ and to assess the activity of 5-HT1A receptors (Rs), evaluating the performance in O.F. at 3 and 18 months of age following 8-OH-DPAT administration. A single daily s.c. injection of DZ (1.5 mg/kg) from gestation day 14 to gestation day 20 induced in aged, but not in young rats, a decrease in total d…

Statistical Analysis of the Gene Expression Profile in Patients with Chronic Myeloid Leukemia and Innately Resistant to Imatinib

ℓ1-Penalized Methods in High-Dimensional Gaussian Markov Random Fields

In the last 20 years, we have witnessed the dramatic development of new data acquisition technologies allowing to collect massive amount of data with relatively low cost. is new feature leads Donoho to define the twenty-first century as the century of data. A major characteristic of this modern data set is that the number of measured variables is larger than the sample size; the word high-dimensional data analysis is referred to the statistical methods developed to make inference with this new kind of data. This chapter is devoted to the study of some of the most recent ℓ1-penalized methods proposed in the literature to make sparse inference in a Gaussian Markov random field (GMRF) defined …

Marketing strategy, social responsibility, and value chain in the agri-food system

The agri-food sector has changed significantly over the years, moving from a simple production system to a more and more industrialized one. For agents/operators involved in this sector, ensuring product quality and environmental externalities has become the key point to gaining a competitive advantage. In this context, corporate social responsibility (CSR) fits perfectly. This study analyzes the influence of CSR practices on the economic performance of a random sample of 130 agri-food companies in Italy. The results of an analysis of multiple linear regression models show that the economic performance (measured through value added and income) of agri-food enterprises seems to be influenced…

A basic graphical user interface: R-interactive

An enhancement of the plaid model algorithm

Microarrays have become a standard tool for studying gene functions. For example, we can investigate if a subset of genes shows a coherent expression pattern under different conditions. The plaid model, a model-based biclustering method, can be used to incorporate the addiction structure used for the microarray experiment. In this paper we describe an enhancement for the plaid model algorithm based on the theory of the false discovery rate.

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.

Le Curve Normali di Ordine p come Distribuzione Generale degli Errori Accidentali: Uno Strumento Software per il loro Utilizzo

A software tool via web for the statistical data analysis; R-php

The spread of Internet and the growing demand of services from the web users have changed and are still changing the way to organize the work or the study. Nowadays, the main part of information and many services are on the web and the software is going toward the same direction: in fact, the use of software implemented via web is ever-increasing, with a client-server logic that enables the “centralized” use of software installed on a server. In this paper we describe the Structure and the running of R-php, an environment for statistical analysis, freely accessible and attainable through the World Wide Web, based on the statistical environment R. R-php is based on two modules: a base module…

Statistical Multivariate Techniques for the Stock Location Assignment Problem

In previous papers we proposed to apply multivariate statistical methodologies, like Multidimensional Scaling (MDS) and Seriation to the stock location assignment problem of a warehouse, often solved by considering the Cube per Order Index (COI). In this paper we compare the results by MDS, Seriation, a COI based method and the Maximum Path criterion, considering the data of a whole year of a Sicilian supermarket chain warehouse. The comparison is based on the simulated times to satisfy a sample of real orders.

Reversal of prenatal diazepam-induced deficit in a spatial-object learning task by brief, periodic maternal separation in adult rats.

In the rat, prenatal exposure to diazepam (DZ) induces a permanent reduction in GABA/BZ receptor (R) function and behavioural abnormalities. Environmental modifications during early stages of life can influence brain development and induce neurobiological and behavioural changes throughout adulthood. Indeed, a subtle, periodic, postnatal manipulation increases GABA/BZ R activity and produces facilitatory effects on neuroendocrine and behavioural responses. We here investigated the impact of prenatal treatment with DZ on learning performance in adult 3- and 8-month-old male rats and the influence of a brief, periodic maternal separation on the effects exerted by prenatal DZ exposure. Learnin…

SPARSE INFERENCE IN COVARIATE ADJUSTED CENSORED GAUSSIAN GRAPHICAL MODELS

The covariate adjusted glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.

