946 resultados para Covariance
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This study aimed to: a) to compare the covariance components obtained by Restricted Maximum Likelihood (REML) and by bayesian inference (BI): b) to run genetic evaluations for weights of Canchim cattle measured at weaning (W240) and at eighteen months of age (W550), adjusted or not to 240 and 550 days of age, respectively, using the mixed model methodology with covariance components obtained by REML or by BI; and c) to compare selection decisions from genetic evaluations using observed or adjusted weights and by REML or BI. Covariance components, heritabilities and genetic correlation for W240 and W550 were estimated and the predicted breeding values were used to select 10% and 50% of the best bulls and cows, respectively. The covariance components obtained by REML were smaller than the a posteriori means obtained by Bl. Selected animals from both procedures were not the same, probably because the covariance components and genetic parameters were different. The inclusion of age of animal at weighing as a covariate in the statistical model fitted by BI did not change the selected bulls and cows.
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We derive a set of relativistic three-particle scattering equations in the three-particle c.m. frame employing a relativistic three-particle propagator suggested long ago by Ahmadzadeh and Tjon in the c.m. frame of a two-particle subsystem. We make the coordinate transformation of this propagator from the c.m. frame of the two-particle subsystem to the three-particle c.m. frame. We also point out that some numerical applications of the Ahmadzadeh and Tjon propagator to the three-nucleon problem use unnecessary nonrelativistic approximations which do not simplify the computational task, but violate constraints of relativistic unitarity and/or covariance.
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The objective of this study was to estimate heritabilities of and genetic correlations among male body weight (BW12) and scrotal circumference (SC12) at 12 months of age, and female body weights at first (BWFC) and second (BWSC) calvings, age at first (AFC) and second (ASC) calvings, adult weight (AW), and mature weight (A) and maturation rate (k) obtained by the use of the Von Bertalanffy model. The restricted maximum likelihood method with an animal model that included the fixed effects of contemporary group and the random effects of animals, was used to estimate the variance and covariance components. The heritability estimates were equal to: 0.37 (BW12),0.30 (SC12),0.38 (A), 0.35 (k), 0.12 (AFC), 0.33 (BWFC), 0.04 (ASC), 0.39 (BWSC), and 0.38 (AW). The genetic correlations among BW12 and the female traits were: 0.19 (parameter A), 0.62 (parameter k), -0.58 (AFC), 0.69 (BWFC), -0.56 (ASC), 0.61 (BWSC), and 0.60 (AW). The genetic correlations among SC12 and the female traits were: -0.24 (A), 0.27 (k), -0.47 (AFC), 0.09 (BWFC), -0.67 (ASC), 0.07 (BWSC), and -0.17 (AW). These results indicate that male body weight and scrotal circumference and female weights (BWFC, BWSC and AW) and growth curve parameters A and k have enough additive genetic variation to respond to mass selection. Selection to increase male body weight at 12 months of age should result on favorable correlated changes in AFC, ASC and parameter k of females, but with increases in female body weights (BWFC, BWSC and AW). Selection to increase SC12 should result on desirable correlated responses in AFC, ASC and k, without any considerable change in female adult body weights.
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Milk yield, fat yield, and fat percentage during the first three lactations were studied using New York Holsteins that were milked twice daily over a 305-d, mature equivalent lactation. Those data were used to estimate variances from direct and maternal genetic effects, cytoplasmic effects, sire by herd interaction, and cow permanent environmental effects. Cytoplasmic line was traced to the last female ancestor using DHI records from 1950 through 1991. Records were 138,869 lactations of 68,063 cows calving from 1980 through 1991. Ten random samples were based on herd code. Samples averaged 4926 dams and 2026 cytoplasmic lines. Model also included herd-year-seasons as fixed effects and genetic covariance for direct-maternal effects. Mean estimates of the effects of maternal genetic variances and direct-maternal covariances, as fractions of phenotypic variances, were 0.008 and 0.007 for milk yield, 0.010 and 0.010 for fat yield, and 0.006 and 0.025 for fat percentage, respectively. Average fractions of variance from cytoplasmic line were 0.011, 0.008, and 0.009 for milk yield, fat yield, and fat percentage. Removal of maternal genetic effects and covariance for maternal direct effects from the model increased the fraction of direct genetic variance by 0.014, 0.021, and 0.046 for milk yield, fat yield, and fat percentage; little change in the fraction was due to cytoplasmic line. Exclusion of cytoplasmic effects from the model increased the ratio of additive direct genetic variance to phenotypic variance by less than 2%. Similarly, when sire by herd interaction was excluded, the ratio of direct genetic variance to phenotypic variance increased 1% or less.
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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.
