Aquisição fonológica de fricativas por crianças com transtorno fonológico: uma investigação acústica

Pós-graduação em Estudos Linguísticos - IBILCE

Usinabilidade e integridade superficial de implantes dentários

Pós-graduação em Engenharia Mecânica - FEIS

The Kumaraswamy Gumbel distribution

The Gumbel distribution is perhaps the most widely applied statistical distribution for problems in engineering. We propose a generalization-referred to as the Kumaraswamy Gumbel distribution-and provide a comprehensive treatment of its structural properties. We obtain the analytical shapes of the density and hazard rate functions. We calculate explicit expressions for the moments and generating function. The variation of the skewness and kurtosis measures is examined and the asymptotic distribution of the extreme values is investigated. Explicit expressions are also derived for the moments of order statistics. The methods of maximum likelihood and parametric bootstrap and a Bayesian procedure are proposed for estimating the model parameters. We obtain the expected information matrix. An application of the new model to a real dataset illustrates the potentiality of the proposed model. Two bivariate generalizations of the model are proposed.

Computational tools for comparing asymmetric GARCH models via Bayes factors

In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into a continuous unimodal and symmetric distribution. For each model we compute an approximation to the marginal likelihood, based on the MCMC output. From these approximations we compute Bayes factors and posterior model probabilities. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

Generalized beta-generated distributions

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets. (c) 2011 Elsevier B.V. All rights reserved.

Understanding bias in geographic range size estimates

Aim Estimates of geographic range size derived from natural history museum specimens are probably biased for many species. We aim to determine how bias in these estimates relates to range size. Location We conducted computer simulations based on herbarium specimen records from localities ranging from the southern United States to northern Argentina. Methods We used theory on the sampling distribution of the mean and variance to develop working hypotheses about how range size, defined as area of occupancy (AOO), was related to the inter-specific distribution of: (1) mean collection effort per area across the range of a species (MC); (2) variance in collection effort per area across the range of a species (VC); and (3) proportional bias in AOO estimates (PBias: the difference between the expected value of the estimate of AOO and true AOO, divided by true AOO). We tested predictions from these hypotheses using computer simulations based on a dataset of more than 29,000 herbarium specimen records documenting occurrences of 377 plant species in the tribe Bignonieae (Bignoniaceae). Results The working hypotheses predicted that the mean of the inter-specific distribution of MC, VC and PBias were independent of AOO, but that the respective variance and skewness decreased with increasing AOO. Computer simulations supported all but one prediction: the variance of the inter-specific distribution of VC did not decrease with increasing AOO. Main conclusions Our results suggest that, despite an invariant mean, the dispersion and symmetry of the inter-specific distribution of PBias decreases as AOO increases. As AOO increased, range size was less severely underestimated for a large proportion of simulated species. However, as AOO increased, range size estimates having extremely low bias were less common.

A quantitative approach to evolution of music and philosophy

The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

Likelihood-based inference for power distributions

This paper considers likelihood-based inference for the family of power distributions. Widely applicable results are presented which can be used to conduct inference for all three parameters of the general location-scale extension of the family. More specific results are given for the special case of the power normal model. The analysis of a large data set, formed from density measurements for a certain type of pollen, illustrates the application of the family and the results for likelihood-based inference. Throughout, comparisons are made with analogous results for the direct parametrisation of the skew-normal distribution.

Genetica molecolare dell'autismo: studi di associazione ed analisi di geni candidati

