the impact of climatic variations on basal area growth of basswood (ba) (tilia americana l.), american beech (be) (fagus grandifolia enrh.), bitternut hickory (bh) (caria cordiformis (wang.) k. koch), largetooth aspen (la) (populus grandidentata michx.), red maple (rm) (acer rubrum l.), red oak (ro) (quercus rubra l.), sugar maple (sm) (acer saccharum marsh.), and white ash (wa) (fraxinus a...

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...

growth analysis is a valuable method in the quantitative analysis of crop growth, development and crop production. there are many regression models to describe the sigmoid growth patterns. by considering that, the parameters of non-linear regression models have physiological meanings, they are preferable relation to linear regression models. the aim of this study was to collect and evaluate the...

The population growth, is increase in the number of individuals in population and it depends on some random environment effects. There are several different mathematical models for population growth. These models are suitable tool to predict future population growth. One of these models is logistic model. In this paper, by using Feynman-Kac formula, the Adomian decomposition method is applied to ...

an analysis of the stages of crop growth presents an important step in the improvement of production management. through growth analysis, planning for planting systems, fertilization, pruning operations, harvest time as well as obtaining economical yield can be more accessible. therefore, a development of mathematical models simulating plant growth would be helpful in improving crop management,...

Computational models are increasingly used to understand and predict complex biological phenomena. These models contain many unknown parameters, at least some of which are difficult to measure directly, and instead are estimated by fitting to time-course data. Previous work has suggested that even with precise data sets, many parameters are unknowable by trajectory measurements. We examined thi...

the logistic, gompertz, richards and asymmetric logistic growth curve models were fitted to body weight data of local ghanaian chickens and french sasso t44 chickens. all four growth models provided good fit for each sex by genotype growth data with r2 values ranging from 86.7% to 96.7%. the rate constant parameter, k, ranged between 0.137 and 0.271 and were significantly different from zero fo...