Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Soft Computing
Published in: Soft Computing 4/2020

02-11-2018 | Focus

Uncertain Gompertz regression model with imprecise observations

Authors: Zeyu Hu, Jinwu Gao

Published in: Soft Computing | Issue 4/2020

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Regression is widely applied in many fields. Regardless of the types of regression, we often assume that the observations are precise. However, in real-life circumstances, this assumption can only be met sometimes, which means the traditional regression methods can result in significant imprecise or biased predictions. Consequently, uncertain regression models might provide more accurate and meaningful results under these circumstances. In this article, we provide the residual analysis of uncertain Gompertz regression model, as well as the corresponding forecast value and confidence interval. Finally, we give a numerical example of uncertain Gompertz regression model.
previous article Estimation of dynamic mixed double factors model in high-dimensional panel data
next article The impact of online referral on brand market strategies with consumer search and spillover effect

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Literature
Corral N, Gil MA (1984) The minimum inaccuracy fuzzy estimation: an extension of the maximum likelihood principle. Stochastica 8:63–81MathSciNetMATH
Fisher RA (1925) Statistical methods for research workers. Oliver and Boyd, EdinburghMATH
Galton F (1885) Regression towards mediocrity in hereditary stature. J Anthropol Inst 15:246–263
Gompertz B (1825) On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philos Trans B 115:513585
Legendre AM (1805) New methods for the determination of the orbits of comets. Firmin Didot, Paris
Lio W, Liu B (2018) Residual and confidence interval for uncertain regression model with imprecise observations. J Intell Fuzzy Syst 35:2573–83CrossRef
Liu B (2009) Some research problems in uncertainty theory. J Uncertain Syst 3:3–10
Liu B (2010) Uncertainty theory: a branch of mathematics for modeling human uncertainty. Springer, BerlinCrossRef
Liu B (2012) Why is there a need for uncertainty theory. J Uncertain Syst 6:3–10
Neyman J, Pearson ES (1933) On the problem of the most efficient tests of statistical hypotheses. Philos Trans R Soc A Math Phys Eng Sci 231:289–337MATH
Nguimkeu P (2014) A simple selection test between the Gompertz and logistic growth models. Technol Forecast Soc Change 88:98–105CrossRef
Tanaka H, Uejima S, Asai K (1982) Linear regression analysis with fuzzy model. IEEE Trans Syst Man Cybern 12:903–907CrossRef
Wilks SS (1938) The large-sample distribution of the likelihood ratio for testing composite hypotheses. Ann Math Stat 9:60–62CrossRef
Yang X, Liu B (2017) Uncertain time series analysis with imprecise observations. Fuzzy Optim Decis Mak (in press)
Yao K, Liu B (2018) Uncertain regression analysis: an approach for imprecise observations. Soft Comput 22:557982
Zwietering MH, Jongenburger I, Rombouts FM, VanT Rie TK (1990) Modeling of the bacterial growth curve. Appl Environ Micriobiol 56:197581
Metadata
Title
Uncertain Gompertz regression model with imprecise observations
Authors
Zeyu Hu
Jinwu Gao
Publication date
02-11-2018
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 4/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3611-1

Other articles of this Issue 4/2020

Soft Computing 4/2020 Go to the issue

Focus

Estimation of dynamic mixed double factors model in high-dimensional panel data

Focus

Effects of risk attitudes and investment spillover on supplier encroachment

Focus

Uncertain population model

Focus

Price discrimination based on purchase behavior and service cost in competitive channels

Focus

Roman domination problem with uncertain positioning and deployment costs

Focus

Internationalization strategy, social responsibility pressure and enterprise value

Premium Partner

    Image Credits