882 resultados para Bayesian model selection
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Knowledge of genetic parameters is essential for improved reproductive management and increased yield. Quantitative analysis of genetic parameters is lacking for many breeds of buffaloes. This article provides the first estimate of genetic parameters for dual purpose (meat and milk) Brazilian Jaffarabadi buffaloes, using Bayesian inference. Data on milk yield (MY), lactation length (LL), weight at 205 days (W205) and 365 (W365) days of age, and average daily gain (ADG) from 205 to 365 days of age were collected in two herds. Bivariate analyses (using the program MTGSAM) were performed with the Gibbs sampler to obtain estimates of variance and covariance. Average lactation milk yield and lactation length were 1 620.2 +/- 450.9 kg and 257.6 +/- 46.8 days, respectively, and the mean values for weight traits (kg) were 181.6 +/- 63.3 (W205), 298.04 +/- 116.1 (W365), and 0.73 +/- 0.35 (ADG). Heritability estimates (modes) were 0.16 for MY, 0.10 for LL, 0.43 for W205, 0.48 for W365 and 0.32 for ADG. There was a high genetic correlation (0.96) between milk yield and lactation length and very high genetic correlations (0.99) between the three growth traits. Our data suggest that both milk production and growth traits have clear potential for yield improvement through direct selection in this dual purpose breed. The selection for weight at an early age would be successful and selection for MY can be performed in the first lactation.
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Scrotal circumference data from 47,605 Nellore young bulls, measured at around 18 mo of age (SC18), were analyzed simultaneously with 27,924 heifer pregnancy (HP) and 80,831 stayability (STAY) records to estimate their additive genetic relationships. Additionally, the possibility that economically relevant traits measured directly in females could replace SC18 as a selection criterion was verified. Heifer pregnancy was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 d. Females were exposed to sires for the first time at about 14 mo of age (between 11 and 16 mo). Stayability was defined as whether or not a cow calved every year up to 5 yr of age, when the opportunity to breed was provided. A Bayesian linear-threshold-threshold analysis via Gibbs sampler was used to estimate the variance and covariance components of the multitrait model. Heritability estimates were 0.42 +/- 0.01, 0.53 +/- 0.03, and 0.10 +/- 0.01, for SC18, HP, and STAY, respectively. The genetic correlation estimates were 0.29 +/- 0.05, 0.19 +/- 0.05, and 0.64 +/- 0.07 between SC18 and HP, SC18 and STAY, and HP and STAY, respectively. The residual correlation estimate between HP and STAY was -0.08 +/- 0.03. The heritability values indicate the existence of considerable genetic variance for SC18 and HP traits. However, genetic correlations between SC18 and the female reproductive traits analyzed in the present study can only be considered moderate. The small residual correlation between HP and STAY suggests that environmental effects common to both traits are not major. The large heritability estimate for HP and the high genetic correlation between HP and STAY obtained in the present study confirm that EPD for HP can be used to select bulls for the production of precocious, fertile, and long-lived daughters. Moreover, SC18 could be incorporated in multitrait analysis to improve the prediction accuracy for HP genetic merit of young bulls.
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An economic model including the labor resource and the process stage configuration is proposed to design g charts allowing for all the design parameters to be varied in an adaptive way. A random shift size is considered during the economic design selection. The results obtained for a benchmark of 64 process stage scenarios show that the activities configuration and some process operating parameters influence the selection of the best control chart strategy: to model the random shift size, its exact distribution can be approximately fitted by a discrete distribution obtained from a relatively small sample of historical data. However, an accurate estimation of the inspection costs associated to the SPC activities is far from being achieved. An illustrative example shows the implementation of the proposed economic model in a real industrial case. (C) 2011 Elsevier B.V. All rights reserved.
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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.
