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About 1,366 papers for “Gompertz function”

Properties of Gompertz function.

Martí Català (8871515), Sergio Alonso (270169), Enrique Alvarez-Lacalle (345336) et al. · Figshare · 2020

<p>Evolution of the cumulative cases (A) and new cases (B) keeping <i>K</i> = 10<sup>4</sup> for three different values of a. Evolution of cumulative cases (C) and new cases (D) keeping <i>μ</i><sub>0</sub> = 0.92 for three different values of <i>a</i>.</p>

Cited by 0Open access

Chebyshev approximation by Gompertz function

P. S. Malachivskyy, L. S. Melnychok, Ya. V. Pizyur · Matematychni Metody Ta Fizyko-Mekhanichni Polya · 2022

The properties of the Chebyshev approximation by the Gompertz function are investigated. The condition under which such approximation with a relative error exists and is unique is established. A method for determining the parameters of the Chebyshev approximation is proposed and substantiated. The presented example confirms the expediency of using the Chebyshev approximation by the Gompertz function for prediction of growth dynamics. Cite as: P. S. Malachivskyy, L. S. Melnychok, Ya. V. Pizyur, “Chebyshev approximation by Gompertz function,” Mat. Met. Fiz. Mekh. Polya , 65 , No. 3-4, 95–100 (2022) (in Ukrainian), https://doi.org/10.15407/mmpmf2022.65.3-4.95-100 Traslation: P. S. Malachivskyy, L. S. Melnychok, Y. V. Pizyur, “Chebyshev approximation by Gompertz function,” J. Math. Sci., 287, No. 2, 216–222 (2025), https://doi.org/10.1007/s10958-025-07586-7

Cited by 0Open access

Haybittle, use of Gompertz function

Rebecca West · International Journal of Epidemiology · 1999

Sir-I was very interested to see the article by John Haybittle 1 on use of the Gompertz function to relate changes in life expectancy to the standardized mortality ratio and I agree wholeheartedly with justification (introduction) and closing paragraph (conclusion); that life expectancy has more meaning than does SMR for the layman and I suspect for many clinicians. I have long held this view, which is why I suggested that the British smoking doctor study be re-analysed by the current life table method and re-presented as survival graphs. This is what you would expect from the Gompertz function ( x = Be kx ) but also, and more relevant to the purpose of the paper, to make things simple for the layman, this would give nearly straight line relationships between SMR and change in life expectancy from the norm or standard (see attached figures).

Cited by 0Open access

Prediction model based on Gompertz function

Zheng Yan · 2009

A novel prediction model based on Gompertz function and customer life cycle (CLC) is presented in this paper. Firstly, the calling behavior between the inner-net (China Unicom) mobile customers and the outer-net (China Mobile) mobile customers are extracted and analyzed, then fitted a CLC curve by Gompertz function. Furthermore, the different period of CLC is identified according to the fitting curve. Finally the number of outer-net mobile customers is predicted accurately and dynamically. The experiments of real data illustrate the availability and accuracy of the proposed prediction model.

Cited by 3

Covid-19 analysis using the Gompertz Function

Pradas Rodriguez, Sergi, Rovira Ferrer, David, Simó Romaguera, Xavier · Repositori UJI (Universitat Jaume I) · 2020

This report analyses the spread of COVID-19 in european countries, focusing especially on Italy
\nand Spain, for which short-term predictions are made for the cumulative number of hospitalizations,
\nICUs, discharges and deaths. Taking into account the different magnitudes considered, for 1 day
\npredictions the mean probability of a right guess is of 0.99, 0.94 for 2 day predictions, 0.89 for 3 day
\npredictions and 0.83 for 4 day predictions

Cited by 0Open access

Bayesian Inference for Reliability Function of Gompertz Distribution

Huda A. Rasheed, Tasnim H.K. Al-Baldawi, Shurooq A.K. Al-Sultany · Journal of Physics Conference Series · 2020

Abstract In this paper, some Bayes estimators of the reliability function of Gompertz distribution have been derived based on generalized weighted loss function. In order to get a best understanding of the behaviour of Bayesian estimators, a non-informative prior as well as an informative prior represented by exponential distribution is considered. Monte-Carlo simulation have been employed to compare the performance of different estimates for the reliability function of Gompertz distribution based on Integrated mean squared errors. It was found that Bayes estimators with exponential prior information under the generalized weighted loss function were generally better than the estimators based on Jeffreys prior information.

Cited by 1Open access

Dynamical fitting of Gompertz function and parameters evolution.

Martí Català (8871515), Sergio Alonso (270169), Enrique Alvarez-Lacalle (345336) et al. · Figshare · 2020

<p>(A-C) Gompertz fitting for China at three different time points, 7 February, 20 February and 14 March. Number of cumulative cases (blue dots) shown together with the function fitted (black dash line). (D-F) Dynamic calculation of parameters <i>μ</i><sub>0</sub>, <i>a</i>, and <i>K</i> in dark blue; light blue mark error bars parameters with confidence intervals of level <i>α</i> = 0.01.</p>

Cited by 0Open access

Gompertz function in the model of gene regulatory networks

Diana Ogorelova, Felix Zharmuhamedovich Sadyrbaev · Итоги науки и техники Серия «Современная математика и ее приложения Тематические обзоры» · 2021

Cited by 0

Growth Data of Broiler Chickens Fitted to Gompertz Function

Somporn Duanyai, B. A. Young, A. Lisle et al. · Asian-Australasian Journal of Animal Sciences · 1999

This study describes the growth of broiler chickens to the two forms of Gompertz function for application in broiler production models. The first form is based on the estimated mature weight (W-A), while the second is based on the estimated hatch weight (W-O). Both equations gave identical estimation because they are mathematically identical. To fit the growth curve of commercial broilers that marketed at 35-42 days, it is unnecessary to keep broilers to near maturity (> day 140) to obtain growth data for deriving the Gompertz function. This data does not improve the curve fitting of the early growing period. Additionally, a high mortality and health problem occurred to this type of chicken after day 105.

Cited by 6Open access

THE "S" CURVES OF A PROJECT AND THE GOMPERTZ FUNCTION

Morelli, Rocco, Lucibello, Pasquale · Zenodo (CERN European Organization for Nuclear Research) · 2018

THE "S" CURVES OF A PROJECT AND THE GOMPERTZ FUNCTION R- Morelli: A heuristic medium for an invitation to an in depth analysis P. Lucibello : algebraic development of the Ulmann method for data fitting Presented at GA 2018 meeting Italian & English text available also at : https://www.amazon.it/dp/8863212147

Cited by 0Open access

Modelling "calcots" (Allium cepa L.) growth by the Gompertz function

Joan A. Sim · 2013

Calcots are the second-year resprouts of the Ceba Blanca Tardana de Lleida landrace of onions. The evolution of three calcots populations has been modeled to help farmers to plan the optimal time to harvest. Four different models that essentially differ in the type of distribution of the fitting Gompertz function parameters (lag time, maximum growth rate and the maximum attainable number of commercial size calcots) have been tested. The model that considers a multinomial distribution of the fitting parameters showed the best agreement with the experimental data. MSC: MSC2000 classification of the American Mathematical Society: 92D25

Cited by 0

Survival Function Estimation for Fuzzy Gompertz Distribution with neutrosophic data

Alan Adham Bibani, Zakariya Yahya Algamal · 2023

A relatively recent area of research known as neutrosophic statistics deals with data that are ambiguous, indeterminate, and inconsistent. By embracing the idea of neutrosophy, which denotes the existence of three components in a statement: truth, falsity, and indeterminacy, it broadens the application of classical statistics. One of the significant offshoots of statistics is life-time data analysis. Traditional statistical methods only account for variation within the data and calculate lifetime observations as accurate numbers. Actually, there are two different kinds of uncertainty in data: fluctuation between observations and fuzziness. As a result, analysis techniques that solely employ precise lifetime data and ignore fuzziness use incomplete information and produce false results. This paper sought to generalize hazard rates, survival functions, and parameter estimates for fuzzy Gompertz Distribution. Simulation studies are implemented to examine the performance of the fuzzy Gompertz Distribution. The results show that the fuzzy Gompertz Distribution has better flexibility in handling over the standard Gompertz Distribution.

Cited by 7