The log-bimodal-skew-normal model. A geochemical application

The main objective of this paper is to study a logarithm extension of the bimodal skew normal model introduced by Elal-Olivero et al. [1]. The model can then be seen as an alternative to the log-normal model typically used for fitting positive data. We study some basic properties such as the distribution function and moments, and discuss maximum likelihood for parameter estimation. We report results of an application to a real data set related to nickel concentration in soil samples. Model fitting comparison with several alternative models indicates that the model proposed presents the best fit and so it can be quite useful in real applications for chemical data on substance concentration. Copyright (C) 2011 John Wiley & Sons, Ltd.

Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.

Skew-normal linear calibration: a Bayesian perspective

In this paper, we present a Bayesian approach for estimation in the skew-normal calibration model, as well as the conditional posterior distributions which are useful for implementing the Gibbs sampler. Data transformation is thus avoided by using the methodology proposed. Model fitting is implemented by proposing the asymmetric deviance information criterion, ADIC, a modification of the ordinary DIC. We also report an application of the model studied by using a real data set, related to the relationship between the resistance and the elasticity of a sample of concrete beams. Copyright (C) 2008 John Wiley & Sons, Ltd.

A non-normal topology generated by a two-point selection

We construct a two-point selection f : [P](2) -> P, where P is the set of the irrational numbers, such that the space (P, tau(f)) is not normal and it is not collectionwise Hausdorff either. Here, tau(f) denotes the topology generated by the two-point selection f. This example answers a question posed by V. Gutev and T. Nogura. We also show that if f :[X](2) -> X is a two-point selection such that the topology tau(f) has countable pseudocharacter, then tau(f) is a Tychonoff topology. (C) 2008 Elsevier B.V. All rights reserved.

Bias correction in a multivariate normal regression model with general parameterization

This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.

Base Excision Repair Activities Differ in Human Lung Cancer Cells and Corresponding Normal Controls

Oxidative damage to DNA is thought to play a role in carcinogenesis by causing Mutations, and indeed accumulation of oxidized DNA bases has been observed in samples obtained from tumors but not from surrounding tissue within the same patient. Base excision repair (BER) is the main pathway for the repair of oxidized modifications both in nuclear and mitochondrial, DNA. In order to ascertain whether diminished BER capacity might account for increased levels of oxidative DNA damage in cancer cells, the activities of BER enzymes in three different lung cancer cell lines and their non-cancerous counterparts were measured using oligonucleotide substrates with single DNA lesions to assess specific BER enzymes. The activities of four BER enzymes, OGG1, NTH1, UDG and APE1, were compared in mitochondrial and nuclear extracts. For each specific lesion, the repair activities were similar among the three cell lines used. However, the specific activities and cancer versus control comparison differed significantly between the nuclear and mitochondrial compartments. OGG1 activity, as measured by 8-oxodA incision, was upregulated in cancer cell mitochondria but down-regulated in the nucleus when compared to control cells. Similarly, NTH1 activity was also up-regulated in mitochondrial extracts from cancer cells but did not change significantly in the nucleus. Together, these results support the idea that alterations in BER capacity are associated with carcinogenesis.