A New Approach to the Stock Location Assignment Problem by Multidimensional Scaling and Seriation

The problem of the best stock location assignment in a warehouse has a fundamental role while optimising picking activities. In the present paper, this problem has been faced by considering seven variables to compute similarity between items. In this context, the problem of the choice of the most adequate similarity (or dissimilarity) measure between units while applying Multidimensional Scaling (MDS), has been examined. Besides the right metric, the possibility of applying a Seriation algorithm has been also considered. By using both MDS and seriation not just a single target can be considered, but we are able to manage with a plenty of variables; on the contrary with techniques used in li…

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 studi…

A new method to "clean up" ultra high-frequency data

In the applied econometrics, the availability of ultra high-frequency databases is having an important impact on the research market microstructure theory. The ultra high-frequency databases contain detailed reports of all the financial market activity information which is available. However, ultra high-frequency databases cannot be directly used. On one hand recording mistakes can be present, on the other hand missing information has to be inferred from the available data. In this paper, we propose a simple method in order to clean up the ultra high-frequency data from possible errors and we examine the method efficacy when we analyze data by using an autoregressive conditional duration (A…

A methodological approach for assessing businness investments in renewable resources from a circular economy perspective

Abstract In this paper, we have analyzed a feasibility project for the realization of a biogas plant at a company in the viticulture sector located in south-central Sicily. Using engineering formulas, we identified the electrical power that the plant could produce using waste products created by the vineyard itself, examined the new and interesting opportunities that have arisen with the encouragement and development of biogas production in Italy, and then assessed the economic feasibility of the investment itself, considering an investment scheme of total capital self-financing. The possibility of using wastes from wine production comes from an in-depth study of the circular economy, that …

Modelling the background correction in microarray data analysis

Microarray technology has been adopted in many areas of biomedical research for quantitative and highly parallel measurements of gene expressions. In this field, the high density oligonucleotide microarray technology is the most used platform; in this platform oligonucleotides of 25 base pairs are used as probe genes. Two types of probes are considered: perfect match (PM) and mismatch (MM) probes. In theory, MM probes are used to quantify and remove two types of error: optical noise and non specific binding. The correction of these two types of error is known as background correction. Preprocessing is an essential step of the analysis in which the intensity, read from each probe, is manipul…

A computational method to estimate sparse multiple Gaussian graphical models

In recent years several researchers have proposed the use of the Gaussian graphical model defined on a high dimensional setting to explore the dependence relationships between random variables. Standard methods, usually proposed in literature, are based on the use of a specific penalty function, such as the L1-penalty function. In this paper our aim is to estimate and compare two or more Gaussian graphical models defined in a high dimensional setting. In order to accomplish our aim, we propose a new computational method, based on glasso method, which lets us to extend the notion of p-value.

Using differential LARS algorithm to study the expression profile of a sample of patients with latex-fruit syndrome

Natural rubber latex IgE-mediated hypersensitivity is one of the most important health problems in allergy during recent years. The prevalence of individuals allergic to latex shows an associated hypersensitivity to some plant-derived foods, especially freshly consumed fruit. This association of latex allergy and allergy to plant-derived foods is called latex-fruit syndrome. The aim of this study is to use the differential geometric generalization of the LARS algorithm to identify candidate genes that may be associated with the pathogenesis of allergy to latex or vegetable food.

Penalized linear discriminant analysis and Discrete AdaBoost to distinguish human hair metal profiles: The case of adolescents residing near Mt. Etna

The research focus of the present paper was twofold. First, we tried to document that human intake of trace elements is influenced by geological factors of the place of residence. Second, we showed that the elemental composition of human hair is a useful screening tool for assessing people's exposure to potentially toxic substances. For this purpose, we used samples of human hair from adolescents and applied two robust statistical approaches. Samples from two distinct geological and environmental sites were collected: the first one was characterized by the presence of the active volcano Mt. Etna (ETNA group) and the second one lithologically made up of sedimentary rocks (SIC group). Chemica…

Prenatal exposure to diazepam and alprazolam, but not to zolpidem, affects behavioural stress reactivity in handling-naïve and handling-habituated adult male rat progeny.

A gentle long-lasting handling produces persistent neurochemical and behavioural changes and attenuates the impairment in the behavioural reactivity to novelty induced by the prenatal exposure to diazepam (DZ) in adult male rat progeny. This study investigated the consequences of a late prenatal treatment with three GABA/BDZ R agonists (DZ) alprazolam (ALP) and zolpidem (ZOLP)), on different stress-related behavioural patterns, in non-handled (NH), short-lasting handled (SLH) and long-lasting handled (LLH) adult male rats exposed to forced swim test (FST), acoustic startle reflex (ASR) and Vogel test (VT). The effects on motor activity were evaluated in the open field and in the Skinner box…

Plaid model for microarray data: an enhancement of the pruning step

Microarrays have become a standard tool for studying gene functions. For example, we can investigate if a subset of genes shows a coherent expression pattern under different conditions. The plaid model, a model-based biclustering method, can be used to incorporate the addiction structure used for the microarray experiment. In this paper we describe an enhancement for the plaid model algorithm based on the theory of the false discovery rate.

