Reliability estimation in a multicomponent stress–strength based on unit-Gompertz distribution

2019 ◽  
Vol 37 (3) ◽  
pp. 428-450
Author(s):  
Mayank Kumar Jha ◽  
Sanku Dey ◽  
Yogesh Mani Tripathi
Keyword(s):  
System Reliability ◽  
Scale Parameter ◽  
Hazard Rates ◽  
Content Type ◽  
Bayes Estimates ◽  
Gompertz Distribution ◽  
Common Scale ◽  
The Common ◽  
Hpd Intervals ◽  
Highest Posterior Density

Purpose The purpose of this paper is to estimate the multicomponent reliability by assuming the unit-Gompertz (UG) distribution. Both stress and strength are assumed to have an UG distribution with common scale parameter. Design/methodology/approach The reliability of a multicomponent stress–strength system is obtained by the maximum likelihood (MLE) and Bayesian method of estimation. Bayes estimates of system reliability are obtained by using Lindley’s approximation and Metropolis–Hastings (M–H) algorithm methods when all the parameters are unknown. The highest posterior density credible interval is obtained by using M–H algorithm method. Besides, uniformly minimum variance unbiased estimator and exact Bayes estimates of system reliability have been obtained when the common scale parameter is known and the results are compared for both small and large samples. Findings Based on the simulation results, the authors observe that Bayes method provides better estimation results as compared to MLE. Proposed asymptotic and HPD intervals show satisfactory coverage probabilities. However, average length of HPD intervals tends to remain shorter than the corresponding asymptotic interval. Overall the authors have observed that better estimates of the reliability may be achieved when the common scale parameter is known. Originality/value Most of the lifetime distributions used in reliability analysis, such as exponential, Lindley, gamma, lognormal, Weibull and Chen, only exhibit constant, monotonically increasing, decreasing and bathtub-shaped hazard rates. However, in many applications in reliability and survival analysis, the most realistic hazard rates are upside-down bathtub and bathtub-shaped, which are found in the unit-Gompertz distribution. Furthermore, when reliability is measured as percentage or ratio, it is important to have models defined on the unit interval in order to have plausible results. Therefore, the authors have studied the multicomponent stress–strength reliability under the unit-Gompertz distribution by comparing the MLEs, Bayes estimators and UMVUEs.

Improved Estimation of the Common Scale Parameter of Several Pareto Distributions

1992 ◽  
Vol 42 (3-4) ◽  
pp. 177-190 ◽  
Author(s):  
Dipak K. De ◽  
Pei-San Liao Liu
Keyword(s):  
Scale Parameter ◽  
Minimum Variance ◽  
New Class ◽  
Numerical Studies ◽  
Pareto Distributions ◽  
Common Scale ◽  
Wage Distributions ◽  
Different Shapes ◽  
The Common ◽  
Improved Estimators

In this paper, we consider the estimation of the common scale parameter of several Pareto distributions with unknown and unequal shape parameters. This problem often arises in practice, for example, when we have several independent wage distributions each having a Pareto distribution with different shapes but common scale parameter which may be the minimum wage rate. A new class of improved estimators is obtained which dominates the Maximum Likelihood Estimator (MLE) and the Uniformly Minimum Variance Unbiased Estimators (UMVUE) under the Mean Square Error (MSE) and Pitman Nearness. (PN) criterion. Numerical studies indicate the amount of improvements are highly significant.

