On the two point Padé table for a distribution

Some additional recurrence relations for the denominator polynomials of two point Padé approximants are derived. An example in which the coefficients of one of the two series, from which the Padé approximants are derived, are moments of a distribution is considered. For this example, properties of the denominator polynomials, and their zeros, are described.

Structural reforms, macroeconomic fluctuations and income distribution in Brazil

Includes bibliography

Intraoral schwannomas: Presentation of a series of 12 cases

Introduction: Schwannomas are benign and not very frequent tumors of the peripheral nerves, derived from the nerve supporting Schwann cells. Study Design: Data were collected on the clinical manifestations (sex, age), location, size and symptonts of the lesions as well as the evolution time and the initial (presumption) diagnosis. Results: Twelve patients were documented, with a mean age of 29,5 ± 12,1 years (range 16-50) and a balanced gender distribution. The mean duration of the lesions was 42,17± 45,3 months. The lesion located in the floor of the mouth was the largest tumor, measuring about 4 cm in maximum diameter, while the average size of the 12 schwannomas was 2.04± 1.1 cm. Conclusion: We present 12 oral schwannomas diagnosed and treated over a period of 10 years. © Medicina Oral S. L. C.I.F. B 96689336 - eISSN: 1989-5488.

Modelagem de comunicações móveis com a utilização de series temporais e geoestatísticas

O presente trabalho apresenta os resultados da modelagem de canal de propagação baseado em séries temporais multivariadas com a utilização de dados coletados em campanhas de medição e as principais características da urbanização de onze vias do centro da cidade de Belém-Pa. Modelos de função de transferência foram utilizados para avaliar efeitos na série temporal da potência do sinal recebido (dBm) que foi utilizada como variável resposta e como variáveis explicativas a altura dos prédios e as distâncias entre os prédios. Como nos modelos em séries temporais desconsideram-se as possíveis correlações entre amostras vizinhas, utilizou-se um modelo geoestatístico para se estabelecer a correção do erro deste modelo. Esta fase do trabalho consistiu em um conjunto de procedimentos necessários às técnicas geoestatísticas. Tendo como objetivo a análise em duas dimensões para dados espacialmente distribuídos, no que diz respeito à interpolação de superfícies geradas a partir das mostras georreferenciadas obtidas dos resíduos da potência do sinal recebido calculados com o modelo em séries temporais. Os resultados obtidos com o modelo proposto apresentam um bom desempenho, com erro médio quadrático na ordem de 0,33 dB em relação ao sinal medido, considerando os dados das onze vias do centro urbano da cidade de Belém/Pa. A partir do mapa de distribuição espacial da potência do sinal recebido (dBm), pode se identificar com facilidade as zonas infra ou supra dimensionadas em termos desta variável, isto é, beneficiadas ou prejudicadas com relação a recepção do sinal, o que pode resultar em um maior investimento da operadora (concessionária de telefonia celular móvel) local naquelas regiões onde o sinal é fraco.

Determinação de vazões extremas para diversos períodos de retorno para o Rio Paraguai utilizando métodos estatísticos

No presente trabalho foram analisadas as distribuições de probabilidade teórica Normal, Log-Normal, Exponencial, Gama e Weibull, para estimar as vazões máximas e mínimas anuais para o rio Paraguai, utilizando dados de uma estação fluviométrica localizado na cidade de Cáceres-MT. Os testes de Kolmogorov-Smirnov e Qui-Quadrado foram utilizados para verificar a aderência das probabilidades estimadas às freqüências observadas. A série utilizada compreende vazões máximas e mínimas anuais dos anos de 1966 a 2003, excluindo- se dados com falhas. Verificou-se que o melhor ajuste dos valores anuais de vazão máximas e mínimas são referentes a distribuição Gama e Weibull, respectivamente, conforme demonstrado pelo teste de Kolmogorov-Smirnov. Palavras-chave: Previsão de Vazão, teste de aderência.

The bias in reversing the Box-Cox transformation in time series forecasting: An empirical study based on neural networks

The Box-Cox transformation is a technique mostly utilized to turn the probabilistic distribution of a time series data into approximately normal. And this helps statistical and neural models to perform more accurate forecastings. However, it introduces a bias when the reversion of the transformation is conducted with the predicted data. The statistical methods to perform a bias-free reversion require, necessarily, the assumption of Gaussianity of the transformed data distribution, which is a rare event in real-world time series. So, the aim of this study was to provide an effective method of removing the bias when the reversion of the Box-Cox transformation is executed. Thus, the developed method is based on a focused time lagged feedforward neural network, which does not require any assumption about the transformed data distribution. Therefore, to evaluate the performance of the proposed method, numerical simulations were conducted and the Mean Absolute Percentage Error, the Theil Inequality Index and the Signal-to-Noise ratio of 20-step-ahead forecasts of 40 time series were compared, and the results obtained indicate that the proposed reversion method is valid and justifies new studies. (C) 2014 Elsevier B.V. All rights reserved.

Spatial distribution of the daily precipitation concentration index in Algeria

In this paper, the spatial and temporal distribution of the daily precipitation concentration index (CI) in Algeria (south Mediterranean Sea) has been assessed. CI is an index related to the rainfall intensity and erosive capacity; therefore, this index is of great interest for studies on torrential rainfall and floods. Forty-two daily rainfall series based on high-quality and fairly regular rainfall records for the period from 1970 to 2008 were used. The daily precipitation CI results allowed the identification of three climate zones: the northern country, characterized by coastal regions with CI values between 0.59 and 0.63; the highlands, with values between 0.57 and 0.62, except for the region of Biskra (CI = 0.70); and the southern region of the country, with high rainfall concentrations with values between 0.62 and 0.69.

