Comparison of Different Estimators of P [Y < X] for a Scaled Burr Type X Distribution
By Mohammad Z. Raqab, Debasis Kundu. 2005
162 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/c54cae5ffd4fc5fde777083495595632207d4c47
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In Statistics and Probability
- Ahmed Z. Afify
- Debasis Kundu
- Mohammad Z. Raqab
- G. Srinivasa Rao
- Mohamed T. Madi
- Filippo Domma
- Sabrina Giordano
- Zohdy M. Nofal
Citations in the corpus
- A copula-based approach to account for dependence in stress-strength models (2013, background): “In particular, estimation of R when the distributions of X and Y are members of the Burr system has been discussed, among others, by Award and Gharraf (1986), Ivshin and Lumelskii (1995), Ahmed et al. (1997), Surles and Padgett (2001), Mokhlis (2005), Raqab and Kundu (2005), Lio and Tsai (2012).”
- Exponentiated Transmuted Generalized Raleigh Distribution: A New Four Parameter Rayleigh Distribution (2015, background): “Surles and Padgett (1998, 2001), Raqab and Kundu (2005) observed that the generalized Rayleigh distribution works quite well for these strength data.”
- Burr-XII Distribution Parametric Estimation and Estimation of Reliability of Multicomponent Stress-Strength (2015, background): “…were considered by several authors for different distributions (Enis and Geisser (1971), Downtown (1973), Awad and Gharraf (1986), McCool (1991), Nandi and Aich (1994), Surles and Padgett (1998), Raqab and Kundu (2005), Kundu and Gupta (2005, 2006), Raqab et al. (2008), and Kundu and Raqab (2009)).”
- Reliability estimation in a multicomponent stress-strength model for unit Burr III distribution under progressive censoring (2020, background): “One may refer to Rastogi & Tripathi (2012), Zimmer et al. (1998), Wingo (1993), Aslam et al. (2016), Maurya et al. (2017), Raqab & Kundu (2005) and Surles & Padgett (1998) for some further applications of this distribution in many practical studies of interest.”
- Estimation of Reliability in Multicomponent Stress-strength Based on Generalized Exponential Distribution (2014, unknown): “The GRD has been studied extensively by Kundu and Raqab (2005) and Raqab and Kundu (2005).”
- Estimation of Reliability in Multicomponent Stress-strength Based on Generalized Exponential Distribution Estimación de confiabilidad en la resistencia al estrés de multicomponentes basado en la distribución exponencial generalizada (2012, background): “…distributions for the stress-strength random variates, e.g. Enis & Geisser (1971), Downtown (1973), Awad & Gharraf (1986), McCool (1991), Nandi & Aich (1994), Surles & Padgett (1998), Raqab & Kundu (2005), Kundu & Gupta (2005), Kundu & Gupta (2006), Raqab, Modi & Kundu (2008), Kundu & Raqab (2009).”
- ESTIMATION OF RELIABILITY IN MULTICOMPONENT STRESS- STRENGTH MODEL: LOG-LOGISTIC DISTRIBUTION (2010, background): “The survival probability of a single component stress – strength versions have been considered by Enis and Geisser [6], Downtown [5], Awad and Gharraf [1], McCool [12], Nandi and Aich [13], Surles and Padgett [22], Raqab and Kundu [16], Kundu and Gupta [9 &10], Raqab et.al.”
- Inferences on Stress-Strength Reliability from Lindley Distributions (2013, background): “Some of the recent work on the stress-strength model can be obtained in Kundu and Gupta (2005, 2006), Raqab and Kundu (2005), Kundu and Raqab (2009), Krishnamoorthy et al. (2007) and the references cited therein.”
- Prediction for future failures in Weibull distribution under hybrid censoring (2015, methodology): “Using Lemma 1 of Kundu,[10] it follows that d dα2 ln ( d∑ i=1 xαi + (n − d)Tα0 + b2 ) ≥ 0.”
- On estimation of R=P(Y<X) for exponential distribution under progressive type-II censoring (2012, background): “For some of the recent references, the readers may refer to Kundu and Gupta [11, 12], Raqab and Kundu [14], Kundu and Raqab [13], Raqab et al.”
- Estimation of P(Y < X) for the Three-Parameter Generalized Exponential Distribution (2008, methodology): “For illustrative purposes, we are also considering the same transformed data sets used by Raqab and Kundu (2005), the single fibers of 20mm (Data Set I) and 10mm (Data Set II) in gauge lengths with sample sizes 69 and 63, respectively.”