On the level-slope-curvature effect in yield curves and eventual total positivity

Principal components analysis has become widely used in a variety of fields. In finance and, more specifically, in the theory of interest rate derivative modeling, its use has been pioneered by Litterman and Scheinkman [J. Fixed Income, 1 (1991), pp. 54--61]. Their key finding was that a few components explain most of the variance of treasury zero-coupon rates and that the first three eigenvectors represent level, slope, and curvature (LSC) changes on the curve. This result has been, since then, observed in various markets. Over the years, there have been several attempts at modeling correlation matrices displaying the observed effects as well as trying to understand what properties of those matrices are responsible for them. Using recent results of the theory of total positiveness [O. Kushel, Matrices with Totally Positive Powers and Their Generalizations, 2014], we characterize these matrices and, as an application, we shed light on the critique to the methodology raised by Lekkos [J. Derivatives, 8 (2000), pp. 72--83].Fil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Tolmasky, Carlos F.. University of Minnesota; Estados Unido

On the existence of the weighted bridge penalized Gaussian likelihood precision matrix estimator

We establish a necessary and sufficient condition for the existence of the precision matrix estimator obtained by minimizing the negative Gaussian log-likelihood plus a weighted bridge penalty. This condition enables us to connect the literature on Gaussian graphical models to the literature on penalized Gaussian likelihood.Fil: Rothman, Adam J.. University of Minnesota. Scool Of Statistics; Estados UnidosFil: Forzani, Liliana Maria. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Matemática Aplicada "Litoral"; Argentin

On the existence of the weighted bridge penalized Gaussian likelihood precision matrix estimator

We establish a necessary and sufficient condition for the existence of the precision matrix estimator obtained by minimizing the negative Gaussian log-likelihood plus a weighted bridge penalty. This condition enables us to connect the literature on Gaussian graphical models to the literature on penalized Gaussian likelihood.Fil: Rothman, Adam J.. University of Minnesota. Scool Of Statistics; Estados UnidosFil: Forzani, Liliana Maria. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Matemática Aplicada "Litoral"; Argentin

Maximal operators associated with Generalized Hermite polynomials and function expansions

We study the weak and strong type boundedness of maximal heat?diffusion operators associated with the system of generalized Hermite polynomials and with two different systems of generalized Hermite functions. We also give a necessary background to define Sobolev spaces in this context.Fil: Forzani, Liliana Maria. Consejo Nacional de Invest.cientif.y Tecnicas. Centro Cientifico Tecnol - CONICET - Santa Fe. Instituto de Matematica Aplicada; Argentina; Universidad Nacional del Litoral. Facultad de Ingenieria Quimica;Fil: Sasso. Emanuela. Universita Di Genova; Italia;Fil: Scotto, Roberto Aníbal. Consejo Nacional de Invest.cientif.y Tecnicas. Centro Cientifico Tecnol - CONICET - Santa Fe. Instituto de Matematica Aplicada; Argentina; Universidad Nacional del Litoral. Facultad de Ingenieria Quimica

Sufficient reductions in regression with mixed predictors

Most data sets comprise of measurements on continuous and categorical variables. Yet,modeling high-dimensional mixed predictors has received limited attention in the regressionand classication statistical literature. We study the general regression problem of inferringon a variable of interest based on high dimensional mixed continuous and binary predictors.The aim is to nd a lower dimensional function of the mixed predictor vector that containsall the modeling information in the mixed predictors for the response, which can be eithercontinuous or categorical. The approach we propose identies sucient reductions byreversing the regression and modeling the mixed predictors conditional on the response.We derive the maximum likelihood estimator of the sucient reductions, asymptotic testsfor dimension, and a regularized estimator, which simultaneously achieves variable (feature)selection and dimension reduction (feature extraction). We study the performance of theproposed method and compare it with other approaches through simulations and real dataexamples.Fil: Bura, Efstathia. Technische Universitat Wien; AustriaFil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química; ArgentinaFil: García Arancibia, Rodrigo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ciencias Económicas. Instituto de Economía Aplicada Litoral; ArgentinaFil: Llop Orzan, Pamela Nerina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química; ArgentinaFil: Tomassi, Diego Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentin

Postbiotics produced at laboratory and industrial level as potential functional food ingredients with the capacity to protect mice against Salmonella infection

AIM:To determine the protective capacity against Salmonella infection in mice of the cell-free fraction (postbiotic) of fermented milk, produced at laboratory and industrial level.METHODS AND RESULTS:The proteolytic activity (PA) of five commercial cultures and eleven autochthonous Lactobacillus strains was evaluated. The DSM-100H culture displayed the highest PA and it was selected for further studies. The capacity of the postbiotics produced by pH-controlled fermentation to stimulate the production of secretory-IgA in faeces and to protect mice against Salmonella infection was evaluated. A significant increase of S-IgA in faeces of mice fed 14 days the postbiotic obtained at the laboratory (F36) was detected compared to control animals. A significantly higher survival was observed in mice fed the F36 and the FiSD (industrial product) compared to controls.CONCLUSION:The postbiotics obtained showed immunomodulatory and protective capacity against Salmonella infection in mice.SIGNIFICANCE AND IMPACT OF THE STUDY:The pH-controlled milk fermentation by the proteolytic DSM-100H culture could be a suitable strategy to obtain a food ingredient to be added to a given food matrix, not adequate to host viable cells of probiotics, to confer it enhanced functionality and thus expand the functional food market. This article is protected by copyright. All rights reserved.Fil: Dunnand, E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Lactología Industrial. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Lactología Industrial; ArgentinaFil: Burns, Patricia Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Lactología Industrial. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Lactología Industrial; ArgentinaFil: Binetti, Ana Griselda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Lactología Industrial. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Lactología Industrial; ArgentinaFil: Bergamini, Carina Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Lactología Industrial. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Lactología Industrial; ArgentinaFil: Peralta, Guillermo Hugo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Lactología Industrial. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Lactología Industrial; ArgentinaFil: Forzani, Liliana Maria. Universidad Nacional del Litoral. Facultad de Ingeniería Química; ArgentinaFil: Reinheimer, Jorge Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Lactología Industrial. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Lactología Industrial; ArgentinaFil: Vinderola, Celso Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Lactología Industrial. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Lactología Industrial; Argentin

Likelihood-Based Sufficient Dimension Reduction. Letters to the Editor

Discussion of the paper Likelihood based sufficient dimension reductionFil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentin

A mean-value inequality for non-negative solutions to the linearized monge-ampère equation

We prove a mean value inequality for non-negative solutions to L in any domain Ω∈∈ n , where L is the Monge-Ampère operator linearized at a convex function, under minimal assumptions on the Monge-Ampère measure of. An application to the Harnack inequality for affine maximal hypersurfaces is included.Fil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Maldonado, Diego. Kansas State University

Recent progress on the Monge-Ampère equation

We consider convex solutions to the Monge-Ampere equation when the measure is doubling.We summarized the latest results on geometric and measure theoretic properties associatesto the solutions. We also discuss applications such as the real analysis related to the solutions and the Holder regularity of the gradient of the solutions.Fil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Maldonado, Diego. University of Kansas; Estados Unido

Properties of the solutions to the Monge-Ampère equation

We consider solutions to the equation detD2φ=μ when μ has a doubling property. We prove new geometric characterizations for this doubling property (by means of the so-called engulfing property) and deduce the quantitative behaviour of φ. Also, a constructive approach to the celebrated C1,β-estimates proved by L. Caffarelli is presented, settling one of the open questions posed by Villani (Amer. Math. Soc. 58 (2003)).Fil: Forzani, Liliana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Maldonado, Diego. University Of Kansas, Lawrence