Autism is a neurodevelpmental disorder characterized by impaired verbal communication, limited reciprocal social interaction, restricted interests and repetitive behaviours. Twin and family studies indicate a large genetic contribution to ASDs (Autism Spectrum Disorders). During my Ph.D. I have been involved in several projects in which I used different genetic approaches in order to identify susceptibility genes in autism on chromosomes 2, 7 and X: 1)High-density SNP association and CNV analysis of two Autism Susceptibility Loci. The International Molecular Genetic Study of Autism Consortium (IMGSAC) previously identified linkage loci on chromosomes 7 and 2, termed AUTS1 and AUTS5, respectively. In this study, we evaluated the patterns of linkage disequilibrium (LD) and the distribution of haplotype blocks, utilising data from the HapMap project, across the two strongest peaks of linkage on chromosome 2 and 7. More than 3000 SNPs have been selected in each locus in all known genes, as well as SNPs in non-genic highly conserved sequences. All markers have been genotyped to perform a high-density association analysis and to explore copy number variation within these regions. The study sample consisted of 127 and 126 multiplex families, showing linkage to the AUTS1 and AUTS5 regions, respectively, and 188 gender-matched controls. Association and CNV analysis implicated several new genes, including IMMP2L and DOCK4 on chromosome 7 and ZNF533 and NOSTRIN on the chromosome 2. Particularly, my contribution to this project focused on the characterization of the best candidate gene in each locus: On the AUTS5 locus I carried out a transcript study of ZNF533 in different human tissues to verify which isoforms and start exons were expressed. High transcript variability and a new exon, never described before, has been identified in this analysis. Furthermore, I selected 31 probands for the risk haplotype and performed a mutation screen of all known exons in order to identify novel coding variants associated to autism. On the AUTS1 locus a duplication was detected in one multiplex family that was transmitted from father to an affected son. This duplication interrupts two genes: IMMP2L and DOCK4 and warranted further analysis. Thus, I performed a screening of the cohort of IMGSAC collection (285 multiplex families), using a QMPSF assay (Quantitative Multiplex PCR of Short fluorescent Fragments) to analyse if CNVs in this genic region segregate with autism phenotype and compare their frequency with a sample of 475 UK controls. Evidence for a role of DOCK4 in autism susceptibility was supported by independent replication of association at rs2217262 and the finding of a deletion segregating in a sib-pair family. 2)Analysis of X chromosome inactivation. Skewed X chromosome inactivation (XCI) is observed in females carrying gene mutations involved in several X-linked syndromes. We aimed to estimate the role of X-linked genes in ASD susceptibility by ascertaining the XCI pattern in a sample of 543 informative mothers of children with ASD and in a sample of 164 affected girls. The study sample included families from different european consortia. I analysed the XCI inactivation pattern in a sample of italian mothers from singletons families with ASD and also a control groups (144 adult females and 40 young females). We observed no significant excess of skewed XCI in families with ASD. Interestingly, two mothers and one girl carrying known mutations in X-linked genes (NLGN3, ATRX, MECP2) showed highly skewed XCI, suggesting that ascertainment of XCI could reveal families with X-linked mutations. Linkage analysis was carried out in the subgroup of multiplex families with skewed XCI (≥80:20) and a modest increased allele sharing was obtained in the Xq27-Xq28 region, with a peak Z score of 1.75 close to rs719489. In this region FMR1 and MECP2 have been associated in some cases with austim and therefore represent candidates for the disorder. I performed a mutation screen of MECP2 in 33 unrelated probands from IMGSAC and italian families, showing XCI skewness. Recently, Xq28 duplications including MECP2, have been identified in families with MR, with asymptomatic carrier females showing extreme (>85%) skewing of XCI. For these reason I used the sample of probands from X-skewed families to perform CNV analysis by Real-time quantitative PCR. No duplications have been found in our sample. I have also confirmed all data using as alternative method the MLPA assay (Multiplex Ligation dependent Probe Amplification). 3)ASMT as functional candidate gene for autism. Recently, a possible involvement of the acetylserotonin O-methyltransferase (ASMT) gene in susceptibility to ASDs has been reported: mutation screening of the ASMT gene in 250 individuals from the PARIS collection revealed several rare variants with a likely functional role; Moreover, significant association was reported for two SNPs (rs4446909 and rs5989681) located in one of the two alternative promoters of the gene. To further investigate these findings, I carried out a replication study using a sample of 263 affected individuals from the IMGSAC collection and 390 control individuals. Several rare mutations were identified, including the splice site mutation IVS5+2T>C and the L326F substitution previously reported by Melke et al (2007), but the same rare variants have been found also in control individuals in our study. Interestingly, a new R319X stop mutation was found in a single autism proband of Italian origin and is absent from the entire control sample. Furthermore, no replication has been found in our case-control study typing the SNPs on the ASMT promoter B.

