Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

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

Ultrastructure of spermatogenesis, spermatozoon and processes of testicular regression and recrudescence in Eptesicus furinalis (Chiroptera: Vespertilionidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

The zero-inflated Conway-Maxwell-Poisson distribution: Bayesian inference, regression modeling and influence diagnostic

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Method validation using weighted linear regression models for quantification of UV filters in water samples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Two periods of total testicular regression are peculiar events of the annual reproductive cycle of the black Myotis bat, Myotis nigricans (Chiroptera: Vespertilionidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A note on model uncertainty in linear regression

We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.

Diversity, natural history, and geographic distribution of snakes in the Caatinga, Northeastern Brazil

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

Biogeographic Distribution Patterns and Their Correlates in the Diverse Frog Fauna of the Atlantic Forest Hotspot

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

Random regression models using different functions to model milk flow in dairy cows

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

Geographic note on species of the genus Upa Kimsey, 1991 (Hymenoptera: Tiphiidae, Thynninae) in the Atlantic Forest, Brazil

Upa Kimsey is a poorly known genus of Tiphiidae with seven species. This genus has records in forest areas and in this paper we present new records to four species. All specimens were collected by malaise traps in four areas of Atlantic Rain Forest and three of Atlantic Semi-deciduous forest, mainly from high and mid-elevations. The new records indicate that species of Upa are not as rare as others genera of Tiphiidae, which are virtually unknown in many Neotropical regions.

Multicollinearity and financial constraint in investment decisions: a bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Advertisement call, colour variation, natural history, and geographic distribution of Proceratophrys caramaschii (Anura: Odontophrynidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Impact of the processes of testicular regression and recrudescence in the prostatic complex of the bat myotis nigricans (Chiroptera: Vespertilionidae)

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

Impact of the processes of total testicular regression and recrudescence on the epididymal physiology of the bat myotis nigricans (chiroptera: vespertilionidae)

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