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This study investigated if overfed rats present morphological and histochemical muscle adaptation similar to normally fed, both submitted to two different weekly frequencies of training. Thirty male Wistar rats were fed either with standard chow (SCO) or with hypercaloric diet (HCO). They were subdivided into six subgroups: sedentary (SCO and HCO), trained twice/week (SC2 and HC2) and trained five times/week (SC5 and HC5). The trained groups swam 60 min/day, during 10 weeks. Twenty four hours after the last training, samples of Gastrocnemius were excised and stained with HE, NADH-TR and m-ATPase, and the capillary density was calculated. Total heart mass (HM) and the mass of atrium (AM), left (LV) and right (RV) ventricles were excised and weighted. The comparisons were made by ANOVA and by Covariance analysis, adjusting the variables by body weight. The results showed that the HCO achieved higher BM, however, absolute HM did not differ post training. Irrespective of the diet, rats that were trained twice a week presented significantly greater increase in the AM. In general, the SC5 and HC5 groups showed higher HM, LV, RV, proportion of oxidative fibres and capillary density, compared to the sedentary and twice week trained groups. A higher proportion of injuries (splitting) was noted in the HC2 and HC5 compared to SC2 and SC5. These results indicate that the frequency of training influenced the skeletal and heart adaptation and larger changes were observed in the 5x/week group, which ingested the standard diet. The 5x/week training groups also presented large amount of muscle fibres damage.
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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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The T-2 and the generalized variance vertical bar S vertical bar charts are used for monitoring the mean vector and the covariance matrix of multivariate processes. In this article, we propose for bivariate processes the use of the T-2 and the VMAX charts. The points plotted on the VMAX chart correspond to the maximum of the sample variances of the two quality characteristics. The reason to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is the user's familiarity with the computation of simple sample variances; we can't say the same with regard to the computation of the generalized variance vertical bar S vertical bar.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We seek new couplings of chiral bosons to U(1) gauge fields. Lorentz covariance of the resulting constrained lagrangian is checked with the help of a procedure based in the first-order formalism of Faddeev and Jackiw. We find Harada's constraint and another local one not previously considered. We analyze the constraint structure and part of the spectrum of this second solution and show that it is equivalent to an explicitly covariant coupling of Siegel's chiral boson to gauge fields, which preserves chirality under gauge transformations.
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We show that the multi-boson KP hierarchies possess a class of discrete symmetries linking them to discrete Toda systems. These discrete symmetries are generated by the similarity transformation of the corresponding Lax operator. This establishes a canonical nature of the discrete transformations. The spectral equation, which defines both the lattice system and the corresponding Lax operator, plays a key role in determining pertinent symmetry structure. We also introduce the concept of the square root lattice leading to a family of new pseudo-differential operators with covariance under additional Bäcklund transformations.
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The merit of the Karhunen-Loève transform is well known. Since its basis is the eigenvector set of the covariance matrix, a statistical, not functional, representation of the variance in pattern ensembles is generated. By using the Karhunen-Loève transform coefficients as a natural feature representation of a character image, the eigenvector set can be regarded as an feature extractor for a classifier.
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An analysis of covariance relating basin area (A, km2) to river length (L, km) and discharge rate (D, m3 s-1) was performed for two continents and showed that the two covariates (L and D) were highly significant and that the strength of the relationship changed between continents. For comparison, D was excluded but the result remained the same. Although geomorphological models are useful for establishing global levels of production, these regressions should be applied with caution. Historically, simple statistical models were developed to predict fish catches in rivers. These, based upon regression of catches on channel length or basin area for Africa and Central Amazonia, are contrasted in this paper because of their generally similar approach.
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The negative-dimensional integration method (NDIM) seems to be a very promising technique for evaluating massless and/or massive Feynman diagrams. It is unique in the sense that the method gives solutions in different regions of external momenta simultaneously. Moreover, it is a technique whereby the difficulties associated with performing parametric integrals in the standard approach are transferred to a simpler solving of a system of linear algebraic equations, thanks to the polynomial character of the relevant integrands. We employ this method to evaluate a scalar integral for a massless two-loop three-point vertex with all the external legs off-shell, and consider several special cases for it, yielding results, even for distinct simpler diagrams. We also consider the possibility of NDIM in non-covariant gauges such as the light-cone gauge and do some illustrative calculations, showing that for one-degree violation of covariance (i.e. one external, gauge-breaking, light-like vector n μ) the ensuing results are concordant with the ones obtained via either the usual dimensional regularization technique, or the use of the principal value prescription for the gauge-dependent pole, while for two-degree violation of covariance - i.e. two external, light-like vectors n μ, the gauge-breaking one, and (its dual) n * μ - the ensuing results are concordant with the ones obtained via causal constraints or the use of the so-called generalized Mandelstam-Leibbrandt prescription. © 1999 Elsevier Science B.V.