Copula-based regression models: A survey

In this review paper we collect several results about copula-based models, especially concerning regression models, by focusing on some insurance applications. (C) 2009 Elsevier B.V. All rights reserved.

Fitting spatial models in the R package: hglm

We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

Essays in macroeconomy and dynamic term-structure models

This thesis is composed of three articles with the subjects of macroeconomics and - nance. Each article corresponds to a chapter and is done in paper format. In the rst article, which was done with Axel Simonsen, we model and estimate a small open economy for the Canadian economy in a two country General Equilibrium (DSGE) framework. We show that it is important to account for the correlation between Domestic and Foreign shocks and for the Incomplete Pass-Through. In the second chapter-paper, which was done with Hedibert Freitas Lopes, we estimate a Regime-switching Macro-Finance model for the term-structure of interest rates to study the US post-World War II (WWII) joint behavior of macro-variables and the yield-curve. We show that our model tracks well the US NBER cycles, the addition of changes of regime are important to explain the Expectation Theory of the term structure, and macro-variables have increasing importance in recessions to explain the variability of the yield curve. We also present a novel sequential Monte-Carlo algorithm to learn about the parameters and the latent states of the Economy. In the third chapter, I present a Gaussian A ne Term Structure Model (ATSM) with latent jumps in order to address two questions: (1) what are the implications of incorporating jumps in an ATSM for Asian option pricing, in the particular case of the Brazilian DI Index (IDI) option, and (2) how jumps and options a ect the bond risk-premia dynamics. I show that jump risk-premia is negative in a scenario of decreasing interest rates (my sample period) and is important to explain the level of yields, and that gaussian models without jumps and with constant intensity jumps are good to price Asian options.

Estimating and forecasting the volatility of Brazilian finance series using arch models (Preliminary Version)

The goal of this paper is to present a comprehensive emprical analysis of the return and conditional variance of four Brazilian …nancial series using models of the ARCH class. Selected models are then compared regarding forecasting accuracy and goodness-of-…t statistics. To help understanding the empirical results, a self-contained theoretical discussion of ARCH models is also presented in such a way that it is useful for the applied researcher. Empirical results show that although all series share ARCH and are leptokurtic relative to the Normal, the return on the US$ has clearly regime switching and no asymmetry for the variance, the return on COCOA has no asymmetry, while the returns on the CBOND and TELEBRAS have clear signs of asymmetry favoring the leverage e¤ect. Regarding forecasting, the best model overall was the EGARCH(1; 1) in its Gaussian version. Regarding goodness-of-…t statistics, the SWARCH model did well, followed closely by the Student-t GARCH(1; 1)

The dorsal raphe nucleus exerts opposed control on generalized anxiety and panic-related defensive responses in rats

It has been proposed that the ascending dorsal raphe (DR)-serotonergic (5-HT) pathway facilitates conditioned avoidance responses to potential or distal threat, while the DR-periventricular 5-HT pathway inhibits unconditioned flight reactions to proximal danger. Dysfunction on these pathways would be, respectively, related to generalized anxiety (GAD) and panic disorder (PD). To investigate this hypothesis, we microinjected into the rat DR the benzodiazepine inverse receptor agonist FG 7142, the 5-HT1A receptor agonist 8-OH-DPAT or the GABA(A) receptor agonist muscimol. Animals were evaluated in the elevated T-maze (ETM) and light/dark transition test. These models generate defensive responses that have been related to GAD and PD. Experiments were also conducted in the ETM 14 days after the selective lesion of DR serotonergic neurons by 5,7-dihydroxytriptamine (DHT). In all cases, rats were pre-exposed to one of the open arms of the ETM 1 day before testing. The results showed that FG 7142 facilitated inhibitory avoidance, an anxiogenic effect, while impairing one-way escape, an anxiolytic effect. 8-OH-DPAT, muscimol, and 5,7-DHT-induced lesions acted in the opposite direction, impairing inhibitory avoidance while facilitating one-way escape from the open arm. In the light/dark transition, 8-OH-DPAT and muscimol increased the time spent in the lighted compartment, an anxiolytic effect. The data supports the view that distinct DR-5-HT pathways regulate neural mechanisms underlying GAD and PD. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Characteristics of family nucleus as correlates of regular participation in sports among adolescents

Objectives To estimate the relationship between family nucleus and sport practice among adolescents.Methods A school-based cross-sectional study carried out with 1,752 Brazilian adolescents (812 male and 940 female), aged 11-17 years. Characteristics of the family nucleus (parental education, socioeconomic status and number of siblings) and sport practice (>= 240 min/week) were assessed by questionnaires. Adjusted prevalence ratios were estimated using Poisson regression models.Results The overall prevalence of sport practice was 14.8% (boys 21.2% and girls 9.4%, P = 0.001). Higher socioeconomic status, number of siblings and parents' educational level were associated with more sport practice.Conclusion Despite the low engagement, family nucleus plays an essential role in the sport practice of our sample of Brazilian adolescents.

