A compound class of Weibull and power series distributions

In this paper we introduce the Weibull power series (WPS) class of distributions which is obtained by compounding Weibull and power series distributions where the compounding procedure follows same way that was previously carried out by Adamidis and Loukas (1998) This new class of distributions has as a particular case the two-parameter exponential power series (EPS) class of distributions (Chahkandi and Gawk 2009) which contains several lifetime models such as exponential geometric (Adamidis and Loukas 1998) exponential Poisson (Kus 2007) and exponential logarithmic (Tahmasbi and Rezaei 2008) distributions The hazard function of our class can be increasing decreasing and upside down bathtub shaped among others while the hazard function of an EPS distribution is only decreasing We obtain several properties of the WPS distributions such as moments order statistics estimation by maximum likelihood and inference for a large sample Furthermore the EM algorithm is also used to determine the maximum likelihood estimates of the parameters and we discuss maximum entropy characterizations under suitable constraints Special distributions are studied in some detail Applications to two real data sets are given to show the flexibility and potentiality of the new class of distributions (C) 2010 Elsevier B V All rights reserved

Asymptotic skewness in Birnbaum-Saunders nonlinear regression models

The family of distributions proposed by Birnbaum and Saunders (1969) can be used to model lifetime data and it is widely applicable to model failure times of fatiguing materials. We give a simple matrix formula of order n(-1/2), where n is the sample size, for the skewness of the distributions of the maximum likelihood estimates of the parameters in Birnbaum-Saunders nonlinear regression models, recently introduced by Lemonte and Cordeiro (2009). The formula is quite suitable for computer implementation, since it involves only simple operations on matrices and vectors, in order to obtain closed-form skewness in a wide range of nonlinear regression models. Empirical and real applications are analyzed and discussed. (C) 2010 Elsevier B.V. All rights reserved.

Birnbaum-Saunders nonlinear regression models

We introduce, for the first time, a new class of Birnbaum-Saunders nonlinear regression models potentially useful in lifetime data analysis. The class generalizes the regression model described by Rieck and Nedelman [Rieck, J.R., Nedelman, J.R., 1991. A log-linear model for the Birnbaum-Saunders distribution. Technometrics 33, 51-60]. We discuss maximum-likelihood estimation for the parameters of the model, and derive closed-form expressions for the second-order biases of these estimates. Our formulae are easily computed as ordinary linear regressions and are then used to define bias corrected maximum-likelihood estimates. Some simulation results show that the bias correction scheme yields nearly unbiased estimates without increasing the mean squared errors. Two empirical applications are analysed and discussed. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Bias correction in a multivariate normal regression model with general parameterization

This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.

Modelagem e estimação de parâmetros genéticos e fenotípicos para pesos do nascimento à seleção (378 dias) de machos Nelore

Genetic parameters for weights (17, 942 records), obtained in intervals of 60 days, from the birth to selection (378 days of age), of 2,582 males of the Nellore breed was estimated in univariate analyses by the Maximum Restricted Likelihood method. The models of analysis models included the fixed effects of contemporary groups, month of birth, mother age and age when the weights were collected as covariate. Three models differing in random effects were tested: the model 1 (M1) was adjusted for the direct and maternal addictive genetic effects and maternal permanent environment; in model 2 (M2) the maternal genetic effect was excluded; and the model 3 (M3) was only adjusted for the direct addictive genetic effect. The test of likelihood (LRT) detected significant differences, for all the ages, of M2 and M1 in relation to the simple model (M3), evidencing the importance of the maternal effects. Except for the birth weight (0.40), low values (0.05 to 0.12) of h(2) were found for M1 and M2 until 8 months of age and, after this period, reasonable increase could be observed, reaching 0.28 until 13 months of age. The estimates of the total variance fraction, due to the effect of maternal permanent environment, were high and practically became unaffected between the models 1 and 2. Maternal effects, not necessarily decomposed (in genetic addictive and permanent environment), affected the Nellore males growth. Models that contemplate maternal effects, besides the genetic addictive direct effects, are more realistic to describe the trajectory of the variances in the initial phases of growth of Nelore male calves.

