The objective of the present study was to estimate genetic trends for lactation milk yield, persistency of milk yield, somatic cell count and interval between first and second calving in Holstein dairy cows of Iran. The dataset consisted of 210,625 test day and 25,883 first parity cows with milk yield recorded from July 2002 to September 2007 comprising 97 herds in Iran. Breeding values of anim...

Ordinary linear and generalized linear regression models relate the mean of a response variable to a linear combination of covariate effects and, as a consequence, focus on average properties of the response. Analyzing childhood malnutrition in developing or transition countries based on such a regression model implies that the estimated effects describe the average nutritional status. However,...

In this paper, we study Bayesian asymptotic properties of the proportional hazards model where link function is modeled by generalized additive model. As standard is, a useful tool in finding nonlinearity covariate effects to survival times. We develop data-dependent sieve prior for and use bootstrap baseline hazard function. prove that posterior contraction rate minimax optimal up logn term wh...

SUMMARY We develop a method to identify a time dependent covariate eeect in the partly parametric additive risk model. The proposed method is based on a formal hypothesis test, whereas previously only an ad hoc procedure was available. Rates of convergence of restricted maximum likelihood estimators of regression coeecients based on the method of sieves play an important role in the development...

Analytical models usually assume an additive sex effect by treating it as a covariate to identify genetic associations with sex-influenced traits. Their underlying assumptions are violated by ignoring interactions of sex with genetic factors and heterogeneous genetic effects by sex. Methods to deal with the problems are compared and discussed in this article. Especially, heterogeneity of geneti...

We present a statistical perspective on boosting. Special emphasis is given to estimating potentially complex parametric or nonparametric models, including generalized linear and additive models as well as regression models for survival analysis. Concepts of degrees of freedom and corresponding Akaike or Bayesian information criteria, particularly useful for regularization and variable selectio...

Economic theory emphasizes that pursuing risk sharing allows to exploit benefits from comparative advantages and economies of scale. Unlike previous works we test (and reject) the assumption of parameter homogeneity across geographical units in measuring risk sharing. The estimated regional-specific index of risk sharing is then used as a covariate in a model of industrial specialization for th...

Investigators interested in whether a disease aggregates in families often collect case-control family data, which consist of disease status and covariate information for members of families selected via case or control probands. Here, we focus on the use of case-control family data to investigate the relative contributions to the disease of additive genetic effects (A), shared family environme...

A common assumption in supervised learning is that the training and test input points follow the same probability distribution. However, this assumption is not fulfilled, e.g., in interpolation, extrapolation, or active learning scenarios. The violation of this assumption— known as the covariate shift—causes a heavy bias in standard generalization error estimation schemes such as cross-validati...

Competing risk failure time data occur frequently in medical studies, and a number of methods have been proposed for the analysis of these data. To assess covariate effects, a standard approach is to model the cause-specific hazard functions of different failure types. Recently, Fine and Gray (1999) proposed directly modeling the subdistribution of a competing risk with a Cox type model. In thi...