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This study aimed to use the generalized linear models with probit and logit link function to evaluate early pregnancy, and to observe the effects on genetic variability and on sire selection when different ages are adopted in the definition of this trait. Early pregnancy was studied at 15 (EP15), and 21 (EP21) months. The analysis was done in R software. Pearson correlations (PC), between genetic predicted values and percentage of bulls in common considering only 10% of bulls with higher genetic values (TOP 10), between classification by logit and probit models and in each model among EP15 and EP21, were calculated. The heritability for EP15 and EP21 were close between models, except for EP15 using probit link function. PC and TOP10 among models were high. The Akaike and Bayesian criteria reported was similar between models. TOP10, considering the same model, among EP15-EP21 were moderated between EP15-EP21.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We conducted a two-way selection experiment in a composite rabbit population to investigate the responses to selection for postweaning ADG and feed conversion (FC). Two generations of crossing, followed by four generations of random pair matings, preceded three generations of selection. Selection was practiced within four lines: high-feed conversion (HFC), low-feed conversion (LFC), high gain (HG), and low gain (LG). Data on 1,446 rabbits from the random mating and selection generations were fitted to an animal model to estimate heritabilities of and the genetic correlation between ADG and FC. The two-trait model included rabbit and common litter random effects and line, generation, and sex fixed effects. Estimates of heritability of ADG and FC were .48 and .29, respectively, and the genetic correlation between them was -.82. Common litter environmental effects accounted for a proportion of .11 and . 13 of the phenotypic variation of the two traits, respectively. For ADG (in g/d) the regressions of mean breeding values on generation number during the selection period were 1.23 ± .12 (P < .01) in the HG line and -.86 ± .12 (P < .01) in the LG line; the regressions for FC (in g feed/g gain) were -.07 ± .01 (P < .01) in the HFC line and .03 ± .01 (P < .05) in the LFC line. Selection for ADG was effective in improving ADG and FC.
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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.
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A total of 20,065 weights recorded on 3016 Nelore animals were used to estimate covariance functions for growth from birth to 630 days of age, assuming a parametric correlation structure to model within-animal correlations. The model of analysis included fixed effects of contemporary groups and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Genetic effects of the animal and its dam and maternal permanent environmental effects were modelled by random regressions on Legendre polynomials of age at recording. Changes in direct permanent environmental effect variances were modelled by a polynomial variance function, together with a parametric correlation function to account for correlations between ages. Stationary and nonstationary models were used to model within-animal correlations between different ages. Residual variances were considered homogeneous or heterogeneous, with changes modelled by a step or polynomial function of age at recording. Based on Bayesian information criterion, a model with a cubic variance function combined with a nonstationary correlation function for permanent environmental effects, with 49 parameters to be estimated, fitted best. Modelling within-animal correlations through a parametric correlation structure can describe the variation pattern adequately. Moreover, the number of parameters to be estimated can be decreased substantially compared to a model fitting random regression on Legendre polynomial of age. © 2004 Elsevier B.V. All rights reserved.
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The analysis of interactions between lineages at varying levels of genetic divergence can provide insights into the process of speciation through the accumulation of incompatible mutations. Ring species, and especially the Ensatina eschscholtzii system exemplify this approach. The plethodontid salamanders E. eschscholtzii xanthoptica and E. eschscholtzii platensis hybridize in the central Sierran foothills of California. We compared the genetic structure across two transects (southern and northern Calaveras Co.), one of which was resampled over 20 years, and examined diagnostic molecular markers (eight allozyme loci and mitochondrial DNA) and a diagnostic quantitative trait (color pattern). Key results across all studies were: (1) cline centers for all markers were coincident and the zones were narrow, with width estimates of 730 m to 2000 m; (2) cline centers at the northern Calaveras transect were coincident between 1981 and 2001, demonstrating repeatability over five generations; (3) there were very few if any putative F1s, but a relatively high number of backcrossed individuals in the central portion of transects: and (4) we found substantial linkage disequilibrium in all three studies and strong heterozygote deficit both in northern Calaveras, in 2001, and southern Calaveras. Both linkage disequilibrium and heterozygote deficit showed maximum values near the center of the zones. Using estimates of cline width and dispersal, we infer strong selection against hybrids. This is sufficient to promote accumulation of differences at loci that are neutral or under divergent selection, but would still allow for introgression of adaptive alleles. The evidence for strong but incomplete isolation across this centrally located contact is consistent with theory suggesting a gradual increase in postzygotic incompatibility between allopatric populations subject to divergent selection and reinforces the value of Ensatina as a system for the study of divergence and speciation at multiple stages. © 2005 The Society for the Study of Evolution. All rights reserved.
