Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Gaze pursuit and arm control of adolescent males diagnosed with attention deficit hyperactivity disorder (ADHD) and normal controls: evidence of a dissociation in processing visual information of short and long duration

Three-dimensional kinematic analysis of line of gaze, arm and ball was used to describe the visual and motor behaviour of male adolescents diagnosed with attention deficit hyperactivity disorder (ADHD). The ADHD participants were tested when both on (ADHD-On) and off (ADHD-Off) their medication and compared to age-matched normal controls in a modified table tennis task that required tracking the ball and hitting to cued right and left targets. Long-duration information was provided by a pre-cue, in which the target was illuminated approximately 2 s before the serve, and short-duration information by an early-cue illuminated about 350 ms after the serve, leaving -500 ms to select the target and perform the action. The ADHD groups differed significantly from the control group in both the pre-cue and early-cue conditions in being less accurate, in having a later onset and duration of pursuit tracking, and a higher frequency of gaze on and off the ball. The use of medication significantly reduced the gaze frequency of the ADHD participants, but surprisingly this did not lead to an increase in pursuit tracking, suggesting a barrier was reached beyond which ball flight information could not be processed. The control and ADHD groups did not differ in arm movement onset, duration and velocity in the short-duration early-cue condition; in the long-duration pre-cue condition, however, the ADHD group's movement time onset and arm velocity differed significantly from controls. The results show that the ADHD groups were able to process short-duration information without experiencing adverse effects on their motor behaviour; however, long-duration information contributed to irregular movement control.

Bayesian outlier analysis in binary regression

We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the focus is mainly on accommodation of outliers, the proposed methodology is also able to detect them. Our approach consists of evaluating the posterior distribution of random effects included in the linear predictor. The evaluation of the posterior distributions of interest involves cumbersome integration, which is easily dealt with through stochastic simulation methods. We also discuss different specifications of prior distributions for the random effects. The potential of these strategies is compared in a real data set. The main finding is that the inclusion of extra variability accommodates the outliers, improving the adjustment of the model substantially, besides correctly indicating the possible outliers.

Bayesian estimation of generalized exponential distribution under noninformative priors

The generalized exponential distribution, proposed by Gupta and Kundu (1999), is a good alternative to standard lifetime distributions as exponential, Weibull or gamma. Several authors have considered the problem of Bayesian estimation of the parameters of generalized exponential distribution, assuming independent gamma priors and other informative priors. In this paper, we consider a Bayesian analysis of the generalized exponential distribution by assuming the conventional non-informative prior distributions, as Jeffreys and reference prior, to estimate the parameters. These priors are compared with independent gamma priors for both parameters. The comparison is carried out by examining the frequentist coverage probabilities of Bayesian credible intervals. We shown that maximal data information prior implies in an improper posterior distribution for the parameters of a generalized exponential distribution. It is also shown that the choice of a parameter of interest is very important for the reference prior. The different choices lead to different reference priors in this case. Numerical inference is illustrated for the parameters by considering data set of different sizes and using MCMC (Markov Chain Monte Carlo) methods.

Thermistor behaviour and electric conduction analysis of Ni-doped niobate ferroelectric: the role of multiple beta parameters

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Impact of breed and sex on porcine endocrine transcriptome: a bayesian biometrical analysis

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Meta-Analysis of Predation Risk Effects on Pollinator Behaviour

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Bayesian Analysis of Spectral ARMA Model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A bayesian analysis for the parameters of the exponential-logarithmic distribution

The exponential-logarithmic is a new lifetime distribution with decreasing failure rate and interesting applications in the biological and engineering sciences. Thus, a Bayesian analysis of the parameters would be desirable. Bayesian estimation requires the selection of prior distributions for all parameters of the model. In this case, researchers usually seek to choose a prior that has little information on the parameters, allowing the data to be very informative relative to the prior information. Assuming some noninformative prior distributions, we present a Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. Jeffreys prior is derived for the parameters of exponential-logarithmic distribution and compared with other common priors such as beta, gamma, and uniform distributions. In this article, we show through a simulation study that the maximum likelihood estimate may not exist except under restrictive conditions. In addition, the posterior density is sometimes bimodal when an improper prior density is used. © 2013 Copyright Taylor and Francis Group, LLC.

Stabilometric parameters analysis in children with visual disorder

Background: Although postural changes were already reported in blind adults, no previous study has investigated postural stability in blind children. Moreover, there are few studies which used a stabilometric instrument to measure postural balance. In this study we evaluated stabilometric paramaters in blind children. Methods: We evaluated children between 7 to 12 years old, they were divided into two groups: Blind (n = 11) and age-matched control (n = 11) groups by using computerized stabilometry. The stabilometric examination was performed taking the gravity centers displacement of the individual projected into the platform. Thirthy seconds after the period in which this information was collected, the program defined a medium-pressure center, which was used to define x and y axes displacement and the distance between the pressure center and the platform center. Furthermore, the average sway rate and the body sway area were obtained by dividing the pressure center displacement and the time spent on the task; and by an ellipse function (95% percentille), respectively. Percentages of anterior, posterior, left and right feet weight also were calculated. Variables were compared by using the Student’s t test for unpaired data. Significance level was considered for p <0.05. Results: Displacement of the x axis (25.55 ± 9.851 vs. -3.545 ± 7.667; p <0.05) and average sway rate (19.18 ± 2.7 vs. -10.55 ± 1.003; p <0.001) were increased in the blind children group. Percentage of left foot weight was reduced (45.82 ± 2.017 vs. 52.36 ± 1.33; p <0.05) while percentage of right foot weight was increased (54.18 ± 2.17 vs. 47.64 ± 1.33; p <0.05) in blind children. Other variables did not show differences. Conclusions: Blind children present impaired stabilometric parameters.

Analysis of the positioning of the head, trunk, and upper limbs during gait in children with visual impairment

Background: This study analyzed the positioning of the head, trunk, and upper extremities during gait in children with visual impairment. Methods: A total of 11 children participated in this study: 6 with blindness and 5 with low vision. The kinematics of the positioning of the head, trunk, shoulders, and elbows in each participant was analyzed during the four phases of the gait cycle: foot strike, support, toe-off, and swing. Results: There were significant differences between children with blindness and low vision in the positioning of the trunk in the sagittal plane during the foot strike, support, and swing phases. Conclusions: The analysis identified postural alterations of the head, trunk, shoulder, and elbow during the children’s gait, highlighting the relevance of appropriate stimulation at an early age in orientation and mobility programs, as well as the essential presence of professionals who work with movement.

Limits of Visual Detection for Finasteride Polymorphs in Prepared Binary Mixtures: Analysis by X-ray Powder Diffraction

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bayesian age and growth analysis of the shortfin mako shark Isurus oxyrinchus in the Western South Atlantic Ocean using a flexible model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation of the diagnostic accuracy of the glyco-C and US9 gene-based polymerase chain reaction technique for the detection of bovine Herpesvirus type 5 DNA in decomposed brain suspension from a slaughter house using Bayesian analysis, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)