Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

Hyperfine interaction studies with (181)Ta and (111)Cd probes in the compound Ti(2)Ag

By using the time-differential perturbed angular correlation technique, the electric field gradients (EFG) at (181)Hf/(181)Ta and (111)In/(111)Cd probe sites in the MoSi(2)-type compound Ti(2)Ag have been measured as a function of temperature in the range from 24 to 1073 K. Ab initio EFG calculations have been performed within the framework of density functional theory using the full-potential augmented plane wave + local orbitals method as implemented in the WIEN2k package. These calculations allowed assignments of the probe lattice sites. For Ta, a single well-defined EFG with very weak temperature dependence was established and attributed to the [4(e)4mm] Ti site. For (111)Cd probes, two of the three measured EFGs are well defined and correlated with substitutional lattice sites, i.e. both the [4(e)4mm] Ti site and the [2(a)4/mmm] Ag site.

Structural and magnetic properties and hyperfine interaction in La(3.5)Ru(4)O(13) compound

Structural, magnetic and hyperfine interaction measurements have been carried out on the novel compound La(3.5)Ru(4)O(13) prepared under two different atmospheres (air and oxygen flow). This compound is formed in the orthorhombic structure (space group Pmmm, # 47). The coexistence of the triple-layered perovskite-type planes (quasi-2D structure) and the rutile-like slabs (1D structure) leads to interesting magnetic and electronic properties in this compound. The magnetic susceptibility of this system shows a peak at T similar to 47 K associated with antiferromagnetic interactions. The Curie-Weiss behaviour of the susceptibility provides an effective magnetic moment consistent with Ru ions in low-spin state. Perturbed angular correlation measurements carried out with (111)Cd probe in the temperature range 10-60 K reveal only quadrupole interactions and indicate the occurrence of structural distortions for T<40K. (C) 2009 Elsevier B.V. All rights reserved.

The Granada ignimbrite: A compound pyroclastic unit and its relationship with Upper Miocene caldera volcanism in the northern Puna

The Granada ignimbrite, an Upper Miocene volcanic unit from the northern Puna, previously has been interpreted as an extensive ignimbrite (>2300 km(2)) associated with eruptions from the Vilama caldera (trap-door event). On the basis of new data, we revise its correlation and redefine the unit as a compound, high aspect ratio ignimbrite, erupted at approximately 9.8 Ma. Calculated volumes (similar to 100 km(3)) are only moderate in comparison with other large volume (>1000 km(3)) ignimbrites that erupted approximately 2-6 m.y. later in the region (e.g. Vilama, Panizos, Atana). Six new volcanic units are recognized from sequences previously correlated with Granada (only one sourced from the same center). Consequently, the area ascribed to the Granada ignimbrite is substantially reduced (630 km(2)), and links to the Vilama caldera are not supported. Transport directions suggest the volcanic source for the Granada ignimbrite corresponds to vents buried under younger (>= 7.9-5 Ma) volcanic rocks of the Abra Granada volcanic complex. Episodes of caldera collapse at some stage of eruption are likely, though their nature and timing cannot be defined from available data. The eruption of the Granada ignimbrite marks the onset of a phase of large volume (caldera-sourced) volcanism in the northern Puna. (C) 2007 Elsevier Ltd. All rights reserved.

Random sums of exchangeable variables and actuarial applications

In this paper we study the accumulated claim in some fixed time period, skipping the classical assumption of mutual independence between the variables involved. Two basic models are considered: Model I assumes that any pair of claims are equally correlated which means that the corresponding square-integrable sequence is exchangeable one. Model 2 states that the correlations between the adjacent claims are the same. Recurrence and explicit expressions for the joint probability generating function are derived and the impact of the dependence parameter (correlation coefficient) in both models is examined. The Markov binomial distribution is obtained as a particular case under assumptions of Model 2. (C) 2007 Elsevier B.V. All rights reserved.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc All rights reserved

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.

A compound class of Weibull and power series distributions

In this paper we introduce the Weibull power series (WPS) class of distributions which is obtained by compounding Weibull and power series distributions where the compounding procedure follows same way that was previously carried out by Adamidis and Loukas (1998) This new class of distributions has as a particular case the two-parameter exponential power series (EPS) class of distributions (Chahkandi and Gawk 2009) which contains several lifetime models such as exponential geometric (Adamidis and Loukas 1998) exponential Poisson (Kus 2007) and exponential logarithmic (Tahmasbi and Rezaei 2008) distributions The hazard function of our class can be increasing decreasing and upside down bathtub shaped among others while the hazard function of an EPS distribution is only decreasing We obtain several properties of the WPS distributions such as moments order statistics estimation by maximum likelihood and inference for a large sample Furthermore the EM algorithm is also used to determine the maximum likelihood estimates of the parameters and we discuss maximum entropy characterizations under suitable constraints Special distributions are studied in some detail Applications to two real data sets are given to show the flexibility and potentiality of the new class of distributions (C) 2010 Elsevier B V All rights reserved