Parâmetros genéticos para diferentes relações de peso ao nascer e à desmama em vacas da raça Nelore

O presente estudo foi desenvolvido com o objetivo de estimar herdabilidade e repetibilidade para diferentes medidas de eficiência produtiva de vacas e determinar a melhor maneira de calcular as relações de peso, visando a sua utilização como critério de seleção em rebanhos da raça Nelore. Os dados analisados são de animais da raça Nelore, pertencentes ao Projeto de Seleção das Raças Zebuínas e Caracu do Centro APTA Bovinos de Corte, do Instituto de Zootecnia de Sertãozinho. Os animais são selecionados para maior peso ao sobreano (rebanhos NeS e NeT, analisados como um único rebanho) e para peso ao sobreano próximo da média (NeC) do grupo de contemporâneos, desde 1980. As características utilizadas no estudo foram: 1) RPN = relação de peso ao nascer do bezerro / peso da vaca ao parto; 2) RPN2 = relação do peso ao nascer do bezerro / peso metabólico da vaca ao parto; 3) RPD = relação de peso à desmama do bezerro / peso da vaca à desmama; e 4) RPD2 = relação do peso à desmama do bezerro / peso metabólico da vaca à desmama. Os parâmetros genéticos foram estimados considerando dois arquivos: vacas com bezerros (CB) e vacas com e sem bezerros (SB). A RPN e a RPN2 foram calculadas somente no arquivo CB, enquanto que RPD e RPD2 foram calculadas em ambos os arquivos (CB e SB). Os parâmetros genéticos foram estimados pelo método da máxima verossimilhança restrita. As estimativas de herdabilidade para as características RPN; RPN2; RPD_CB; RPD2_CB; RPD_SB e RPD2_SB foram: 0,17±0,02; 0,16±0,02; 0,22±0,04; 0,19±0,03; 0,20±0,01 e 0,16±0,01, respectivamente. As repetibilidades estimadas variaram de 0,22 a 0,68. A utilização das relações de peso como critério de seleção deve promover, a longo prazo, melhorias na eficiência produtiva das vacas. As relações de peso têm sido consideradas apenas como informações para o descarte de vacas em alguns programas de seleção, mas poderiam ser incluídas em índices de seleção, principalmente quando calculada considerando o peso metabólico da vaca à desmama, incluindo tanto as vacas que desmamaram um bezerro, quanto aquelas que falharam em desmamar.

Estudo das precipitações máximas anuais em Presidente Prudente

Considerando a importância sócio-econômica da região de Presidente Prudente, este estudo teve como objetivo estimar a precipitação pluvial máxima esperada para diferentes níveis de probabilidade e verificar o grau de ajuste dos dados ao modelo Gumbel, com as estimativas dos parâmetros obtidas pelo método de máxima verossimilhança. Pelos resultados, o teste de Kolmogorov-Sminorv (K-S) mostrou que a distribuição Gumbel testada se ajustou com p-valor maior que 0.28 para todos os períodos de tempo considerados, comprovando que a distribuição Gumbel apresenta um bom ajustamento aos dados observados para representar as precipitações pluviais máximas. As estimativas de precipitação obtidas pelo método de máxima verossimilhança são consistentes, conseguindo reproduzir com bastante fidelidade o regime de chuvas da região de Presidente Prudente. Assim, o conhecimento da distribuição da precipitação pluvial máxima mensal e das estimativas das precipitações diárias máximas esperadas, possibilita um planejamento estratégico melhor, minimizando assim o risco de ocorrência de perdas econômicas para essa região.

Evaluación genética de búfalos de la raza Murrah para la producción de leche en el día de control y a los 305 días de lactancia

There were analyzed 4757 complete lactations of the Murrah breed, daughters of 187 bulls, with the goal of verifying the viability upon employing the test-day (PDLC), on substitution of the milk yield at 305th day of lactation (PL305), in the genetic evaluations. The components of variance for the PDLC1 to PDLC9 and for the PL305 were estimated in uni-traits analysis according to maximum restricted likelihood method. The used model included the genetic direct additive random effects, of residual and permanent environment. There were considered as fixed effects, the contemporary group and the number of milkings and the age of the cow at the moment of parity co-variable (quadratic and linear effect). The contemporary groups were constituted by the herd-year-month of control for the PDLC and by herd-year-epoch of parity for PL305. The estimates of heritability for the PDLC and PL305 were 0.12 to 0.23 and 0.22, respectively. The correlations of order of the predicted genetic values for the 187 bulls, obtained between the PDLC and the PL305, were from moderate to high, varying from 67.74 to 83.12. From the minimum selection of the 10% of the best bulls relating to the predicted genetic value for the PL305, the coincidence among the classification of these animals was over 68%, when evaluated by the PDLC3,PDLC4,PDLC5 and PDLC6. Upon selecting the 5% of the best animals that coincidence presented a lower value.

