Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 10,000 papers for “Logistic function”

Logistic function

Darre, Yann, Ministere de la Recherche et de l'Espace (MRE), 75 - Paris (France), Centre d'Etudes et de Recherches sur les Qualifications, 75 - Paris (France) · OpenGrey (Institut de l'Information Scientifique et Technique) · 1992

Cited by 0

Fitting the logistic function

Markku Löytönen · SHILAP Revista de lepidopterología · 1987

The logistic function is widely used in many disciplines to study the asymptotic growth behaviour of various populations. The multiscience interest in the logis­tic function is due to the fact that with it one can describe growth following or approximating a cumulative normal distribution. Despite its positive qualities, the logistic function has proved difficult to apply to empirical data in the case with three unknown parameters, one parameter being the asymptotic maximum size of the population. In geographical research the maximum size of the population is usually known, leaving only two parameters to be estimated. This can easily be done either by the linear regression formula ‑ a method generally recommended in the geograpical literature ‑ or by the method presented by Croxton & al. In this paper it is shown that both of these simple methods for fitting the logistic function produce inaccurate estimates of the parameters. The use of these simple methods should be abandoned and in the future the logistic function should be applied to empirical data with some iterative optimization algorithm, like the Gauss‑Newton algorithm applied in this paper. This would ensure the compati­bility and reliability of the estimation results.

Cited by 2Open access

Reparametrized asymmetric logistic function.

Laura Marie Helleckes (12206910), Michael Osthege (12206913), Wolfgang Wiechert (39471) et al. · Figshare · 2022

<p>When parametrized as shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1009223#pcbi.1009223.e043" target="_blank">Eq 11</a>, each of the 5 parameters can be manipulated without influencing the others. Note that, for example, the symmetry parameter <i>c</i> can be changed without affecting the x-coordinate of the inflection point (<i>I</i><sub><i>x</i></sub>), or the slope <i>S</i> at the inflection point (gray vs. black).</p>

Cited by 0Open access

THE POWER OF THE LOGISTIC FUNCTION,

Harrison,K. W. · Defense Technical Information Center (DTIC) · 1967

In previous papers the use of the logistic function in assessing radar performance has been discussed, with reference to examples, and the theory of subjective probability proposed by Dr. I. J. Good has been featured. In this paper the use of the logistic by other workers will be considered and the function will be examined in the light of views held by Dr. Good, Professor Hogben, Dr. J. Berkson and other scientists. An example will be referred to briefly to explain a choice of model and two fresh examples will be given to illustrate some further deliberations. (Author)

Cited by 0

ENTERPRISE LOGISTIC FUNCTION OUTSOURCING: STRATEGIC CONTEXT

О. В. Коровина, І. В. Шаповалова · TRADE AND MARKET OF UKRAINE · 2019

OUTSOURCING: STRATEGIC CONTEXT Мета -аналіз сучасних тенденцій розвитку аутсорсингу та можливостей його застосування при передачі логістичних функцій за межі діяльності підприємства в стратегічному контексті

Cited by 0Open access

Logistic function data analysis program LOGIT

William H. Kirchhoff · 1989

A FORTRAN program has been written for the statistical analysis of experimental data in terms of an extended logistic function that includes non-horizontal asymptotes and asymmetry in the pre-and post-transition portions of growth and decay curves. The program is robust in that situations in which few or no data fall within the transition interval can be analyzed by the program.

Cited by 0Open access

Learning Polyhedral Classiers Using Logistic Function

Naresh Manwani, P. S. Sastry, Masashi Sugiyama et al. · 2014

In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimization problem, our method solves an unconstrained optimization problem. Our method is based on a logistic function based model for the posterior probability function. We propose an al-ternating optimization algorithm, namely, SPLA1 (Single Polyhedral Learning Algorithm1) which maximizes the log-likelihood of the training data to learn the parameters. We also extend our method to make it independent of any user specified parameter (e.g., number of hyperplanes required to form a polyhedral set) in SPLA2. We show the effectiveness of our approach with experiments on various synthetic and real world datasets and compare our approach with a standard decision tree method (OC1) and a constrained optimization based method for learning polyhedral sets (Astorino and Gaudioso, 2002).

Cited by 0

A generalization of the logistic function

Sabrina Diomede, Giovanni Taglialatela · CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) · 2021

In this note we introduce a generalization of the well-known logistic function, and we analyse some shape properties as well as some differential properties of such generalization.

Cited by 0

Production Control – A Logistic Control Function

Henny Van Ooijen, Corné Dirne · 2024

Production control can be regarded as a logistic planning and control (LPC) function within a production environment. This chapter discusses logistics in the general sense. The basic function of logistics is to make sure that the transformation process can perform its function effectively and efficiently by providing that process with the proper information, materials, and resource. The chapter focuses on basic decision elements in planning and control for logistics. LPC is about making decisions on the availability and the supply of materials, information, and capacity resources at which place and in what quantity to get the transformation process going. The chapter discusses specific characteristics of LPC in production. LPC can be considered as an aspect system of the control part of the production system. It focuses on the planning and control of the timeliness of the process. The chapter defines crucial concepts used in production control and discusses some general characteristics of a production situation.

Cited by 0

Gauss quadrature and Christoffel function for the logistic weight function

Walter Gautschi · Purdue University Research Repository · 2020

<p>MATLAB software is provided for generating to any given accuracy <em>n</em>-point Gauss quadrature rules, <em>n</em> ≥ 1, relative to the logistic weight function as well as approximations and respective errors for the quadrature weights and for the Christoffel function.</p>

Cited by 0Open access