in this study, the incomplete gamma function, an exponential function, a mixed-log function and a polynomial function were evaluated to describe the lactation curve in moroccan holstein-friesian dairy cows. data from 1990 to 1999, comprising 77130 monthly milk yields of 6029 dairy cows in 280 dairy herds, were used. edits were carried out by considering the lactation length (5 d and

Score limitation at the top of a scale is commonly termed "ceiling effect." Ceiling effects can lead to serious artifactual parameter estimates in most data analysis. This study examines the consequences of ceiling effects in longitudinal data analysis and investigates several methods of dealing with ceiling effects through Monte Carlo simulations and empirical data analyses. Data were simulate...

the objective of this study was to estimate variance components and genetic parameters for growth curve parameters in shall sheep. studied traits were parameters of brody growth model which included a (asymptotic mature weight), b (initial animal weight) and k (maturation rate). the data set and pedigree information used in this study were obtained from the animal breeding center of iran and co...

The goal of this study is to assess whether a growth curve model approach will lead to a more precise detection of Turner sydnrome (TS) than conventional referral criteria for growth monitoring. The Jenss-Bayley growth curve model was used to describe the process of growth over time. A new screening rule is defined on the parameters of this growth curve model, parental height and gestational ag...

We introduce equity forward variance term-structure models and derive the respective HJM-type arbitrage conditions. We then discuss finitedimensional Markovian representations of the infinite-dimensional fixed time-to-maturity forward variance swap curve and analyse examples of such variance curve functionals. The results are then applied to show that the speed of mean-reversion in standard sto...

Latent state-trait (LST) and latent growth curve (LGC) models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM) or multilevel (ML; hierarchical linear modeling) frameworks, few researchers realize that LST and multivariate LGC models, which use multipl...

Background and Objectives: Gestational Diabetes Mellitus (GDM) is the most common metabolic disorder in pregnancy. In case of early detection, some of its complications can be prevented. The aim of this study was to investigate early prediction of GDM by logistic regression (LR), discriminant analysis (DA), decision tree (DT) and perceptron artificial neural network (ANN) and to compare these m...

this paper investigates the relationship between inflation and growth uncertainty in iran for the period of 1988-2008 by using quarterly data. we employ generalized autoregressive conditional heteroscedasticity in mean (garch-m) model to estimate time-varying conditional residual variance of growth, as a standard measures of growth uncertainty. the empirical evidence shows that growth uncertain...

in this research, 272977 test day records collected from 659 herds during years 2001 to 2011 by the iranian animal breeding center were used. in the first section the ability of different models to predict daily milk yield from alternative milk recording was tested. the result showed that a complex model including noon milking time plus the effect of lactation curve of ali and schaeffer functio...