Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Sources of variation of energy and nutrient intake among adolescents in São Paulo, Brazil

The aim of the current study was to describe the sources of variation of energy and nutrient intake and to calculate the number of repetitions of diet measurements to estimate usual intake in adolescents from São Paulo, Brazil. Data was collected using 24-hour dietary recalls (24hR) in 273 adolescents between 2007 and 2008. Individuals completed a repeat 24hR around two months later. The sources of variation were estimated using the random effect model. Variance ratios (within-person to between-person variance ratio) and the number of repetitions of 24hR to estimate usual intake were calculated. The principal source of variation was due to within-person variance. The contribution of day of week and month of year was less than 8%. Variations ranged from 1.15 for calcium to 7.31 for vitamin E. The number of 24hR repeats required to estimate usual intake varied according to nutrient and gender, numbering 15 for males and 8 for females.

Fontes de variação da ingestão de energia e nutrientes entre adolescentes do Município de São Paulo, Brasil

Este estudo propôs-se a descrever as fontes de variação da ingestão de energia e nutrientes e calcular o número de dias necessários para a estimativa da ingestão habitual em adolescentes do Município de São Paulo, Brasil. Foi aplicado um recordatório alimentar de 24 horas (R24h) em 273 adolescentes, durante os anos de 2007 e 2008, e posteriormente cada indivíduo foi convidado a responder a outro R24h. Foram estimadas as fontes de variação da ingestão utilizando-se modelo de efeitos aleatórios. A variância intrapessoal foi o componente de variância que mais contribuiu para a variabilidade da ingestão de energia e nutrientes, ao passo que a contribuição do dia da semana e mês do ano foi pequena (< 8por cento ) para a variabilidade total da ingestão. As razões de variância variaram de 1,15 para o cálcio a 7,31 para a vitamina E. O número de R24h necessário para estimar a ingestão habitual variou de acordo com o nutriente: em torno de 15 para o sexo masculino e 8 para o feminino

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Influence of memory in deterministic walks in random media: Analytical calculation within a mean-field approximation

Consider a random medium consisting of N points randomly distributed so that there is no correlation among the distances separating them. This is the random link model, which is the high dimensionality limit (mean-field approximation) for the Euclidean random point structure. In the random link model, at discrete time steps, a walker moves to the nearest point, which has not been visited in the last mu steps (memory), producing a deterministic partially self-avoiding walk (the tourist walk). We have analytically obtained the distribution of the number n of points explored by the walker with memory mu=2, as well as the transient and period joint distribution. This result enables us to explain the abrupt change in the exploratory behavior between the cases mu=1 (memoryless walker, driven by extreme value statistics) and mu=2 (walker with memory, driven by combinatorial statistics). In the mu=1 case, the mean newly visited points in the thermodynamic limit (N >> 1) is just < n >=e=2.72... while in the mu=2 case, the mean number < n > of visited points grows proportionally to N(1/2). Also, this result allows us to establish an equivalence between the random link model with mu=2 and random map (uncorrelated back and forth distances) with mu=0 and the abrupt change between the probabilities for null transient time and subsequent ones.

Placebo Response of Non-Pharmacological and Pharmacological Trials in Major Depression: A Systematic Review and Meta-Analysis

Background: Although meta-analyses have shown that placebo responses are large in Major Depressive Disorder (MDD) trials; the placebo response of devices such as repetitive transcranial magnetic stimulation (rTMS) has not been systematically assessed. We proposed to assess placebo responses in two categories of MDD trials: pharmacological (antidepressant drugs) and non-pharmacological (device-rTMS) trials. Methodology/Principal Findings: We performed a systematic review and meta-analysis of the literature from April 2002 to April 2008, searching MEDLINE, Cochrane, Scielo and CRISP electronic databases and reference lists from retrieved studies and conference abstracts. We used the keywords placebo and depression and escitalopram for pharmacological studies; and transcranial magnetic stimulation and depression and sham for non-pharmacological studies. All randomized, double-blinded, placebo-controlled, parallel articles on major depressive disorder were included. Forty-one studies met our inclusion criteria-29 in the rTMS arm and 12 in the escitalopram arm. We extracted the mean and standard values of depression scores in the placebo group of each study. Then, we calculated the pooled effect size for escitalopram and rTMS arm separately, using Cohen's d as the measure of effect size. We found that placebo response are large for both escitalopram (Cohen's d-random-effects model-1.48; 95% C.I. 1.26 to 1.6) and rTMS studies (0.82; 95% C.I. 0.63 to 1). Exploratory analyses show that sham response is associated with refractoriness and with the use of rTMS as an add-on therapy, but not with age, gender and sham method utilized. Conclusions/Significance: We confirmed that placebo response in MDD is large regardless of the intervention and is associated with depression refractoriness and treatment combination (add-on rTMS studies). The magnitude of the placebo response seems to be related with study population and study design rather than the intervention itself.

Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

Evaluation of carcass characteristics of Bos indicus and tropically adapted Bos taurus breeds selected for postweaning weight

Data from 9 studies were compiled to evaluate the effects of 20 yr of selection for postweaning weight (PWW) on carcass characteristics and meat quality in experimental herds of control Nellore (NeC) and selected Nellore (NeS), Caracu (CaS), Guzerah (GuS), and Gir (GiS) breeds. These studies were conducted with animals from a genetic selection program at the Experimental Station of Sertaozinho, Sao Paulo State, Brazil. After the performance test (168 d postweaning), bulls (n = 490) from the calf crops born between 1992 and 2000 were finished and slaughtered to evaluate carcass traits and meat quality. Treatments were different across studies. A meta-analysis was conducted with a random coefficients model in which herd was considered a fixed effect and treatments within year and year were considered as random effects. Either calculated maturity degree or initial BW was used interchangeably as the covariate, and least squares means were used in the multiple-comparison analysis. The CaS and NeS had heavier (P = 0.002) carcasses than the NeC and GiS; GuS were intermediate. The CaS had the longest carcass (P < 0.001) and heaviest spare ribs (P < 0.001), striploin (P < 0.001), and beef plate (P = 0.013). Although the body, carcass, and quarter weights of NeS were similar to those of CaS, NeS had more edible meat in the leg region than did CaS bulls. Selection for PWW increased rib-eye area in Nellore bulls. Selected Caracu had the lowest (most favorable) shear force values compared with the NeS (P = 0.003), NeC (P = 0.005), GuS (P = 0.003), and GiS (P = 0.008). Selection for PWW increased body, carcass, and meat retail weights in the Nellore without altering dressing percentage and body fat percentage.

A Dynamic Model of Hand-and-Foot Syndrome in Patients Receiving Capecitabine

For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.

Predator-prey models: an application for the plankton dynamics of lake Geneva

In this paper we present a hierarchical Bayesian analysis for a predator-prey model applied to ecology considering the use of Markov Chain Monte Carlo methods. We consider the introduction of a random effect in the model and the presence of a covariate vector. An application to ecology is considered using a data set related to the plankton dynamics of lake Geneva for the year 1990. We also discuss some aspects of discrimination of the proposed models.

Antiferromagnetic spherical spin-glass model

We study the thermodynamic properties and the phase diagrams of a multi-spin antiferromagnetic spherical spin-glass model using the replica method. It is a two-sublattice version of the ferromagnetic spherical p-spin glass model. We consider both the replica-symmetric and the one-step replica-symmetry-breaking solutions, the latter being the most general solution for this model. We find paramagnetic, spin-glass, antiferromagnetic and mixed or glassy antiferromagnetic phases. The phase transitions are always of second order in the thermodynamic sense, but the spin-glass order parameter may undergo a discontinuous change.

Pseudolikelihood equations for Potts MRF model parameter estimation on higher order neighborhood systems

This letter presents pseudolikelihood equations for the estimation of the Potts Markov random field model parameter on higher order neighborhood systems. The derived equation for second-order systems is a significantly reduced version of a recent result found in the literature (from 67 to 22 terms). Also, with the proposed method, a completely original equation for Potts model parameter estimation in third-order systems was obtained. These equations allow the modeling of less restrictive contextual systems for a large number of applications in a computationally feasible way. Experiments with both simulated and real remote sensing images provided good results.

Prediction in Multilevel Logistic Regression

The purpose of this article is to present a new method to predict the response variable of an observation in a new cluster for a multilevel logistic regression. The central idea is based on the empirical best estimator for the random effect. Two estimation methods for multilevel model are compared: penalized quasi-likelihood and Gauss-Hermite quadrature. The performance measures for the prediction of the probability for a new cluster observation of the multilevel logistic model in comparison with the usual logistic model are examined through simulations and an application.

Spontaneous symmetry breaking in amnestically induced persistence

We investigate a recently proposed non-Markovian random walk model characterized by loss of memories of the recent past and amnestically induced persistence. We report numerical and analytical results showing the complete phase diagram, consisting of four phases, for this system: (i) classical nonpersistence, (ii) classical persistence, (iii) log-periodic nonpersistence, and (iv) log-periodic persistence driven by negative feedback. The first two phases possess continuous scale invariance symmetry, however, log-periodicity breaks this symmetry. Instead, log-periodic motion satisfies discrete scale invariance symmetry, with complex rather than real fractal dimensions. We find for log-periodic persistence evidence not only of statistical but also of geometric self-similarity.

Fluoride-modified electrical properties of lead borate glasses and electrochemically induced crystallization in the glassy state

Lead fluoroborate glasses were prepared by the melt-quenching technique and characterized in terms of (micro)structural and electrical properties. The study was conducted on as prepared as well as temperature- and/or electric field-treated glass samples. The results show that, in the as-prepared glassy-state materials, electrical conductivity improved with increasing the PbF(2) glass content. This result involves both an increase of the fluoride charge carrier density and, especially, a decrease of the activation energy from a glass structure expansion improving charge carrier mobility. Moreover, for the electric field-treated glass samples, surface crystallization was observed even below the glass transition temperature. As previously proposed in literature, and shown here, the occurrence of this phenomenon arose from an electrochemically induced redox reaction at the electrodes, followed by crystallite nucleation. Once nucleated, growth of beta-PbF(2) crystallites, with the indication of incorporating reduced lead ions (Pb(+)), was both (micro)structurally and electrically detectable and analyzed. The overall crystallization-associated features observed here adapt well with the floppy-rigid model that has been proposed to further complete the original continuous-random-network model by Zachariasen for closely addressing not only glasses' structure but also crystallization mechanism. Finally, the crystallization-modified kinetic picture of the glasses' electrical properties, through application of polarization/depolarization measurements originally combined with impedance spectroscopy, was extensively explored. (c) 2008 American Institute of Physics.