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Ciudad Universitaria, Argentina

Kelmansky D.M.,Institute Calculo
Methods in Molecular Biology | Year: 2013

This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed. © Springer Science+Business Media New York 2013. Source

Soriano M.C.,University of the Balearic Islands | Zunino L.,University of the Balearic Islands | Zunino L.,CONICET | Zunino L.,National University of La Plata | And 4 more authors.
IEEE Journal of Quantum Electronics | Year: 2011

We analyze the intrinsic time scales of the chaotic dynamics of a semiconductor laser subject to optical feedback by estimating quantifiers derived from a permutation information approach. Based on numerically and experimentally obtained times series, we find that permutation entropy and permutation statistical complexity allow the extraction of important characteristics of the dynamics of the system. We provide evidence that permutation statistical complexity is complementary to permutation entropy, giving valuable insights into the role of the different time scales involved in the chaotic regime of the semiconductor laser dynamics subject to delay optical feedback. The results obtained confirm that this novel approach is a conceptually simple and computationally efficient method to identify the characteristic time scales of this relevant physical system. © 2011 IEEE. Source

Zunino L.,University of the Balearic Islands | Zunino L.,CONICET | Zunino L.,National University of La Plata | Soriano M.C.,University of the Balearic Islands | And 4 more authors.
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

In this paper an approach to identify delay phenomena from time series is developed. We show that it is possible to perform a reliable time delay identification by using quantifiers derived from information theory, more precisely, permutation entropy and permutation statistical complexity. These quantifiers show clear extrema when the embedding delay τ of the symbolic reconstruction matches the characteristic time delay τS of the system. Numerical data originating from a time delay system based on the well-known Mackey-Glass equations operating in the chaotic regime were used as test beds. We show that our method is straightforward to apply and robust to additive observational and dynamical noise. Moreover, we find that the identification of the time delay is even more efficient in a noise environment. Our permutation approach is also able to recover the time delay in systems with low feedback rate or high nonlinearity. © 2010 The American Physical Society. Source

Boente G.,University of Buenos Aires | Boente G.,Institute Calculo | Rodriguez D.,University of Buenos Aires
Computational Statistics and Data Analysis | Year: 2010

In many situations, data follow a generalized partly linear model in which the mean of the responses is modeled, through a link function, linearly on some covariates and nonparametrically on the remaining ones. A new class of robust estimates for the smooth function η, associated to the nonparametric component, and for the parameter β, related to the linear one, is defined. The robust estimators are based on a three-step procedure, where large values of the deviance or Pearson residuals are bounded through a score function. These estimators allow us to make easier inferences on the regression parameter β and also improve computationally those based on a robust profile likelihood approach. The resulting estimates of β turn out to be root-n consistent and asymptotically normally distributed. Besides, the empirical influence function allows us to study the sensitivity of the estimators to anomalous observations. A robust Wald test for the regression parameter is also provided. Through a Monte Carlo study, the performance of the robust estimators and the robust Wald test is compared with that of the classical ones. © 2010 Elsevier B.V. All rights reserved. Source

Soriano M.C.,University of the Balearic Islands | Zunino L.,University of the Balearic Islands | Zunino L.,CONICET | Zunino L.,National University of La Plata | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010

The time evolution of the output of a semiconductor laser subject to optical feedback can exhibit high-dimensional chaotic fluctuations. In this contribution, our aim is to quantify the complexity of the chaotic time-trace generated by a semiconductor laser subject to delayed optical feedback. To that end, we discuss the properties of two recently introduced complexity measures based on information theory, namely the permutation entropy (PE) and the statistical complexity measure (SCM). The PE and SCM are defined as a functional of a symbolic probability distribution, evaluated using the Bandt-Pompe recipe to assign a probability distribution function to the time series generated by the chaotic system. In order to evaluate the performance of these novel complexity quantifiers, we compare them to a more standard chaos quantifier, namely the Kolmogorov-Sinai entropy. Here, we present numerical results showing that the statistical complexity and the permutation entropy, evaluated at the different time-scales involved in the chaotic regime of the laser subject to optical feedback, give valuable information about the complexity of the laser dynamics. © 2010 SPIE. Source

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