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We study the problem of estimating a regression function when the predictor and/or the response are circular random variables in the presence of measurement errors. We propose estimators whose weight functions are deconvolution kernels defined according to the nature of the involved variables. We derive the asymptotic properties of the proposed estimators and consider possible generalizations and extensions. We provide some simulation results and a real data case study to illustrate and compare the proposed methods.

The aim of this study was to provide an updated meta-analysis assessing the therapeutic equivalence between follitropin alfa biosimilars and the reference medication in women undergoing assisted reproductive technologies (ART).The studies included in the analysis were pooled together in order to estimate the log odds ratio (OR) for binary outcomes and the mean difference (MD) for continuous outcomes along with the corresponding 95% confidence intervals (CI) by using a random effects model. The heterogeneity between the studies was evaluated with the Higgins and χNo differences were found concerning the number of oocytes retrieved at ovum pick-up, the primary endpoint recommended by the European Medicines Agency (EMA) (MD -0.04 CI [-0.78, 0.71], P=0.92). A significantly higher clinical pregnancy rate (OR 0.70 CI [0.53, 0.93], P=0.01) was observed in the reference product group in comparison to the biosimilar follitropin alfa, whereas no statistically significant differences were found for biochemical pregnancy rate, take home baby rate, total follitropin alfa dose, duration of stimulation, and ovarian hyperstimulation syndrome risk.The non-inferiority of biosimilar formulations in comparison to the reference product, with respect to number of oocytes retrieved at ovum pick-up, was shown.

The package implements nonparametric (smooth) regression for spherical data in , and is freely available from the Comprehensive Archive Network (CRAN), licensed under the MIT License. It can be use...

Until now the problem of estimating circular densities when data are observed with errors has been mainly treated by Fourier series methods. We propose kernel-based estimators exhibiting simple construction and easy implementation. Specifically, we consider three different approaches: the first one is based on the equivalence between kernel estimators using data corrupted with different levels of error. This proposal appears to be totally unexplored, despite its potential for application also in the Euclidean setting. The second approach relies on estimators whose weight functions are circular deconvolution kernels. Due to the periodicity of the involved densities, it requires ad hoc mathematical tools. Finally, the third one is based on the idea of correcting extra bias of kernel estimators which use contaminated data and is essentially an adaptation of the standard theory to the circular case. For all the proposed estimators, we derive asymptotic properties, provide some simulation results, and also discuss some possible generalizations and extensions. Real data case studies are also included.

Our contribution deals with the description and evaluation of a graphical user interface—called GEM—designed as a math quasi-experimental contest. The Gifted European Mathematicians (GEM) project was born from the recognition of the need for many European countries for highly qualified youngers in mathematics, science and technology. Conceived in the field of mathematics education, by and large, GEM is an e-learning platform developed to test and improve high-school students mathematical skills. The efficiency of this platform is evaluated by analyzing the competences of the experimental subjects involved after attending lessons and consulting the material.

Fluconazole is a bis-triazole agent used in the treatment of superficial and systemic fungal infections, with vaginal candidiasis being one of the commonest indications to fluconazole treatment. There is increasing concern regarding the teratogenic potential of fluconazole. The aim of this meta-analysis is to pool the literature data in order to evaluate the possible association between fluconazole exposure during pregnancy and birth defects. A total of nine studies were included in the meta-analysis. Results were expressed as odds ratios (OR) with 95 % confidence intervals (CI) and statistical heterogeneity between the studies was evaluated with Higgins index (I2) and Q-test (Q). A p-value

Recently published multicentre, randomized phase III studies suggested the therapeutic equivalence of biosimilar follitropin alpha medicaments compared to the reference product. The aim of this meta-analysis is to pool the results of the three phase III trials in order to provide an overall analysis about the clinical bioequivalence between biosimilars and the originator.The studies included in the analysis were pooled together in order to estimate the log odds ratio (OR) for binary outcomes and the weighted mean difference (WMD) for continuous outcomes along with the corresponding 95% confidence intervals (CI) by using a random effects model. The heterogeneity between the studies was evaluated with the Higgins and Chi-square tests.No differences were found in term of number of oocytes retrieved at ovum pick-up, the primary endpoint recommended by the European Medicines Agency. No statistical differences were also found for biochemical pregnancy rate, take home baby rate, total follitropin alpha dose, duration of stimulation, and OHSS risk. A significantly higher clinical pregnancy rate (Biosimilar follitropin alpha medicaments resulted comparable in comparison to the reference product with respect to the number of oocytes retrieved, that is the primary endpoint recommended by the European Medicines Agency .Further study is needed to evaluate the therapeutic bioequivalence between follitropin alpha biosimilar and the reference medication with respect to secondary endpoints.

