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
DE
EN
Books
Journals
Events
Topic Page
Marketing
Start single access now
Access for companies
12th International Engine Congress 2025 | 25. + 26. February 2025

Meeting Place for the Powertrain and Sustainable Fuels Community

The congress will examine the future role of the internal combustion engine and its non-fossil fuels from a global perspective with leading experts. Be part of it! More information and booking options are available on our website.
EXTENDED SEARCH
Log in
Top
Annals of Data Science
Published in:

24-03-2022

Progressive Type-II Censored Samples for Bivariate Weibull Distribution with Economic and Medical Applications

Authors: El-Sayed A. El-Sherpieny, Hiba Z. Muhammed, Ehab M. Almetwally

Published in: Annals of Data Science | Issue 1/2024

Log in

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

search-config
loading …

Abstract

Recently, the Bivariate Weibull distribution based on different copula functions has received considerable attention in the statistical literature. For progressive Type-II censored samples of bivariate distribution, the effective sample size of censored sample \(m\) is fixed; the progressive censoring scheme is provided during the experiment for one variable and the second variable concomitant it. The Farlie–Gumbel–Morgenstern (FGM) copula has been used to construct the Bivariate Weibull distribution, which is called FGM Bivariate Weibull (FGMBW) distribution. In this paper, we consider the point, and interval estimation of the unknown parameters of the FGM bivariate Weibull distribution based on progressive Type-II censored samples. Two bootstrap confidence intervals are also proposed. In addition, two real data sets have been introduced and analyzed to examine the model in practice. A simulation study has been conducted to compare the preferences between different censoring schemes.
previous article A Review on Applications of Chaotic Maps in Pseudo-Random Number Generators and Encryption
next article A Generalization of New Pareto-Type Distribution

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

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
Literature
1.
Flores AQ (2009) Testing copula functions as a method to derive bivariate Weibull distributions. In American Political Science Association (APSA), Annual Meeting.‏
2.
Kundu D, Dey AK (2009) Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm. Comput Stat Data Anal 53(4):956–965MathSciNetCrossRef
3.
Kundu D, Gupta AK (2013) Bayes estimation for the Marshall-Olkin bivariate Weibull distribution. Comput Stat Data Anal 57(1):271–281MathSciNetCrossRef
4.
Almetwally EM, Muhammed HZ (2020) On a bivariate Fréchet distribution. J Stat Appl Probab 9(1):1–21
5.
6.
Muhammed HZ, El-Sherpieny ESA, Almetwally EM (2021) Dependency measures for new bivariate models based on copula function. Inform Sci Lett 10(3):511–526
7.
El-Sherpieny EA, Muhammed HZ, and Almetwally EM (2018) FGM bivariate weibull distribution. In Proceedings of the Annual Conference in Statistics (53rd), Computer Science, and Operations Research, Institute of Statistical Studies and Research, Cairo University
8.
Almetwally EM, Muhammed HZ, El-Sherpieny ESA (2020) Bivariate Weibull distribution: properties and different methods of estimation. Annals Data Sci 7(1):163–193CrossRef
9.
Balakrishnan N and Kim JA (2004) EM algorithm for Type-II right censored bivariate normal data. In Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life (pp. 177–210). Birkhäuser, Boston, MA.
10.
Kim SW, Ng HKT, Jang H (2016) Estimation of parameters in a bivariate generalized exponential distribution based on Type-II censored samples. Commun Stat-Simul Comput 45(10):3776–3797MathSciNetCrossRef
11.
Balakrishnan N, Kim JA (2005) Point and interval estimation for bivariate normal distribution based on progressively type-II censored data. Commun Stat Theory Methods 34(6):1297–1347CrossRef
12.
Bai X, Shi Y, Liu B, Fu Q (2018) Statistical inference of Marshall-Olkin bivariate Weibull distribution with three shocks based on progressive interval censored data. Commun Stat-Simul Comput 48(3):637–654MathSciNetCrossRef
13.
14.
15.
Olson DL, Shi Y and Shi Y (2007) Introduction to business data mining (Vol. 10, pp. 2250–2254). New York: McGraw-Hill/Irwin
16.
Gramaje A, Thabtah F, Abdelhamid N, Ray SK (2021) Patient discharge classification using machine learning techniques. Annal. Data Sci. 8(4):755–767CrossRef
17.
Shi Y, Tian Y, Kou G, Peng Y, Li J (2011) Optimization based data mining: theory and applications. Springer Science & Business Media, BerlinCrossRef
18.
Tien JM (2017) Internet of things, real-time decision making, and artificial intelligence. Annal Data Science 4(2):149–178CrossRef
19.
20.
Efron B (1992) Bootstrap methods: another look at the jackknife. In Breakthroughs in statistics. Springer, New York, NY.
21.
Elaal MKA, Jarwan RS (2017) Inference of Bivariate generalized exponential distribution based on copula functions. Appl Math Sci 11(24):1155–1186
22.
Genest C, Huang W, Dufour J-M (2013) A regularized goodness-of-fit test for copulas. Journal de la Société Française de Statistique 154:64–77MathSciNet
23.
Kotz S, Balakrishnan N and Johnson NL (2004) Continuous multivariate distributions, Volume 1: Models and applications (Vol. 1). Wiley, NY
24.
McGilchrist CA, Aisbett CW (1991) Regression with frailty in survival analysis. Biometrics 47(2):461–466CrossRefPubMed
Metadata
Title
Progressive Type-II Censored Samples for Bivariate Weibull Distribution with Economic and Medical Applications
Authors
El-Sayed A. El-Sherpieny
Hiba Z. Muhammed
Ehab M. Almetwally
Publication date
24-03-2022
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 1/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-022-00375-y

Other articles of this Issue 1/2024

Machine Learning Algorithms for Crime Prediction under Indian Penal Code

Performances of Machine Learning Models for Diagnosis of Alzheimer’s Disease

Prediction Control Charts: A New and Flexible Artificial Intelligence-Based Statistical Process Control Approach

Deep Neural Network (DNN) Mechanism for Identification of Diseased and Healthy Plant Leaf Images Using Computer Vision

A Review on Applications of Chaotic Maps in Pseudo-Random Number Generators and Encryption

Sentiment Analysis of Twitter Feeds Using Flask Environment: A Superior Application of Data Analysis

Premium Partner

    Image Credits