On the Efficiency of the Benchmarks Used in the Asset Management

In this work we studied the efficiency of the benchmarks used in the asset management industry. In chapter 2 we analyzed the efficiency of the benchmark used for the government bond markets. We found that for the Emerging Market Bonds an equally weighted index for the country weights is probably the more suited because guarantees maximum diversification of country risk but for the Eurozone government bond market we found a GDP weighted index is better because the most important matter is to avoid a higher weight for highly indebted countries. In chapter 3 we analyzed the efficiency of a Derivatives Index to invest in the European corporate bond market instead of a Cash Index. We can state that the two indexes are similar in terms of returns, but that the Derivatives Index is less risky because it has a lower volatility, has values of skewness and kurtosis closer to those of a normal distribution and is a more liquid instrument, as the autocorrelation is not significant. In chapter 4 it is analyzed the impact of fallen angels on the corporate bond portfolios. Our analysis investigated the impact of the month-end rebalancing of the ML Emu Non Financial Corporate Index for the exit of downgraded bond (the event). We can conclude a flexible approach to the month-end rebalancing is better in order to avoid a loss of valued due to the benchmark construction rules. In chapter 5 we did a comparison between the equally weighted and capitalization weighted method for the European equity market. The benefit which results from reweighting the portfolio into equal weights can be attributed to the fact that EW portfolios implicitly follow a contrarian investment strategy, because they mechanically rebalance away from stocks that increase in price.

Gold and the Stock Market: 3 Essays on Gold Investments

This thesis gives an overview of the history of gold per se, of gold as an investment good and offers some institutional details about gold and other precious metal markets. The goal of this study is to investigate the role of gold as a store of value and hedge against negative market movements in turbulent times. I investigate gold’s ability to act as a safe haven during periods of financial stress by employing instrumental variable techniques that allow for time varying conditional covariance. I find broad evidence supporting the view that gold acts as an anchor of stability during market downturns. During periods of high uncertainty and low stock market returns, gold tends to have higher than average excess returns. The effectiveness of gold as a safe haven is enhanced during periods of extreme crises: the largest peaks are observed during the global financial crises of 2007-2009 and, in particular, during the Lehman default (October 2008). A further goal of this thesis is to investigate whether gold provides protection from tail risk. I address the issue of asymmetric precious metal behavior conditioned to stock market performance and provide empirical evidence about the contribution of gold to a portfolio’s systematic skewness and kurtosis. I find that gold has positive coskewness with the market portfolio when the market is skewed to the left. Moreover, gold shows low cokurtosis with the market returns during volatile periods. I therefore show that gold is a desirable investment good to risk averse investors, since it tends to decrease the probability of experiencing extreme bad outcomes, and the magnitude of losses in case such events occur. Gold thus bears very important and under-researched characteristics as an asset class per se, which this thesis contributed to address and unveil.

