In this paper, we study the estimation for stress-strength reliability of the system with multiple types of components based on survival signature. In the situation that different types of components are subjected to different types of random stresses, the maximum likelihood estimator, maximum spacing estimator, bootstrap-p confidence interval, two point estimators and generalized confidence interval using generalized pivotal quantity for system stress-strength reliability are derived under the assumption that the stresses and strengths variables follow the Gompertz distributions with common or unequal scale parameters. Additionally, when the stresses and strengths variables follow the Gompertz distributions with unequal scale parameters, a modified generalized confidence interval for the system stress-strength reliability based on the Fisher Z transformation is also proposed. In the situation that the system is subjected to the common stress, the above point estimators and confidence intervals for the system stress-strength reliability are also developed. Monte Carlo simulations are performed to compare the performance of these point estimators and confidence intervals. A real data analysis is presented for an illustration of the findings. (C) 2018 Elsevier B.V. All rights reserved.
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Indian Sch Mines, Indian Inst Technol, Dept Math & Comp, Dhanbad, Bihar, IndiaIndian Sch Mines, Indian Inst Technol, Dept Math & Comp, Dhanbad, Bihar, India
Jana, Nabakumar
Bera, Samadrita
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Indian Sch Mines, Indian Inst Technol, Dept Math & Comp, Dhanbad, Bihar, IndiaIndian Sch Mines, Indian Inst Technol, Dept Math & Comp, Dhanbad, Bihar, India
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Imam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi ArabiaImam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi Arabia
Elbatal, Ibrahim
Hassan, Amal S.
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Cairo Univ, Fac Grad Studies Stat Res, 5 Dr Ahmed Zewail St, Giza 12613, EgyptImam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi Arabia
Hassan, Amal S.
Diab, L. S.
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Imam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi ArabiaImam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi Arabia
Diab, L. S.
Ben Ghorbal, Anis
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Imam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi ArabiaImam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi Arabia
Ben Ghorbal, Anis
Elgarhy, Mohammed
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Beni Suef Univ, Fac Sci, Math & Comp Sci Dept, Bani Suwayf 62521, Egypt
Higher Inst Adm Sci, Dept Basic Sci, Belbeis 44621, EgyptImam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi Arabia
Elgarhy, Mohammed
El-Saeed, Ahmed R.
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Obour High Inst Management & Informat, Dept Basic Sci, Obour 11828, EgyptImam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi Arabia