Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

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.

Microwave-assisted solid-phase peptide synthesis at 60 degrees C: alternative conditions with low enantiomerization

Several conditions have been used in the coupling reaction of stepwise SPPS at elevated temperature (SPPS-ET), but we have elected the following as our first choice: 2.5-fold molar excess of 0.04-0.08 M Boc or Fmoc-amino acid derivative, equimolar amount of DIC/HOBt (1:1)or TBTU/DIPEA(1:3), 25% DMSO/toluene, 60 degrees C, conventional heating. In this study, aimed to further examine enantiomerization under such condition and study the applicability of our protocols to microwave-SPPS, peptides containing L-Ser, L-His, L-Cys and/or L-Met were manually synthesized traditionally, at 60 degrees C using conventional heating and at 60 degrees C using microwave heating. Detailed assessment of all crude peptides (in their intact and/or fully hydrolyzed forms) revealed that, except for the microwave-assisted coupling of L-Cys, all other reactions occurred with low levels of amino acid enantiomerization (<2%). Therefore, herein we (i) provide new evidences that our protocols for SPPS at 60 degrees C using conventional heating are suitable for routine use, (ii) demonstrate their appropriateness for microwave-assisted SPPS by Boc and Fmoc chemistries, (iii) disclose advantages and limitations of the three synthetic approaches employed. Thus, this study complements our past research on SPPS-ET and suggests alternative conditions for microwave-assisted SPPS. Copyright (C) 2009 European Peptide Society and John Wiley & Sons, Ltd.