This paper presents a Logistic Maturity Model. The goal is to provide companies with a system that allows both to assess their logistic processes current status and to outline an action plan for improvement, considering four key elements: Modeling Framework, Maturity Framework, Performance Framework and Improvement Systems.

1. The Effect of Response Level Ordering on Parameter Estimate Interpretation 2. Odds Ratios 2.1 Binary Explanatory Variable Modeling the Event 2.2 Binary Explanatory Variable Modeling the Nonevent 2.3 Continuous Explanatory Variable 3. Predicted Probabilities 4. Predicted by Observed Classification Tables 4.1 Classification Using Predicted Probabilities 4.2 Classification Using Bias-adjusted P...

When response outcomes are continuous error terms in models are normally distributed and a standard normal distribution function is adequate. The logistic distribution function which is very similar to the normal distribution function is required when the response variable is binary. Parameters of a logistic response function are often estimated using the method of maximum likelihood (ML). One ...

A decrease in myocardial intracellular calcium concentration ([Ca(2+)](i)) precedes relaxation, and a monoexponential function is typically used for fitting the decay of the Ca(2+) transient. However, a logistic function has been shown to be a better fit for the relaxation force curve, compared to the conventional monoexponential function. In the present study, we compared the logistic and mono...

We consider empirical risk minimization of linear predictors with convex loss functions. Such problems can be reformulated as convex-concave saddle point problems, and thus are well suitable for primal-dual first-order algorithms. However, primal-dual algorithms often require explicit strongly convex regularization in order to obtain fast linear convergence, and the required dual proximal mappi...

Logistic regression may be useful when we are trying to model a categorical dependent variable (DV) as a function of one or more independent variables. This paper reviews the case when the DV has more than two levels, either ordered or not, gives and explains SAS R © code for these methods, and illustrates them with examples.

We construct groups in which FV (n) ≁ δ(n). This construction also leads to groups Gk, k ≥ 3 for which δ (n) is not subrecursive. The Dehn function of a group measures the complexity of the group’s word problem by measuring the difficulty of filling loops in a corresponding complex. A natural generalization is to consider the difficulty of filling higher-dimensional manifolds or cycles, and the...

In this study, we consider two different inequivalent formulations of the logistic difference equation $x_{n+1}= beta x_n(1- x_n), n=0,1,..., $ where $x_n$ is a sequence of fuzzy numbers and $beta$ is a positive fuzzy number. The major contribution of this paper is to study the existence, uniqueness and global behavior of the solutions for two corresponding equations, using the concept of Huku...