cornea curvature maps, functional data, principal components analysis, robust statistics, spherical PCA, Zernike basis, 62H99,

Over the last few years many methods have been developed for analyzing functional data with different objectives. The purpose of this paper is to predict a binary response variable in terms of a functional variable whose sample information is given by a set of curves measured without error. In order to solve this problem we formulate a functional logistic regression model and propose its estimation by approximating the sample paths in a finite dimensional space generated by a basis. Then, the problem is reduced to a multiple logistic regression model with highly correlated covariates. In order to reduce dimension and to avoid multicollinearity, two different approaches of functional principal component analysis of the sample paths are proposed. Finally, a simulation study for evaluating the estimating performance of the proposed principal component approaches is developed.

No abstract

CYP1A1, CYP2E1 and GSTM1 polymorphisms were evaluated in Chilean healthy controls and lung cancer patients. In the Chilean healthy group, frequencies of CYP1A1 variant alleles for MspI (m2 or CYP1A1*2A) and ile/val (val or CYP1A1*2B) polymorphisms were 0.25 and 0.33, respectively. Frequencies of variant alleles C (CYP2E1*6) and c2 (CYP2E1*5B) for CYP2E1 were 0.21 and 0.16, respectively and frequency for GSTM1(-) was 0.24. The presence of variant alleles for GSTM1, MspI and Ile/val polymorphisms was more frequent in cases than in controls. However, frequencies for the c2 and C alleles were not significantly different in controls and in cases. The estimated relative risk for lung cancer associated to a single mutated allele in CYP1A1, CYP2E1 or GSTM1 was 2.41 for m2, 1.69 for val, 1.16 for C, 0.71 for c2 and 2.46 for GSTM1(-). The estimated relative risk was higher for individuals carrying combined CYP1A1 and GSTM1 mutated alleles (m2/val, OR=6.28; m2/GSTM1(-), OR=3.56) and lower in individuals carrying CYP1A1 and CYP2E1 mutated alleles (m2/C, OR=1.39; m2/c2, OR=2.00; val/C, OR=1.45; val/c2, OR=0.48; not significant). The OR values considering smoking were 4.37 for m2, 4.05 for val, 3.47 for GSTM1(-), 7.38 for m2/val and 3.68 for m2/GSTM1(-), higher values than those observed without any stratification by smoking. Taken together, these findings suggest that Chilean people carrying single or combined GSTM1 and CYP1A1 polymorphisms could be more susceptible to lung cancer induced by environmental pollutants such as polycyclic aromatic hydrocarbons.

Time series statistical analyses (TSSA) have been employed to evaluate the variability of resistive switching memories, and to model the set and reset voltages for modeling purposes. The conventional procedures behind time series theory have been used to obtain autocorrelation and partial autocorrelation functions and determine the simplest analytical models to forecast the set and reset voltages in long series of resistive switching processes. To do so, and for the sake of generality in our study, a wide range of devices have been fabricated and measured. Different oxides and electrodes have been employed, including bilayer dielectrics in devices such as: