In this paper, a logistic model incorporating nonlinear impulsive Holling type-II harvesting is proposed and studied.
In this paper, multivariate logistic regression was run to see the net effects of independent variables over the dependent one.
This paper uses logistic regression to estimate the shape of the prevalence trend, while adjusting for variables that may explain the changing recruitment in unlinked anonymous data.
Even with this restriction, this paper unifies logistic and probit ordinal regression under a Bayesian framework and is a useful alternative for genomic-enabled prediction of ordinal categorical trials where available data sets have a larger number of parameters to estimate than observations.
For example, for the ACL injury differences project, a library of papers describing experimental equipment, techniques, and expected outcomes was combined with papers describing logistic models and their use.
In this paper, an improved logistic map, namely a double-bottom map, with particle swarm optimization was applied to the test function.
Different from other similar research, based on the analysis of the factors which can influence people choose subway or not, this paper constructs the logistic model.
In this paper we use logistic regression techniques to evaluate the relation between reading achievement at school entry and conduct problems 30 months later, in a representative, non-clinic sample of kindergarten and grade one children, in Ontario, Canada.
