A segmented regression model for the description of microbial growth has been suggested. The model is able to predict the exponential growth, logistic growth, logistic growth with a phase of decline, diauxic growth, microbial growth in synchronous cultures and the oscillatory growth

The Liu estimator has consistently been demonstrated to be an attractive shrinkage method for reducing the effects of multicollinearity. The Poisson regression model is a well-known model in applications when the response variable consists of count data. However, it is known that multicollinearity negatively affects the variance of the maximum likelihood estimator (MLE) of the Poisson regressio...

this study concerns the scope to improve water flooding in heterogeneous reservoirs. we used an existing, in-house developed, optimization program consisting of a reservoir simulator in combination with an adjoint-based optimal control algorithm. in particular we aimed to examine the scope for optimization in a two-dimensional horizontal reservoir containing a single high permeable streak, as a...

decision making on budgeting is one of the most important issues for executing managers. budgeting is a major tool for planning and control of projects. in public and non-profit organizations and institutions, estimating the costs and revenues plays an important role in receiving credit and budgeting. in this regard, in the present paper the case of isfahan municipality is considered. one of th...

A weighted linear regression model with impercise response and p-real explanatory variables is analyzed. The LR fuzzy random variable is introduced and a metric is suggested for coping with this kind of variables. A least square solution for estimating the parameters of the model is derived. The result are illustrated by the means of some case studies.

Following a Bayesian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate logistic regression. We use a multivariate normal prior in the Bayesian analysis. We present a unique Bayes estimator associated with a prior which is admissible. The Bayes estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure...

The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framewo...

Internet of Things (IoT) is a popular social network in which devices are virtually connected for communicating and sharing information. This applied greatly business enterprises government sectors delivering the services to their customers, clients citizens. But, interaction successful only based on trust that each device has another. Thus very much essential network. As have access over sensi...