We investigate the relation between the CEO gender and the performance of banks operating in the EMEA countries. There is a long debate about the risk adversity of the females sitting on the board of directors and the consequences this behavior leads to in terms of financial performance. We estimate a dynamic model from a panel of 101 EMEA banks over the period 2000–2016 by using the generalized method of moments. Our findings of a positive relation between a female CEO and the bank performance are supported by well known statistical tests.

We consider the problem of nonparametrically estimating a circular density from data contaminated by angular measurement errors. Specifically, we obtain a kernel-type estimator with weight functions that are reminiscent of deconvolution kernels. Here, differently from the Euclidean setting, discrete Fourier coefficients are involved rather than characteristic functions. We provide some simulation results along with a real data application.

There is convincing evidence that cigarette smoking can impair female reproductive potential. This meta-analysis updates the knowledge regarding the effects of cigarette smoking on clinical outcomes of assisted reproductive technologies (ART). Twenty-six studies were included in this meta-analysis. Results were expressed as odds ratios (OR) with 95% confidence intervals (CI) and statistical heterogeneity between the studies was evaluated with Higgins (I2), Breslow (τ2), Birge’s ratio (H2) indices and Chi-square test (χ2). A P-value

Classifying 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 L 2 properties. A real-data application using global climate data is finally discussed.

We discuss local regression estimators when the predictor lies on the d -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.

Local likelihood has been mainly developed from an asymptotic point of view, with little attention to finite sample size issues. The present paper provides simulation evidence of how likelihood density estimation practically performs from two points of view. First, we explore the impact of the normalization step of the final estimate, second we show the effectiveness of higher order fits in identifying modes present in the population when small sample sizes are available. We refer to circular data, nevertheless it is easily seen that our findings straightforwardly extend to the Euclidean setting, where they appear to be somehow new.

The conditional density offers the most informative summary of the relationship between explanatory and response variables. We need to estimate it in place of the simple conditional mean when its shape is not well-behaved. A motivation for estimating conditional densities, specific to the circular setting, lies in the fact that a natural alternative of it, like quantile regression, could be considered problematic because circular quantiles are not rotationally equivariant. We treat conditional density estimation as a local polynomial fitting problem as proposed by Fan et al. [Estimation of conditional densities and sensitivity measures in nonlinear dynamical systems. Biometrika. 1996;83:189–206] in the Euclidean setting, and discuss a class of estimators in the cases when the conditioning variable is either circular or linear. Asymptotic properties for some members of the proposed class are derived. The effectiveness of the methods for finite sample sizes is illustrated by simulation experiments a...

The 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.

Land 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.

Circular data occur when the sample space is the unit circle. The peculiarity of a circular measurement scale is that its beginning and its end coincide. After both an origin and an orientation have been chosen, a circular observation can be measured, in radians, by an angle θ ∈ [−pi, pi). Circular data often arise in biology (migration paths, flight directions of animals), meteorology (wind and marine current directions), and geology (orientations of joints and faults, landforms, oriented stones). For comprehensive accounts see, for example, [9] and [1].

We 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.

We 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.

The present study offers a meta-analysis of published randomized controlled trials (RCTs) evaluating the outcomes of in vitro fertilization (IVF) cycles using corifollitropin alfa for controlled ovarian stimulation (COS) in comparison with daily recombinant FSH (rFSH). The study examined seven RCTs including 2138 patients receiving corifollitropin alfa and 1788 women receiving daily rFSH for COS. As a novel aspect, this meta-analysis included two specific subpopulations of IVF patients, i.e. egg donors and poor responders. There were no significant differences between corifollitropin alfa and rFSH with respect to the majority of the clinical parameters considered, and comparable were the outcomes in terms of live birth rate, ongoing pregnancy rate, and clinical pregnancy rate. Women receiving corifollitropin alfa had a significantly higher number of metaphase II oocytes at ovum pick-up, and number of formed embryos, in comparison to rFSH. The risk of cycle cancellation due to overstimulation was significantly higher in the corifollitropin alfa group. Ovarian hyperstimulation syndrome (OHSS) incidence was statistically comparable between patients receiving long lasting or daily rFSH. Nevertheless, in view of the fact that corifollitropin alfa resulted in a higher number of metaphase II oocytes collected and a higher number of cycles cancelled due to overstimulation, corifollitropin alfa should be cautiously considered in women with the potential of being hyper responders.