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.

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator. (C) 2007 Elsevier B.V. All rights reserved.

Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

Perpendicularly self-oriented and shape-controlled L1(0)-FePt nanorods directly synthesized by a temperature-modulated process

The synthesis and self-assembly of tetragonal phase-containing L1(0)-Fe(55)Pt(45) nanorods with high coercive field is described. The experimental procedure resulted in a tetragonal/cubic phase ratio close to 1:1 for the as-synthesized nanoparticles. Using different surfactant/solvent proportions in the process allowed control of particle morphology from nanospheres to nanowires. Monodisperse nanorods with lengths of 60 +/- 5 nm and diameters of 2-3 nm were self-assembled in a perpendicular oriented array onto a substrate surface using hexadecylamine as organic spacer. Magnetic alignment and properties assigned, respectively, to the shape anisotropy and the tetragonal phase suggest that the self-assembled materials are a strong candidate to solve the problem of random magnetic alignment observed in FePt nanospheres leading to applications in ultrahigh magnetic recording (UHMR) systems capable of achieving a performance of the order of terabits/in(2).