Multicomponent stress-strength reliability estimation based on unit generalized Rayleigh distribution

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mayank Kumar Jha ◽  
Yogesh Mani Tripathi ◽  
Sanku Dey
Keyword(s):  
Numerical Study ◽  
Reliability Estimation ◽  
Least Square ◽  
Estimation Methods ◽  
Average Height ◽  
Prior Distributions ◽  
Content Type ◽  
Bounded Interval ◽  
Common Scale ◽  
Highest Posterior Density

PurposeThe purpose of this article is to derive inference for multicomponent reliability where stress-strength variables follow unit generalized Rayleigh (GR) distributions with common scale parameter.Design/methodology/approachThe authors derive inference for the unknown parametric function using classical and Bayesian approaches. In sequel, (weighted) least square (LS) and maximum product of spacing methods are used to estimate the reliability. Bootstrapping is also considered for this purpose. Bayesian inference is derived under gamma prior distributions. In consequence credible intervals are constructed. For the known common scale, unbiased estimator is obtained and is compared with the corresponding exact Bayes estimate.FindingsDifferent point and interval estimators of the reliability are examined using Monte Carlo simulations for different sample sizes. In summary, the authors observe that Bayes estimators obtained using gamma prior distributions perform well compared to the other studied estimators. The average length (AL) of highest posterior density (HPD) interval remains shorter than other proposed intervals. Further coverage probabilities of all the intervals are reasonably satisfactory. A data analysis is also presented in support of studied estimation methods. It is noted that proposed methods work good for the considered estimation problem.Originality/valueIn the literature various probability distributions which are often analyzed in life test studies are mostly unbounded in nature, that is, their support of positive probabilities lie in infinite interval. This class of distributions includes generalized exponential, Burr family, gamma, lognormal and Weibull models, among others. In many situations the authors need to analyze data which lie in bounded interval like average height of individual, survival time from a disease, income per-capita etc. Thus use of probability models with support on finite intervals becomes inevitable. The authors have investigated stress-strength reliability based on unit GR distribution. Useful comments are obtained based on the numerical study.

scholarly journals From “Technical Newbies” to “Optimistic Politicians”

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
James Prater ◽  
Konstantinos Kirytopoulos ◽  
Tony Ma
Keyword(s):  
Information Technology ◽  
Quantitative Research ◽  
Valuable Insight ◽  
Scheduling Problems ◽  
Information Technology Projects ◽  
Content Type ◽  
Common Causes ◽  
The Common ◽  
Project Estimation ◽  
Engineering Projects

Purpose Despite the advent of sophisticated control methods, there are still significant issues regarding late delivery of information technology projects. The purpose of this paper is to investigate the common causes of scheduling problems specifically in the information technology projects context. Design/methodology/approach Through a quantitative research, the importance of those causes, as well as the underpinning factors driving them, is explored. The causes are ranked according to their relative important index, and exploratory factor analysis is employed to reveal underlying dimensions (factors) of these causes. Findings From the analysis, four factors were extracted, namely, “Dataless Newbie,” “Technical Newbie,” “Pragmatic Futurist” and “Optimistic Politician.” These factors explain the different latent conditions that lead to scheduling problems in information technology projects. Practical implications The key contribution of this research is that it enlightens the latent conditions underpinning scheduling problems. Also, the evidence provides that schedule development for information technology projects is impacted by the same causes that impact engineering projects, and that applying a number of mitigation techniques widely used within the engineering area, such as reference class, would, no doubt, not only improve information technology schedules but also reduce the political pressures on the project manager. Originality/value This research provides a valuable insight into understanding the underlying factors for poor project estimation.

Unveiling the myths of M&A integration: challenging general management and consulting practice

2015 ◽  
Vol 36 (2) ◽  
pp. 16-24 ◽  
Author(s):  
Florian Bauer ◽  
Julia Hautz ◽  
Kurt Matzler
Keyword(s):  
Design Methodology ◽  
Research Management ◽  
Integration Process ◽  
Senior Managers ◽  
Content Type ◽  
Corporate Development ◽  
General Management ◽  
Quantitative Studies ◽  
The Common ◽  
Successful Integration

Purpose – The purpose of this paper is to detect and challenge generally accepted management and consulting practice in Mergers & Acquisitions (M&As). M&As have been an important issue in strategic management and corporate development for decades. The integration process of two separate entities has been found to be of importance, and has, accordingly, received a significant amount of attention by research, management and consulting literature. Based on these insights, managers tend to rely on well-established and generally accepted rules developed by practice and consultants that should support a successful integration process and the generation of value. Nonetheless, M&As’ efforts still often fail to create value. So is the common practice of the established drivers and beneficial consequences of the integration of M&As right, or do the experiences of consultants, companies and managers reveal something different? Design/methodology/approach – To understand these challenges, the authors spent four years studying M&A projects and subsequent integration processes of more than 400 companies that engaged in M&A efforts. The data derived from four survey-based quantitative studies among more than 430 CEOs, CFOs and other senior managers in the field of M&As and personal interviews that were conducted to get in-depth insights. Findings – This extensive research on the efforts and projects of M&As over many years and including many companies reveals that successful integration processes are complex, social and culturally dependent endeavors and that the application of commonly accepted and established principles oversimplifies and disregards the interdependencies. Originality/value – The present paper unveils four established principles concerning the successful integration after M&As as tenacious myths and provides more differentiated insights into value-destroying and value-creating mechanisms in M&As.

Volatility discovery in cryptocurrency markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thomas Dimpfl ◽  
Dalia Elshiaty
Keyword(s):  
Design Methodology ◽  
Stochastic Volatility Model ◽  
Discrete Version ◽  
Data Series ◽  
Content Type ◽  
Vector Autoregressive ◽  
Volatility Model ◽  
Information Shares ◽  
The Common ◽  
To Come

PurposeCryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, the aim of this paper is to investigate which one of the cryptocurrency markets contributes the most to the common volatility component inherent in the market.Design/methodology/approachThe paper extracts each of the cryptocurrency's markets' latent volatility using a stochastic volatility model and, subsequently, models their dynamics in a fractionally cointegrated vector autoregressive model. The authors use the refinement of Lien and Shrestha (2009, J. Futures Mark) to come up with unique Hasbrouck (1995, J. Finance) information shares.FindingsThe authors’ findings indicate that Bitfinex is the leading market for Bitcoin and Ripple, while Bitstamp dominates for Ethereum and Litecoin. Based on the dominant market for each cryptocurrency, the authors find that the volatility of Bitcoin explains most of the volatility among the different cryptocurrencies.Research limitations/implicationsThe authors’ findings are limited by the availability of the cryptocurrency data. Apart from Bitcoin, the data series for the other cryptocurrencies are not long enough to ensure the precision of the authors’ estimates.Originality/valueTo date, only price discovery in cryptocurrencies has been studied and identified. This paper extends the current literature into the realm of volatility discovery. In addition, the authors propose a discrete version for the evolution of a markets fundamental volatility, extending the work of Dias et al. (2018).

Modeling multi-state system reliability analysis in a power station under fatal and nonfatal shocks: a simulation approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Reza Pourhassan ◽  
Sadigh Raissi ◽  
Arash Apornak
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
System Performance ◽  
Failure Process ◽  
State System ◽  
Failure Behavior ◽  
Simulation Approach ◽  
Critical System ◽  
Content Type ◽  
System Reliability Analysis

PurposeIn some environments, the failure rate of a system depends not only on time but also on the system condition, such as vibrational level, efficiency and the number of random shocks, each of which causes failure. In this situation, systems can keep working, though they fail gradually. So, the purpose of this paper is modeling multi-state system reliability analysis in capacitor bank under fatal and nonfatal shocks by a simulation approach.Design/methodology/approachIn some situations, there may be several levels of failure where the system performance diminishes gradually. However, if the level of failure is beyond a certain threshold, the system may stop working. Transition from one faulty stage to the next can lead the system to more rapid degradation. Thus, in failure analysis, the authors need to consider the transition rate from these stages in order to model the failure process.FindingsThis study aims to perform multi-state system reliability analysis in energy storage facilities of SAIPA Corporation. This is performed to extract a predictive model for failure behavior as well as to analyze the effect of shocks on deterioration. The results indicate that the reliability of the system improved by 6%.Originality/valueThe results of this study can provide more confidence for critical system designers who are engaged on the proper system performance beyond economic design.

Sign in / Sign up

Export Citation Format

Share Document