Effects of 8-OH-DPAT on open field performance of young and aged rats prenatally exposed to diazepam: a tool to reveal 5-HT1A receptor function

Central GABAergic and serotoninergic systems interact with one another and are implicated in controlling different behaviours. A gentle early long-lasting handling can prevent the deficits in locomotion and exploration in open field (O.F.) in 3-month-old male rats prenatally exposed to diazepam (DZ). Purpose of this study was to extend the research to older handled rats prenatally exposed to DZ and to assess the activity of 5-HT1A receptors (Rs), evaluating the performance in O.F. at 3 and 18 months of age following 8-OH-DPAT administration. A single daily s.c. injection of DZ (1.5 mg/kg) from gestation day 14 to gestation day 20 induced in aged, but not in young rats, a decrease in total d…

Selecting the tuning parameter in penalized Gaussian graphical models

Penalized inference of Gaussian graphical models is a way to assess the conditional independence structure in multivariate problems. In this setting, the conditional independence structure, corresponding to a graph, is related to the choice of the tuning parameter, which determines the model complexity or degrees of freedom. There has been little research on the degrees of freedom for penalized Gaussian graphical models. In this paper, we propose an estimator of the degrees of freedom in $$\ell _1$$ -penalized Gaussian graphical models. Specifically, we derive an estimator inspired by the generalized information criterion and propose to use this estimator as the bias term for two informatio…

Analisi delle Strutture di Interdipendenza Correlativa e Associativa e della Variabilità Relativa di Variabili Statistiche Multiple

Different methods to clean up ultra high frequency data

Inferring networks from high-dimensional data with mixed variables

We present two methodologies to deal with high-dimensional data with mixed variables, the strongly decomposable graphical model and the regression-type graphical model. The first model is used to infer conditional independence graphs. The latter model is applied to compute the relative importance or contribution of each predictor to the response variables. Recently, penalized likelihood approaches have also been proposed to estimate graph structures. In a simulation study, we compare the performance of the strongly decomposable graphical model and the graphical lasso in terms of graph recovering. Five different graph structures are used to simulate the data: the banded graph, the cluster gr…

Economic development and agriculture: Managing protected areas and safeguarding the environment

Abstract The establishment of protected areas has been one of the most important interventions to protect biodiversity from the threat of human activities and in particular from the agricultural traditional activities where they have been restricted at the expense of the economy of the territory sparking in literature a heated debate between those who argue the these hinder the socio-economic development and on the other hand are those who argue that is able to advance social welfare. On the basis of these considerations, the weight of agricultural sector of a country is highly linked to the percentage of protected areas even though the trend of the weight of agriculture in the overall econ…

NMDA-GABA interactions in an animal model of behaviour: a gating mechanism from motivation toward psychotic-like symptoms

We studied the effects of desipramine, alprazolam, muscimol and dizocilpine (MK-801) (alone or associated with desipramine) in the forced swimming test in rats after long-lasting termination of chronic exposure to vehicle and pentylenetetrazol. Sensitisation with pentylenetetrazol was ineffective in changing immobility time in the forced swimming test compared to vehicle treatment; pentylenetetrazol enhanced the anti-immobility effect of desipramine, abolished the anti-immobility effect of alprazolam and did not affect the anti-immobility effect of muscimol. MK-801 at the dose that did not modify immobility time in vehicle-treated rats and in pentylenetetrazol-treated animals strongly poten…

Applying differential geometric LARS algorithm to ultra-high dimensional feature space

Variable selection is fundamental in high-dimensional statistical modeling. Many techniques to select relevant variables in generalized linear models are based on a penalized likelihood approach. In a recent paper, Fan and Lv (2008) proposed a sure independent screening (SIS) method to select relevant variables in a linear regression model defined on a ultrahigh dimensional feature space. Aim of this paper is to define a generalization of the SIS method for generalized linear models based on a differential geometric approach.

dglars: An R Package to Estimate Sparse Generalized Linear Models

dglars is a publicly available R package that implements the method proposed in Augugliaro, Mineo, and Wit (2013), developed to study the sparse structure of a generalized linear model. This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method proposed in Efron, Hastie, Johnstone, and Tibshirani (2004). The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve: a predictor-corrector algorithm, proposed in Augugliaro et al. (2013), and a cyclic coordinate descent algorithm, proposed in Augugliaro, Mineo, and Wit (2012). The latter algorithm, as shown here, is significan…