The Poisson-exponential lifetime distribution

In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. © 2010 Elsevier B.V. All rights reserved.

Comparação entre metodologias para avaliar a idade à primeira concepção em éguas puro-sangue inglês

In Brazil, due to the breeding season for Thoroughbred, the reproductive data are normally truncate, since the breeders try to get animals that were born at the beginning of the breeding season in order to take their competitive advantages (more developed, mature and trained animals) compared to animals born later in the same breeding season. To analyze these data suitable methods should be used. Then, this paper aims to compare three methodologies: the method of maximum restricted likelihood, using MTDFREML, bayesian analysis without censured data by software MTGSAM and bayesian analysis with censured data by software LMCD, to evaluate age at first conception in thoroughbred mares, in order to verify its impact on the choice of stallions during selection. The database contained 3509 records for age at first conception (months) for thoroughbred mares. The heritability estimates were 0.23, 0.30 and 0.0926 (log scale), for MTDF, MTGSAM and LMCD, respectively. Considering all animals in the pedigree (6713), ranking correlations varied from 0.91 to 0.99. When only stallions were considered (656), those varied from 0.48 to 0.99 (considering different percentages of selected males) between evalua-tion methods. The highest changes in the general classification were observed when LMCD was compared to the other two methods. As the linear censured model is the most suitable for trait analysis with censured data, it was observed that censure information would lead to the choice of different animals during the selection process, when compared to the two other methodologies.

Análise genética de características de crescimento e de carcaça em bovinos Nelore

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Influências multi-escala da paisagem e limiar da fragmentação em morcegos no cerrado

Pós-graduação em Ciências Biológicas (Zoologia) - IBRC

A novel linkage map of sugarcane with evidence for clustering of retrotransposon-based markers

Background: The development of sugarcane as a sustainable crop has unlimited applications. The crop is one of the most economically viable for renewable energy production, and CO2 balance. Linkage maps are valuable tools for understanding genetic and genomic organization, particularly in sugarcane due to its complex polyploid genome of multispecific origins. The overall objective of our study was to construct a novel sugarcane linkage map, compiling AFLP and EST-SSR markers, and to generate data on the distribution of markers anchored to sequences of scIvana_1, a complete sugarcane transposable element, and member of the Copia superfamily. Results: The mapping population parents ('IAC66-6' and 'TUC71-7') contributed equally to polymorphisms, independent of marker type, and generated markers that were distributed into nearly the same number of co-segregation groups (or CGs). Bi-parentally inherited alleles provided the integration of 19 CGs. The marker number per CG ranged from two to 39. The total map length was 4,843.19 cM, with a marker density of 8.87 cM. Markers were assembled into 92 CGs that ranged in length from 1.14 to 404.72 cM, with an estimated average length of 52.64 cM. The greatest distance between two adjacent markers was 48.25 cM. The scIvana_1-based markers (56) were positioned on 21 CGs, but were not regularly distributed. Interestingly, the distance between adjacent scIvana_1-based markers was less than 5 cM, and was observed on five CGs, suggesting a clustered organization. Conclusions: Results indicated the use of a NBS-profiling technique was efficient to develop retrotransposon-based markers in sugarcane. The simultaneous maximum-likelihood estimates of linkage and linkage phase based strategies confirmed the suitability of its approach to estimate linkage, and construct the linkage map. Interestingly, using our genetic data it was possible to calculate the number of retrotransposonscIvana_1 (similar to 60) copies in the sugarcane genome, confirming previously reported molecular results. In addition, this research possibly will have indirect implications in crop economics e. g., productivity enhancement via QTL studies, as the mapping population parents differ in response to an important fungal disease.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.