Aerosol-cloud interactions studied with a chemistry-climate model

This study aims at a comprehensive understanding of the effects of aerosol-cloud interactions and their effects on cloud properties and climate using the chemistry-climate model EMAC. In this study, CCN activation is regarded as the dominant driver in aerosol-cloud feedback loops in warm clouds. The CCN activation is calculated prognostically using two different cloud droplet nucleation parameterizations, the STN and HYB CDN schemes. Both CDN schemes account for size and chemistry effects on the droplet formation based on the same aerosol properties. The calculation of the solute effect (hygroscopicity) is the main difference between the CDN schemes. The kappa-method is for the first time incorporated into Abdul-Razzak and Ghan activation scheme (ARG) to calculate hygroscopicity and critical supersaturation of aerosols (HYB), and the performance of the modied scheme is compared with the osmotic coefficient model (STN), which is the standard in the ARG scheme. Reference simulations (REF) with the prescribed cloud droplet number concentration have also been carried out in order to understand the effects of aerosol-cloud feedbacks. In addition, since the calculated cloud coverage is an important determinant of cloud radiative effects and is influencing the nucleation process two cloud cover parameterizations (i.e., a relative humidity threshold; RH-CLC and a statistical cloud cover scheme; ST-CLC) have been examined together with the CDN schemes, and their effects on the simulated cloud properties and relevant climate parameters have been investigated. The distinct cloud droplet spectra show strong sensitivity to aerosol composition effects on cloud droplet formation in all particle sizes, especially for the Aitken mode. As Aitken particles are the major component of the total aerosol number concentration and CCN, and are most sensitive to aerosol chemical composition effect (solute effect) on droplet formation, the activation of Aitken particles strongly contribute to total cloud droplet formation and thereby providing different cloud droplet spectra. These different spectra influence cloud structure, cloud properties, and climate, and show regionally varying sensitivity to meteorological and geographical condition as well as the spatiotemporal aerosol properties (i.e., particle size, number, and composition). The changes responding to different CDN schemes are more pronounced at lower altitudes than higher altitudes. Among regions, the subarctic regions show the strongest changes, as the lower surface temperature amplifies the effects of the activated aerosols; in contrast, the Sahara desert, where is an extremely dry area, is less influenced by changes in CCN number concentration. The aerosol-cloud coupling effects have been examined by comparing the prognostic CDN simulations (STN, HYB) with the reference simulation (REF). Most pronounced effects are found in the cloud droplet number concentration, cloud water distribution, and cloud radiative effect. The aerosol-cloud coupling generally increases cloud droplet number concentration; this decreases the efficiency of the formation of weak stratiform precipitation, and increases the cloud water loading. These large-scale changes lead to larger cloud cover and longer cloud lifetime, and contribute to high optical thickness and strong cloud cooling effects. This cools the Earth's surface, increases atmospheric stability, and reduces convective activity. These changes corresponding to aerosol-cloud feedbacks are also differently simulated depending on the cloud cover scheme. The ST-CLC scheme is more sensitive to aerosol-cloud coupling, since this scheme uses a tighter linkage of local dynamics and cloud water distributions in cloud formation process than the RH-CLC scheme. For the calculated total cloud cover, the RH-CLC scheme simulates relatively similar pattern to observations than the ST-CLC scheme does, but the overall properties (e.g., total cloud cover, cloud water content) in the RH simulations are overestimated, particularly over ocean. This is mainly originated from the difference in simulated skewness in each scheme: the RH simulations calculate negatively skewed distributions of cloud cover and relevant cloud water, which is similar to that of the observations, while the ST simulations yield positively skewed distributions resulting in lower mean values than the RH-CLC scheme does. The underestimation of total cloud cover over ocean, particularly over the intertropical convergence zone (ITCZ) relates to systematic defficiency of the prognostic calculation of skewness in the current set-ups of the ST-CLC scheme.rnOverall, the current EMAC model set-ups perform better over continents for all combinations of the cloud droplet nucleation and cloud cover schemes. To consider aerosol-cloud feedbacks, the HYB scheme is a better method for predicting cloud and climate parameters for both cloud cover schemes than the STN scheme. The RH-CLC scheme offers a better simulation of total cloud cover and the relevant parameters with the HYB scheme and single-moment microphysics (REF) than the ST-CLC does, but is not very sensitive to aerosol-cloud interactions.

Intra-subject variability in attention-deficit hyperactivity disorder

BACKGROUND: This study is based on a comprehensive survey of the neuropsychological attention-deficit hyperactivity disorder (ADHD) literature and presents the first psychometric analyses of different parameters of intra-subject variability (ISV) in patients with ADHD compared to healthy controls, using the Continuous Performance Test, a Go-NoGo task, a Stop Signal Task, as well as N-back tasks. METHODS: Data of 57 patients with ADHD and 53 age- and gender-matched controls were available for statistical analysis. Different parameters were used to describe central tendency (arithmetic mean, median), dispersion (standard deviation, coefficient of variation, consecutive variance), and shape (skewness, excess) of reaction time distributions, as well as errors (commissions and omissions). RESULTS: Group comparisons revealed by far the strongest effect sizes for measures of dispersion, followed by measures of central tendency, and by commission errors. Statistical control of ISV reduced group differences in the other measures substantially. One (patients) or two (controls) principal components explained up to 67% of the inter-individual differences in intra-individual variability. CONCLUSIONS: Results suggest that, across a variety of neuropsychological tests, measures of ISV contribute best to group discrimination, with limited incremental validity of measures of central tendency and errors. Furthermore, increased ISV might be a unitary construct in ADHD.

MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

Long-run performance of initial public offerings: The evidence for Switzerland

We estimate the underpricing and long-run performance of Swiss initial public offerings (IPOs) from 1983 to 2000. The average market adjusted initial return is 34.97%. To examine the long-run performance of Swiss IPOs, we compute buy-and-hold abnormal returns, skewness-adjusted wealth ratios, and cumulative abnormal returns using 120 months of secondary market returns. In contrast to previous findings for the U.S. and Germany, we do not find strong evidence for a distinct IPO effect. We attribute long-run underperformance to the fact that IPO firms tend to be small firms. It virtually vanishes when we use a small capitalization index as a benchmark. In spite of distinct economic implications and statistical properties, our basic results are similar for all performance measures applied.