The Development of Parameter Estimation on Hazard Rate of Trivariate Weibull Distribution

Wahyudi, Irfan; Purhadi, Purhadi; Irhamah,; Sutikno, Sutikno

doi:10.3844/amjbsp.2011.26.35

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…For instance; the Science Publications JMSS trivariate hazard rate function of trivariate liftime distribution was presented by Wahyudi et al (2011).…”

Section: Hazard Ratementioning

confidence: 99%

Length Biased Beta-Pareto Distribution and Its Structural Properties With Application

Nanuwong¹,

Bodhisuwan²

2014

Journal of Mathematics and Statistics

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The concept of length biased distribution can be employed in development of proper models for lifetime data. Its method is adjusting the original probability density function from real data and the expectation of those data. This adjustment can bring about to correct conclusions of models. Therefore, we introduced the Length Biased Beta-Pareto (LBBP) distribution, so-called a new generalized of Pareto distribution in this article. The distribution is more flexible and has some interesting properties such as hazard rate, Renyi and Shannon entropies and other types of distribution. There are several sub-models include in the length biased Pareto, arcsine, log-beta, exponential and beta-Pareto distributions. We apply maximum likelihood estimation to estimate parameters of the distribution. We illustrate the superiority of the LBBP distribution to Norwegian fire claims data. The LBBP distribution seems to be the most appropriate model for this data set, since it provides a significantly better fit than the length biased Pareto and the beta-Pareto distributions. We hope that the LBBP distribution is an alternative distribution can be used in lifetime data analysis and other fields.

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“…For instance; the Science Publications JMSS trivariate hazard rate function of trivariate liftime distribution was presented by Wahyudi et al (2011).…”

Section: Hazard Ratementioning

confidence: 99%

Length Biased Beta-Pareto Distribution and Its Structural Properties With Application

Nanuwong¹,

Bodhisuwan²

2014

Journal of Mathematics and Statistics

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A New Family of Generalized Gamma Distribution and Its Application

Suksaengrakcharoen¹

2014

Journal of Mathematics and Statistics

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The mixture distribution is defined as one of the most important ways to obtain new probability distributions in applied probability and several research areas. According to the previous reason, we have been looking for more flexible alternative to the lifetime data. Therefore, we introduced a new mixed distribution, namely the Mixture Generalized Gamma (MGG) distribution, which is obtained by mixing between generalized gamma distribution and length biased generalized gamma distribution is introduced. The MGG distribution is capable of modeling bathtub-shaped hazard rate, which contains special submodels, namely, the exponential, length biased exponential, generalized gamma, length biased gamma and length biased generalized gamma distributions. We present some useful properties of the MGG distribution such as mean, variance, skewness, kurtosis and hazard rate. Parameter estimations are also implemented using maximum likelihood method. The application of the MGG distribution is illustrated by real data set. The results demonstrate that MGG distribution can provide the fitted values more consistent and flexible framework than a number of distribution include important lifetime data; the generalized gamma, length biased generalized gamma and the three parameters Weibull distributions.

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Implementing Weibull Distribution to Generate Prediction Function for National Final Examination in Papua Province

Manurung¹,

Sediyono²,

Sembiring³

2014

IJCA

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One of Indonesia government's program which is being implemented in the last ten years is to increase the education quality nationally. One of the education quality standards is final examination. Final examination is a concrete form of what the school has given before, during, and after the learning process, so the result of school policy in conducting learning process can be known from the national final examination score. Hence, the result of final examination is totally important to be analyzed and predicted based on the classification tested knowledge field.This thesis examines about the method for estimating the parameters of Weilbul distribution with likelihood estimation maximum method by using newton raphson iteration to the final examination score in Papua province. The result of this research is a distribution function which can be used to predict the next year national final examination score based on the previous condition and score that the students achieved. The function of the prediction that has been found before can be used to estimate what kind of condition can be applied to improve the learning quality so that the score of final examination will be better than before.

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The Development of Parameter Estimation on Hazard Rate of Trivariate Weibull Distribution

Cited by 3 publications

References 9 publications

Length Biased Beta-Pareto Distribution and Its Structural Properties With Application

Length Biased Beta-Pareto Distribution and Its Structural Properties With Application

A New Family of Generalized Gamma Distribution and Its Application

Implementing Weibull Distribution to Generate Prediction Function for National Final Examination in Papua Province

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