Serotonergic mechanisms of the lateral parabrachial nucleus on DOCA-induced sodium intake

It has been shown that the serotonergic mechanisms of the lateral parabrachial nucleus (LPBN) inhibit NaCl intake in different models of angiotensin II (ANG II)-dependent NaCl intake in rats. However, there is no information about the involvement of LPBN serotonergic mechanisms on NaCl intake in a model of NaCl intake not dependent on ANG II like deoxycorticosterone (DOCA)-induced NaCl intake. Therefore, in this study we investigated the effects of bilateral injections of serotonergic agonist and antagonist into the LPBN on DOCA-induced 1.8% NaCl intake in rats. Male Holtzman rats were treated with s.c. DOCA (10 mg/rat each every 3 days). After a period of training, in which the rats had access to 1.8% NaCI during 2 h for several days, the rats were implanted with stainless steel cannulas bilaterally into the LPBN. Bilateral injections of the serotonergic receptor antagonist methysergide (4 mug/0.2 mul each site) in the LPBN increased 1.8% NaCI intake (32.2+/-3.9 versus vehicle: 15.0+/-1.6 ml/2 h, n = 10) and water intake (11.5+/-3.5 versus vehicle: 3.2+/-1.0 ml/2 h). Injections of the serotonergic 5HT(2A/2C) receptor agonist DOI (5 mug/0,2 mul each site) in the LPBN reduced 1.8% NaCl intake (6.8+/-1.7 versus saline: 12.4+/-1.9 ml/2 h, n = 10) and water intake (2.2+/-0.8 versus saline: 4.4+/-1.0 ml/2 h). Besides the previously demonstrated importance for the control of ANG II-dependent water and NaCl intake, the data show that the serotonergic inhibitory mechanisms of the LPBN are also involved in the control of DOCA-induced NaCl intake. (C) 2000 Elsevier B.V. B.V. All rights reserved.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

EXOTIC CARBON SYSTEMS IN TWO-NEUTRON HALO THREE-BODY MODELS

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

Serotonergic mechanisms of the lateral parabrachial nucleus and cholinergic-induced sodium appetite

Central cholinergic mechanisms are suggested to participate in osmoreceptor-induced water intake. Therefore, central injections of the cholinergic agonist carbachol usually produce water intake (i.e., thirst) and are ineffective in inducing the intake of hypertonic saline solutions (i.e., the operational definition of sodium appetite). Recent studies have indicated that bilateral injections of the serotonin receptor antagonist methysergide into the lateral parabrachial nucleus (LPBN) markedly increases salt intake in models involving the activation of the renin-angiotensin system or mineralocorticoid hormones. The present studies investigated whether sodium appetite could be induced by central cholinergic activation with carbachol (an experimental condition where only water is typically ingested) after the blockade of LPBN serotonergic mechanisms with methysergide treatment in rats. When administered intracerebroventricularly in combination with injections of vehicle into both LPBN, carbachol (4 nmol) caused water drinking but insignificant intake of hypertonic saline. In contrast, after bilateral LPBN injections of methysergide (4 mug), intracerebroventricular carbachol induced the intake of 0.3 M NaCl. Water intake stimulated by intracerebroventricular carbachol was not changed by LPBN methysergide injections. The results indicate that central cholinergic activation can induce marked intake of hypertonic NaCl if the inhibitory serotonergic mechanisms of the LPBN are attenuated.

Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC

Linear mixed effects models are frequently used to analyse longitudinal data, due to their flexibility in modelling the covariance structure between and within observations. Further, it is easy to deal with unbalanced data, either with respect to the number of observations per subject or per time period, and with varying time intervals between observations. In most applications of mixed models to biological sciences, a normal distribution is assumed both for the random effects and for the residuals. This, however, makes inferences vulnerable to the presence of outliers. Here, linear mixed models employing thick-tailed distributions for robust inferences in longitudinal data analysis are described. Specific distributions discussed include the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted, and the Gibbs sampler and the Metropolis-Hastings algorithms are used to carry out the posterior analyses. An example with data on orthodontic distance growth in children is discussed to illustrate the methodology. Analyses based on either the Student-t distribution or on the usual Gaussian assumption are contrasted. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process for modelling distributions of the random effects and of residuals in linear mixed models, and the MCMC implementation allows the computations to be performed in a flexible manner.

Spatial variability models of CO2 emissions from soils colonized by grass (Deschampsia antarctica) and moss (Sanionia uncinata) in Admiralty Bay, King George Island

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Deformed Gaussian orthogonal ensemble and the statistical fluctuations in the spectra of the quartic oscillator

The nearest-neighbor spacing distributions proposed by four models, namely, the Berry-Robnik, Caurier-Grammaticos-Ramani, Lenz-Haake, and the deformed Gaussian orthogonal ensemble, as well as the ansatz by Brody, are applied to the transition between chaos and order that occurs in the isotropic quartic oscillator. The advantages and disadvantages of these five descriptions are discussed. In addition, the results of a simple extension of the expression for the Dyson-Mehta statistic Δ3 are compared with those of a more popular one, usually associated with the Berry-Robnik formalism. ©1999 The American Physical Society.

Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation

Linear mixed effects models have been widely used in analysis of data where responses are clustered around some random effects, so it is not reasonable to assume independence between observations in the same cluster. In most biological applications, it is assumed that the distributions of the random effects and of the residuals are Gaussian. This makes inferences vulnerable to the presence of outliers. Here, linear mixed effects models with normal/independent residual distributions for robust inferences are described. Specific distributions examined include univariate and multivariate versions of the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted and Markov chain Monte Carlo is used to carry out the posterior analysis. The procedures are illustrated using birth weight data on rats in a texicological experiment. Results from the Gaussian and robust models are contrasted, and it is shown how the implementation can be used for outlier detection. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process in linear mixed models, and they are easily implemented using data augmentation and MCMC techniques.