Evaluation of petrogenetic models for intermediate and silicic plutonic rocks from the Sierra de Valle Fertil-La Huerta, Argentina: Petrologic constraints on the origin of igneous rocks in the Ordovician Famatinian-Puna paleoarc

The whole Valle Fertil-La Huerta section appears as a calc-alkaline plutonic suite typical of a destructive plate margin. New Sr and Nd isotopic whole-rock data and published whole-rock geochemistry suggest that the less-evolved intermediate (dioritic) rocks can be derived by magmatic differentiation, mainly by hornblende + plagioclase +/- Fe-Ti oxide fractional crystallization, from mafic (gabbroic) igneous precursors. Closed-system differentiation, however, cannot produce the typical intermediate (tonalitic) and silicic (granodioritic) plutonic rocks, which requires a preponderant contribution of crustal components. Intermediate and silicic plutonic rocks from Valle Fertil-La Huerta section have formed in a plate subduction setting where the thermal and material input of mantle-derived magmas promoted fusion of fertile metasedimentary rocks and favored mixing of gabbroic or dioritic magmas with crustal granitic melts. Magma mixing is observable in the field and evident in variations of chemical elemental parameters and isotopic ratios, revealing that hybridization coupled with fractionation of magmas took place in the crust. Consideration of the whole-rock geochemical and isotopic data in the context of the Famatinian-Puna magmatic belt as a whole demonstrates that the petrologic model postulated for the Sierra Valle Fertil-La Huerta section has the potential to explain the generation of plutonic and volcanic rocks across the Early Ordovician paleoarc from central and northwestern Argentina. As the petrologic model does not require the intervention of old Precambrian continental crust, the nature of the basement on which thick accretionary turbiditic sequences were deposited remains a puzzling aspect. Discussion in this paper provides insights into the nature of magmatic source rocks and mechanisms of magma generation in Cordilleran-type volcano-plutonic arcs of destructive plate margins. (C) 2010 Elsevier Ltd. All rights reserved.

Bayesian analysis and constraints on kinematic models from union SNIa

The kinematic expansion history of the universe is investigated by using the 307 supernovae type Ia from the Union Compilation set. Three simple model parameterizations for the deceleration parameter ( constant, linear and abrupt transition) and two different models that are explicitly parametrized by the cosmic jerk parameter ( constant and variable) are considered. Likelihood and Bayesian analyses are employed to find best fit parameters and compare models among themselves and with the flat Lambda CDM model. Analytical expressions and estimates for the deceleration and cosmic jerk parameters today (q(0) and j(0)) and for the transition redshift (z(t)) between a past phase of cosmic deceleration to a current phase of acceleration are given. All models characterize an accelerated expansion for the universe today and largely indicate that it was decelerating in the past, having a transition redshift around 0.5. The cosmic jerk is not strongly constrained by the present supernovae data. For the most realistic kinematic models the 1 sigma confidence limits imply the following ranges of values: q(0) is an element of [-0.96, -0.46], j(0) is an element of [-3.2,-0.3] and z(t) is an element of [0.36, 0.84], which are compatible with the Lambda CDM predictions, q(0) = -0.57 +/- 0.04, j(0) = -1 and z(t) = 0.71 +/- 0.08. We find that even very simple kinematic models are equally good to describe the data compared to the concordance Lambda CDM model, and that the current observations are not powerful enough to discriminate among all of them.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.