• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.2
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• pp.99-106
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• 1999

In this paper, the spline hazard rate model to the randomly censored data is introduced. The unknown hazard rate function is expressed as a linear combination of B-splines which is constrained to be linear(or constant) in tails. We determine the coefficients of the linear combination by maximizing the likelihood function. The number of knots are determined by Bayesian Information Criterion. Examples using simulated data are used to illustrate the performance of this method under presenting the random censoring.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.561-570
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• 2003

We propose a nonparametric test procedure for checking the proportionality assumption between hazard functions using a functional equation. Because of the involvement of censoring distribution function, we consider the large sample case only and obtain the asymptotic normality of the proposeed test statistic. Then we discuss the rationale of the use of the functional equation, give some examples and compare the performances with Andersen's procedure by computing powers through simulations.

• International Journal of Reliability and Applications
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• v.14 no.1
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• pp.27-39
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• 2013

In this article, a new model based on the Rayleigh distribution is introduced. This model is useful and practical in physics, reliability, and life testing. The statistical and reliability properties of this model are presented, including moments, the hazard rate, the reversed hazard rate, and mean residual life functions, among others. In addition, it is shown that the distributions of the new model are ordered regarding the strongest likelihood ratio ordering. Four estimating methods, namely, method of moment, maximum likelihood method, Bayes estimation, and uniformly minimum variance unbiased, are used to estimate the parameters of this model. Simulation is used to calculate the estimates and to study their properties. Finally, the appropriateness of this model for real data sets is shown by using the chi-square goodness of fit test and the Kolmogorov-Smirnov statistic.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.623-632
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• 2014

We shall consider the estimation for the parameter and the right tail probability in a general exponential distribution. We also shall consider the estimation of the reliability P(X < Y ) and the skewness trends of the density function of the ratio X=(X+Y) for two independent general exponential variables each having different shape parameters and known scale parameter. We then shall consider the estimation of the failure rate average and the hazard function for a general exponential variable having the density function with the unknown shape and known scale parameters, and for a bivariate density induced by the general exponential density.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.405-411
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• 2004

In the analysis of cancer data, it is important to make inferences of survival function and to assess the effects of covariates. Cox's proportional hazard model(PHM) and Beran's nonparametric method are generally used to estimate the survival function with covariates. We adjusted the incomplete survival time using the Buckley and James's(1979) pseudo random variables, and then proposed the estimator for the conditional survival function. Also, we carried out the simulation studies to compare the performances of the proposed method.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.399-409
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• 2016

Many of studies have suggested the modifications on Weibull distribution to model the non-monotone hazards. In this paper, we combine two cumulative hazard functions and propose a new modified Weibull distribution function. The newly suggested distribution will be named as a new flexible Weibull distribution. Corresponding hazard function of the proposed distribution shows flexible (monotone or non-monotone) shapes. We study the characteristics of the proposed distribution that includes ageing behavior, moment, and order statistic. We also discuss an estimation method for its parameters. The performance of the proposed distribution is compared with existing modified Weibull distributions using various types of hazard functions. We also use real data example to illustrate the efficiency of the proposed distribution.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.800-806
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• 2018

Software efficiency is the probability of failure free use in operating environments, and is the most fundamental factor affecting software system stability. The malfunction of the computer system used in the information technology field may cause a significant loss in the related industry. Therefore, in this study, we analyze the attributes of software reliability models that depend on various hazard functions based on finite fault NHPP model with software failure time data. The hazard function pattern of proposed model is constant for the Goel-Okumoto model, and the Minimax and Rayleigh models follow the incremental pattern, but the hazard function increase value of the Minimax model is smaller than that of the Rayleigh model and the Goel-Okumoto model. Also, the Minimax model was relatively efficient because the true value error of the mean value function m(t) and the mean square error (MSE) of the Minimax model were smaller than those of the Rayleigh and Goel-Okumoto models. The results of this study are expected to be useful for software developers as basic information about the hazard function.

• Nonlinear Functional Analysis and Applications
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• v.28 no.3
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• pp.793-800
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• 2023

In this paper, we propose a generalization of Lindley distribution (GLD) via a special structure that is concern with progressively Type-II right censoring and time failure data. We study the modern properties that we have built by such combination, for example, survival function, hazard function, moments, and estimation by non-Bayesian methods. Application on some selected data related to Lindley distribution (LD) and (ED) have been employed to find out the best distribution that can fit data comparing with the GLD.

• International Journal of Reliability and Applications
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• v.1 no.2
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• pp.133-143
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• 2000

Data from weighted distributions appear, among other situations, when some of the data are missing or are damaged, a case that is important in reliability and life testing. The kernel method for hazard rate estimation is discussed for these data where the basic large sample properties are given. As a by product, the basic properties of the kernel estimate of the distribution function for data from weighted distribution are presented.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.491-496
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• 1997

For the survival data analysis of no covariate the discount survival model is proposed to estimate the time-varying hazard rate and the survival function recursively. In comparison with the covariate case it provide the distributionally explicit evolution of hazard rate between time intervals under the assumption of a conjugate gamma distribution. Also forecasting of the hazard rate in the next time interval is suggested, which leads to the forcecasted survival function.