A statistical calibration model for Affymetrix probe level data

Gene expression microarrays allow a researcher to measure the simultaneous response of thousands of genes to external conditions. Affymetrix GeneChip{ $Ⓡ$} expression array technology has become a standard tool in medical research. Anyway, a preprocessing step is usually necessary in order to obtain a gene expression measure. Aim of this paper is to propose a calibration method to estimate the nominal concentration based on a nonlinear mixed model. This method is an enhancement of a method proposed in Mineo et al. (2006). The relationship between raw intensities and concentration is obtained by using the Langmuir isotherm theory.

Le curve normali di ordine p come distribuzione degli errori accidentali: uno strumento software per il loro utilizzo

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 associatio…

Using the dglars Package to Estimate a Sparse Generalized Linear Model

dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method. The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve. dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, call…

Agritourism and local development: A methodology for assessing the role of public contributions in the creation of competitive advantage

Abstract Agriculture has been an economic mainstay of countries throughout history. Recently, its importance and essential role in local and regional growth and development have also received due acknowledgment. However, agritourism entrepreneurs often lack the necessary means, when relying only on their own funds alone. For these reasons, targeted aid measures are provided at the regional, national and European levels, provided they fulfill specified subjective and objective eligibility criteria. This investigation aims at understanding the rationale, if any, according to which the Public Administration allots such contributions. To this end, a two-tiered analysis was conducted on the data…

Identifying modularity structure of a genetic network in gene expression profile data

Aim of this paper is to define a new statistical framework to identify central modules in Gaussian Graphical Models (GGMs) estimated by gene expression data measured on a sample of patients with negative molecular response to Imatinib. Imanitib is a drug used to treat certain types of cancer that in many statistical studies has been reported to have a significant clinical effect on chronic myeloid leukemia (CML) in chronic phase as well as in blast crisis. For central module in a GGM we intend a module containing genes that are defined differently expressed.

Using differential geometric LARS algorithm to study the expression profile of a sample of patients with latex-fruit syndrome

Natural rubber latex IgE-mediated hypersensitivity is one of the most important health problems in allergy during recent years. The prevalence of individuals allergic to latex shows an associated hypersensitivity to some plant-derived foods, especially freshly consumed fruit. This association of latex allergy and allergy to plant-derived foods is called latex-fruit syndrome. The aim of this study is to use the differential geometric generalization of the LARS algorithm to identify candidate genes that may be associated with the pathogenesis of allergy to latex or vegetable.

Food consumer models: The case of the responsible consumer

The profile of the responsible consumer, that is, an individual whose purchases strive to satisfy altruistic aims above and beyond one’s merely personal consumer necessities, is closely correlated to the one’s socio-economic conditions. All subjective aspects considered, the correlation between responsible consumption in the agri-food sector and the level of education of the individual was studied herein by way of a statistical survey, conducted on a sample of 108 individuals. Likewise, the correlation between the level of responsible consumption and the average monthly expenditures was also elucidated. The study was carried out using the statistical software environment R and the resul…

A STATISTICAL SOFTWARE TOOL VIA WEB: R-PHP

Using R via PHP: R-php

This paper deals with the R-php statistical software, that is an environment for statistical analysis, freely accessible and attainable through the World Wide Web, based on R. Indeed, this software uses, as "engine" for statistical analyses, R via PHP and its design has been inspired by a paper of de Leeuw (1997). R-php is based on two modules: a base module and a point-and-click module. R-php base allows the simple editing of R code in a form. R-php point-and-click allows some statistical analyses by means of a graphical user interface (GUI): then, to use this module it is not necessary for the user to know the R environment, but all the allowed analyses can be performed by using the compu…

A software tool via web for the statistical data analysis

The spread of Internet and the growing demand of services from the web users have changed and are still changing the way to organize the work or tthe study. Nowadays, the main part of information and many services are on the web and the software is going toward the same direction: in fact, the use of software implemented via web is ever-increasing, with a client-server logic that enables the "centralized" use of software installed on a server. In this paper we describe the structure and the running of R-php, an environment for statistical analysis, freely accessible and attainable through the World Wide Web, based on the statistical environment R. R-php is based on two modules: a base modul…

Corrigendum to “Effects of 8-OH-DPAT on open field performance of young and aged rats prenatally exposed to diazepam: a tool to reveal 5-HT1A receptor function”