A matheuristic for the selection of beam directions and dose distribution in radiotherapy planning

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Distribution of Abacion texense (Loomis, 1937), the only milliped species traversing the Rio Grande, Mississippi, and Pecos rivers (Callipodida: Abacionidae)

Localities are documented for the milliped Abacion texense (Loomis, 1837) (Callipodida: Abacionidae) whose distribution forms both the northern and southern ordinal limits in the Western Hemisphere. The westernmost component of Abacion Rafinesque, 1820, A. texense is the only milliped species whose range spans the Mississippi and Pecos rivers and the Rio Grande. Distribution extremes are in Hennepin County (Co.), Minnesota, in the north; Terrell and Potter cos., Texas, in the west; Alcorn Co., Mississippi, in the east; and southwestern Tamaulipas, Mexico, in the south. Occurrences are projected for southeastern South Dakota, northwestern Alabama, and the southwestern periphery of Tennessee. The type series of A. texense consists solely of the male holotype, so a neotype will be needed if this individual is ever lost, because no paratypes were officially designated.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

Global pharmacogenomics: Impact of population diversity on the distribution of polymorphisms in the CYP2C cluster among Brazilians

The impact of biogeographical ancestry, self-reported 'race/color' and geographical origin on the frequency distribution of 10 CYP2C functional polymorphisms (CYP2C8*2, *3, *4, CYP2C9*2, *3, *5, *11, CYP2C19*2, *3 and *17) and their haplotypes was assessed in a representative cohort of the Brazilian population (n = 1034). TaqMan assays were used for allele discrimination at each CYP2C locus investigated. Individual proportions of European, African and Amerindian biogeographical ancestry were estimated using a panel of insertion-deletion polymorphisms. Multinomial log-linear models were applied to infer the statistical association between the CYP2C alleles and haplotypes (response variables), and biogeographical ancestry, self-reported Color and geographical origin (explanatory variables). The results showed that CYP2C19*3, CYP2C9*5 and CYP2C9*11 were rare alleles (<1%), the frequency of other variants ranged from 3.4% (CYP2C8*4) to 17.3% (CYP2C19*17). Two distinct haplotype blocks were identified: block 1 consists of three single nucleotide polymorphisms (SNPs) (CYP2C19*17, CYP2C19*2 and CYP2C9*2) and block 2 of six SNPs (CYP2C9*11, CYP2C9*3, CYP2C9*5, CYP2C8*2, CYP2C8*4 and CYP2C8*3). Diplotype analysis generated 41 haplotypes, of which eight had frequencies greater than 1% and together accounted for 96.4% of the overall genetic diversity. The distribution of CYP2C8 and CYP2C9 (but not CYP2C19) alleles, and of CYP2C haplotypes was significantly associated with self-reported Color and with the individual proportions of European and African genetic ancestry, irrespective of Color self-identification. The individual odds of having alleles CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3, and haplotypes including these alleles, varied continuously as the proportion of European ancestry increased. Collectively, these data strongly suggest that the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of pharmacogenomic studies of the CYP2C cluster in order to avoid spurious conclusions based on improper matching of study cohorts. This conclusion extends to other polymorphic pharmacogenes among Brazilians, and most likely to other admixed populations of the Americas. The Pharmacogenomics Journal (2012) 12, 267-276; doi: 10.1038/tpj.2010.89; published online 21 December 2010

Residence Time Distribution Models Derived from Non-Ideal Laminar Velocity Profiles in Tubes

The theoretical E-curve for the laminar flow of non-Newtonian fluids in circular tubes may not be accurate for real tubular systems with diffusion, mechanical vibration, wall roughness, pipe fittings, curves, coils, or corrugated walls. Deviations from the idealized laminar flow reactor (LFR) cannot be well represented using the axial dispersion or the tanks-in-series models of residence time distribution (RTD). In this work, four RTD models derived from non-ideal velocity profiles in segregated tube flow are proposed. They were used to represent the RTD of three tubular systems working with Newtonian and pseudoplastic fluids. Other RTD models were considered for comparison. The proposed models provided good adjustments, and it was possible to determine the active volumes. It is expected that these models can be useful for the analysis of LFR or for the evaluation of continuous thermal processing of viscous foods.

A log-Birnbaum-Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.

The log-exponentiated generalized gamma regression model for censored data

For the first time, we introduce a generalized form of the exponentiated generalized gamma distribution [Cordeiro et al. The exponentiated generalized gamma distribution with application to lifetime data, J. Statist. Comput. Simul. 81 (2011), pp. 827-842.] that is the baseline for the log-exponentiated generalized gamma regression model. The new distribution can accommodate increasing, decreasing, bathtub- and unimodal-shaped hazard functions. A second advantage is that it includes classical distributions reported in the lifetime literature as special cases. We obtain explicit expressions for the moments of the baseline distribution of the new regression model. The proposed model can be applied to censored data since it includes as sub-models several widely known regression models. It therefore can be used more effectively in the analysis of survival data. We obtain maximum likelihood estimates for the model parameters by considering censored data. We show that our extended regression model is very useful by means of two applications to real data.

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.