Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation

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.

Principal components and factor analytic models for birth to mature weights in Nellore cattle

A total of 61,528 weight records from 22,246 Nellore animals born between 1984 and 2002 were used to compare different multiple-trait analysis methods for birth to mature weights. The following models were used: standard multivarite model (MV), five reduced-rank models fitting the first 1, 2, 3, 4 and 5 genetic principal components, and five models using factor analysis with 1, 2, 3, 4 and 5 factors. Direct additive genetic random effects and residual effects were included in all models. In addition, maternal genetic and maternal permanent environmental effects were included as random effects for birth and weaning weight. The models included contemporary group as fixed effect and age of animal at recording (except for birth weight) and age of dam at calving as linear and quadratic effects (for birth weight and weaning weight). The maternal genetic, maternal permanent environmental and residual (co)variance matrices were assumed to be full rank. According to model selection criteria, the model fitting the three first principal components (PC3) provided the best fit, without the need for factor analysis models. Similar estimates of phenotypic, direct additive and maternal genetic, maternal permanent environmental and residual (co)variances were obtained with models MV and PC3. Direct heritability ranged from 0.21 (birth weight) to 0.45 (weight at 6 years of age). The genetic and phenotypic correlations obtained with model PC3 were slightly higher than those estimated with model MV. In general, the reduced-rank model substantially decreased the number of parameters in the analyses without reducing the goodness-of-fit. © 2013 Elsevier B.V.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

Positioning and number of nutritional levels in dose-response trials to estimate the optimal-level and the adjustment of the models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Growth in weight and of some tissues in the bullfrog: fitting nonlinear models during the fattening phase

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation of roof slope and exposure with different roofing materials in reduced models of animal production facilities in spring and summer

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Models for the analysis of growth curves for rearing tinamous (Rhynchotus rufescens) in captivity

Growth curves models provide a visual assessment of growth as a function of time, and prediction body weight at a specific age. This study aimed at estimating tinamous growth curve using different models, and at verifying their goodness of fit. A total number 11,639 weight records from 411 birds, being 6,671 from females and 3,095 from males, was analyzed. The highest estimates of a parameter were obtained using Brody (BD), von Bertalanffy (VB), Gompertz (GP,) and Logistic function (LG). Adult females were 5.7% heavier than males. The highest estimates of b parameter were obtained in the LG, GP, BID, and VB models. The estimated k parameter values in decreasing order were obtained in LG, GP, VB, and BID models. The correlation between the parameters a and k showed heavier birds are less precocious than the lighter. The estimates of intercept, linear regression coefficient, quadratic regression coefficient, and differences between quadratic coefficient of functions and estimated ties of quadratic-quadratic-quadratic segmented polynomials (QQQSP) were: 31.1732 +/- 2.41339; 3.07898 +/- 0.13287; 0.02689 +/- 0.00152; -0.05566 +/- 0.00193; 0.02349 +/- 0.00107, and 57 and 145 days, respectively. The estimated predicted mean error values (PME) of VB, GP, BID, LG, and QQQSP models were, respectively, 0.8353; 0.01715; -0.6939; -2.2453; and -0.7544%. The coefficient of determination (RI) and least square error values (MS) showed similar results. In conclusion, the VB and the QQQSP models adequately described tinamous growth. The best model to describe tinamous growth was the Gompertz model, because it presented the highest R-2 values, easiness of convergence, lower PME, and the easiness of parameter biological interpretation.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Environmental and genetic factors affecting the weaning-estrus interval in sows

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bundle Block Adjustment of CBERS-2B HRC Imagery Combining Control Points and Lines

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detection and thinning of edges in previously known directions

This work presents a study on the generation of digital masks aiming at edge detection with previously known directions. This solution is important when edge direction is available either from a direction histogram or from a prediction based on camera and object models. A modification in the non-maximum suppression method of thinning is also presented enabling the comparison of local maxima for any edge directions. Results with a synthetic image and with crops of a CBERS satellite images are presented showing an example with its application in road detection, provided that directions are previously known.

LEARNING A COMPLEX MOTOR SKILL FROM VIDEO and POINT-LIGHT DEMONSTRATIONS

The aim of this Study was to compare the learning process of a highly complex ballet skill following demonstrations of point light and video models 16 participants divided into point light and video groups (ns = 8) performed 160 trials of a pirouette equally distributed in blocks of 20 trials alternating periods of demonstration and practice with a retention test a day later Measures of head and trunk oscillation coordination d1 parity from the model and movement time difference showed similarities between video and point light groups ballet experts evaluations indicated superiority of performance in the video over the point light group Results are discussed in terms of the task requirements of dissociation between head and trunk rotations focusing on the hypothesis of sufficiency and higher relevance of information contained in biological motion models applied to learning of complex motor skills

Structural and Electronic Effects of Incorporating Mn in TiO2 Films Grown by Sputtering: Anatase versus Rutile

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)