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Rhodococcus equi is a Gram-positive, facultative intracellular bacterium which infects macrophages and causes rhodococcal pneumonia and enteritis in foals. Recently, this agent has been recognized as an opportunistic pathogen for immunocompromised humans. Several murine experimental models have been used to study R. equi infection. High (H IV-A) and Low (L IV-A) antibody (Ab)-producers mice were obtained by bi-directional genetic selections for their ability to produce antibodies against sheep and human erythrocytes (Selection IV-A). These lines maintain their phenotypes of high and low responders also for other antigens than those of selection (multispeciflc effect). A higher macrophage activity in L IV-A mice has been described for several intracellular infectious agents, which could be responsible for their intense macrophage antigens (Ag)-handling and low Ab production. Due to these differences, L IV-A mice were found to exhibit a better performance to trigger an effective immune response towards intracellular pathogens. The objective of this work was to characterize the immune response of Selection IV-A against R. equi. H IV-A and L IV-A mice were infected with 2.0 × 10 6 CFU of ATCC 33701 +R. equi by intravenous route. With regards to bacterial clearance and survival assays, L IV-A mice were more resistant than H IV-A mice to virulent R. equi. L IV-A mice presented a higher hydrogen peroxide (H 2O 2) and nitric oxide (NO) endogenous production by splenic macrophages than H IV-A mice. L IV-A expressed the most intense cellular response, available by the Delayed-Type Hypersensitivity (DTH) reaction, which activated macrophages and produced more H 2O 2 and NO. The three times higher specific antibodies titres in H IV-A indicated that Selection IV-A maintained the multispecific effect and the polygenic control of humoral and cellular responses also to R. equi.
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In order to evaluate the flying capacity and nest site selection of Angiopolybia pallens (Lepeletier, 1836), we made 17 incursions (136 hours of sample efforts) in Atlantic Rain Forest environments in Bahia state. Our data show this wasp prefers to nest on wide leaves of bushes and short trees (nests between 0.30 and 3m from the ground) placed in half-shady environments (clearings and shadowed cultivations). The logistic regression model using Quasi-Newton method provided a good description of the flying capacity observed in A. pallens (x 2 = 91.52; p≪0.001). According to the logistic regression model, the A. pallens flight autonomy is low, flying for short distances and with an effective radius of action of about 24m measured from their nests, which means a foraging area of nearly 1,800 m 2.
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Mice genetically selected for high (H) and low (L) antibody production (Selection IV-A) were used as murine experimental model. The aim of the present work was to evaluate the macrophagic activity and to characterize the immune response in Mycobacterium bovis-AN5 infected mice (3×10 7 bacteria). The response profile previously observed in such strains was not similar to that obtained during M. bovis infection; however, it corroborated works carried out using Selection I, which is very similar to Selection IV-A regarding infection by M. tuberculosis and Bacillus Calmette-Guérin (BCG). Considering bacterial recovery, LIV-A mice showed higher control of the infectious process in the lungs than in the spleen, whereas HIV-A mice presented more resistance in the spleen. With respect to macrophagic activity, hydrogen peroxide (H2O 2) was probably not involved in the infection control since there was an inhibition in the production of this metabolite. Nitric oxide (NO) and TNF-α production seemed to be important in the control of bacterial replication and varied according to the strain, period and organ. Evaluation of the antibody production indicated that the multi-specific effect commonly observed in these strains was not the same in the response to M. bovis. Antibody concentrations were higher in LIV-A than in HIV-A mice at the beginning of the infection, being similar afterwards. Such data were compared with delayed-type hypersensitivity (DTH), which was more intense in HIV-A than in LIV-A mice, indicating that antibody production is independent of the capability to trigger DTH reactions and that cellular and humoral responses to M. bovis antigens show a polygenic control and an independent quantitative genetic regulation. Differences were observed among organs and metabolites, suggesting that different mechanisms play an important role in this infection in natural heterogeneous populations, indicating that NO, TNF-α and Th1 cytokines are involved in the infection control.
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Purpose - The purpose of this paper is to present designs for an accelerated life test (ALT). Design/methodology/approach - Bayesian methods and simulation Monte Carlo Markov Chain (MCMC) methods were used. Findings - In the paper a Bayesian method based on MCMC for ALT under EW distribution (for life time) and Arrhenius models (relating the stress variable and parameters) was proposed. The paper can conclude that it is a reasonable alternative to the classical statistical methods since the implementation of the proposed method is simple, not requiring advanced computational understanding and inferences on the parameters can be made easily. By the predictive density of a future observation, a procedure was developed to plan ALT and also to verify if the conformance fraction of the manufactured process reaches some desired level of quality. This procedure is useful for statistical process control in many industrial applications. Research limitations/implications - The results may be applied in a semiconductor manufacturer. Originality/value - The Exponentiated-Weibull-Arrhenius model has never before been used to plan an ALT. © Emerald Group Publishing Limited.