Horseradish peroxidase compound I as a tool to investigate reactive protein-cysteine residues: from quantification to kinetics

Proteins containing reactive cysteine residues (protein-Cys) are receiving increased attention as mediators of hydrogen peroxide signaling. These proteins are mainly identified by mining the thiol proteomes of oxidized protein-Cys in cells and tissues. However, it is difficult to determine if oxidation occurs through a direct reaction with hydrogen peroxide or by thiol-disulfide exchange reactions. Kinetic studies with purified proteins provide invaluable information about the reactivity of protein-Cys residues with hydrogen peroxide. Previously, we showed that the characteristic UV-Vis spectrum of horseradish peroxidase compound I, produced from the oxidation of horseradish peroxidase by hydrogen peroxide, is a simple, reliable, and useful tool to determine the second-order rate constant of the reaction of reactive protein-Cys with hydrogen peroxide and peroxynitrite. Here, the method is fully described and extended to quantify reactive protein-Cys residues and micromolar concentrations of hydrogen peroxide. Members of the peroxiredoxin family were selected for the demonstration and validation of this methodology. In particular, we determined the pK(a) of the peroxidatic thiol of rPrx6 (5.2) and the second-order rate constant of its reactions with hydrogen peroxide ((3.4 +/- 0.2) x 10(7) M(-1) s(-1)) and peroxynitrite ((3.7 +/- 0.4) x 10(5) M(-1) s(-1)) at pH 7.4 and 25 degrees C. (C) 2011 Elsevier Inc. All rights reserved.

Bcl-2 expression and apoptosis induction in human HL60 leukaemic cells treated with a novel organotellurium(IV) compound RT-04

Organotellurium(]V) compounds have been reported to have multiple biological activities including cysteine protease-inhibitory activity, mainly cathepsin B. As cathepsin B is a highly predictive indicator for prognosis and diagnosis of cancer, a possible antitumor potential for these new compounds is expected. In this work, it was investigated the effectiveness of organotellurium(IV) RT-04 to produce lethal effects in the human promyelocytic leukaemia cell line HL60. Using the MTT tetrazolium reduction test, and trypan blue exclusion assay, the IC50 for the compound after 24 h incubation was 6.8 and 0.35 mu M, respectively. Moreover, the compound was found to trigger apoptosis in HL60 cells, inducing DNA fragmentation and caspase-3, -6, and -9 activations. The apoptsosis-induced by RT-04 is probably related to the diminished Bcl-2 expression, observed by RT-PCR, in HL60-treated cells. In vivo studies demonstrated that the RT-04 treatment (2.76 mg/kg given for three consecutive days) produces no significant toxic effects for bone marrow and spleen CFU-GM. However, higher doses (5.0 and 10 mg/kg) produced a dose-dependent reduction in the number of CFU-GM of RT-04-treated mice. These results suggest that RT-04 is able to induce apoptosis in HL60 cells by Bcl-2 expression down-modulation. Further studies are necessary to better clarify the effects of this compound on bone marrow normal cells. (C) 2008 Elsevier Ltd. All rights reserved.

Expression Profile of Rat Hippocampal Neurons Treated with the Neuroprotective Compound 2,4-Dinitrophenol: Up-Regulation of cAMP Signaling Genes

2,4-Dinitrophenol (DNP) is classically known as a mitochondrial uncoupler and, at high concentrations, is toxic to a variety of cells. However, it has recently been shown that, at subtoxic concentrations, DNP protects neurons against a variety of insults and promotes neuronal differentiation and neuritogenesis. The molecular and cellular mechanisms underlying the beneficial neuroactive properties of DNP are still largely unknown. We have now used DNA microarray analysis to investigate changes in gene expression in rat hippocampal neurons in culture treated with low micromolar concentrations of DNP. Under conditions that did not affect neuronal viability, high-energy phosphate levels or mitochondrial oxygen consumption, DNP induced up-regulation of 275 genes and down-regulation of 231 genes. Significantly, several up-regulated genes were linked to intracellular cAMP signaling, known to be involved in neurite outgrowth, synaptic plasticity, and neuronal survival. Differential expression of specific genes was validated by quantitative RT-PCR using independent samples. Results shed light on molecular mechanisms underlying neuroprotection by DNP and point to possible targets for development of novel therapeutics for neurodegenerative disorders.

A Note on Proxy Variables and Instrument Variable Regression

This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists