• International Journal of Reliability and Applications
• /
• v.6 no.1
• /
• pp.1-12
• /
• 2005

A new test for testing that a life distribution is exponential against the alternative that it is harmonic new better (worse) than used in expectation upper tail HNBUET (HNWUET), but not exponential is presented based on the highly popular 'Kernel methods' of curve fitting. This new procedure is competitive with old one in the sense of Pitman's asymptotic relative efficiency, easy to compute and does not depend on the choice of either the band width or kernel. It also enjoys good power.

• International Journal of Reliability and Applications
• /
• v.2 no.2
• /
• pp.81-97
• /
• 2001

Lifetesting problems have been the subject of investigations for over three decades. Most suggested approaches are markedly different from those used in the related but wider goodness of fit problems. In the current investigation, it is demonstrated that a goodness of fit approach is possible in many lifetesting problems and that It results in simpler procedures that are asymptotically equivalent or better than standard ones. They may also have superior finite sample behavior. Several perennial classes are addressed here. The class of increasing failure rate (IFR) and the class of new better than used (NBU) are addressed first. In addition, we provide testing for a newer and practical class of new better than used in convex ordering (NBUC) due to Cao and Wang (1991). Other classes can be developed similarly and this point is illustrated with the classes of new better than used in expectation (NBUE) and harmonic new better than used in expectation (HNBUE).

• International Journal of Reliability and Applications
• /
• v.4 no.4
• /
• pp.171-181
• /
• 2003

This paper proposes a U-test statistic for the problem of testing that a life distribution is exponential against the alternative that it is harmonic new better (worse) than used in expectation upper tail HNBUET (HNWUET), but not exponential on complete data. Selected critical values are tabulated for sample sizes n =5(1)60. The asymptotic normality of the statistic is proved and a comparison is made of the asymptotic efficiency between the statistic and other statistics. The power of the test is studied by simulation. A test for HNBUET in the case of randomly right-censored data is also considered. An application of the proposed test statistic in medical sciences is given.

• KIISE Transactions on Computing Practices
• /
• v.21 no.6
• /
• pp.436-441
• /
• 2015

There are many types of clustering algorithms such as centroid, hierarchical, or density-based methods. Each algorithm has unique data grouping principles, which creates different varieties of clusters. Ordering Points To Identify the Clustering Structure (OPTICS) is a well-known density-based algorithm to analyze arbitrary shaped and varying density clusters, but the obtained clusters only correlate loosely. Hierarchical agglomerative clustering (HAC) reveals a hierarchical structure of clusters, but is unable to clearly find non-convex shaped clusters. In this paper, we provide a novel hierarchy generation framework and application which can aid users by combining the advantages of the two clustering methods.