1,720,963 research outputs found
Validating Benfordness on contaminated data
No full textBenford's law is a mathematical model, very recurrent in practice for a wide variety of datasets, used to represent the frequencies of digits. A well-established usage of Benfordness statistical testing lies within investigations aimed to ascertain if balance sheet and income statement data are genuine. A typical, frustrating problem of Benfordness statistical tests on big, practical datasets is that they often provide p-valuessmaller than expected when the Benfordness null hypothesis is very realistic. A possible reason is that data are contaminated by some kind of noise. In this paper we propose the deconvolution approach to alleviate this issue, using both simulated and real data
Local binary regression with spherical predictors
Get PDFWe discuss local regression estimators when the predictor lies on the -dimensional sphere and the response is binary. Despite Di Marzio et al. (2018b), who introduce spherical kernel density classification, we build on the theory of local polynomial regression and local likelihood. Simulations and a real-data application illustrate the effectiveness of the proposals
Kernel density classification for spherical data
Get PDFClassifying observations coming from two different spherical populations by using a nonparametric method appears to be an unexplored field, although clearly worth to pursue. We propose some decision rules based on spherical kernel density estimation and we provide asymptotic L₂ properties. A real-data application using global climate data is finally discussed
A Statistical Tool as a Decision Support in Enterprise Financial Crisis
No full textThe recent reform of Italian Insolvency Law introduced new instruments aimed to restore companies in financial distress and potential in bankruptcy. In particular, the Article 182-bis restructuring agreements has been introduced by the Italian Civil Code to manage company crisis. The objective of this study is to underline the ability of seven specific accounting ratios and coefficients to predict the status of financial distress of the firms. We introduce a new formula that we call M-Index indicator, and then provide an empirical analysis through a sample of Italian listed companies collected from the Milan Stock Exchange in the period 2003–2012. The results of the empirical analysis validate the predictive accuracy power of our indicator
Effective Land-Use and Public Regional Planning in the Mining Industry: The Case of Abruzzo
No full textLand use patterns are the visible consequences of human intervention on the natural environment, especially with reference to mining activities for direct trade or subsequent manufacturing purposes. But the extractive industry and the activities of its supply chain have divergent interests related to the quantities of materials that can be extracted in compliance with the fundamental parameters of environmental sustainability. This is the main reason why mining activities are generally allowed only if public authorities issue the specific permits consistently with a specific long range plan. As the Italian legislation attributes this planning authority to regional governments, the present work aims to help to describe the socio-economic variables most affected by quarry extraction processes by referring to the case of Abruzzo (region of Central Italy). We also introduce a model for quantification of the quarry material requirements expressed by the economic operators of the same territory with a time horizon of 2020. To this end, we suggest the use of economic and statistical indicators, such as public investment on infrastructures, GDP growth, social housing policies, private building permits, to optimize the predicting power of the model as they represent reliable proxies of the demand of raw materials, in respect to the need to limit the impact on the environment
Nonparametric estimating equations for circular probability density functions and their derivatives
Get PDFWe propose estimating equations whose unknown parameters are the values taken by a circular density and its derivatives at a point. Specifically, we solve equations which relate local versions of population trigonometric moments with their sample counterparts. Major advantages of our approach are: higher order bias without asymptotic variance inflation, closed form for the estimators, and absence of numerical tasks. We also investigate situations where the observed data are dependent. Theoretical results along with simulation experiments are provided
Circular local likelihood
Get PDFWe introduce a class of local likelihood circular density estimators, which includes the kernel density estimator as a special case. The idea lies in optimizing a spatially weighted version of the log-likelihood function, where the logarithm of the density is locally approximated by a periodic polynomial. The use of von Mises density functions as weights reduces the computational burden. Also, we propose closed-form estimators which could form the basis of counterparts in the multidimensional Euclidean setting. Simulation results and a real data case study are used to evaluate the performance and illustrate the results
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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