M.Z. Anis

Estimation of Reliability of Multicomponent Stress-Strength for a Kumaraswamy Distribution

Abstract This article deals with the Bayesian and non Bayesian estimation of multicomponent stress–strength reliability by assuming the Kumaraswamy distribution. Both stress and strength are assumed to have a Kumaraswamy distribution with common and known shape parameter. The reliability of such a system is obtained by the methods of maximum likelihood and Bayesian approach and the results are compared using Markov Chain Monte Carlo (MCMC) technique for both small and large samples. Finally, two data sets are analyzed for illustrative purposes.

Tests for exponentiality against NBUE alternatives: a Monte Carlo comparison

Testing of various classes of life distributions has been addressed in the literature for more than 45 years. In this paper, we consider the problem of testing exponentiality (which essentially implies no ageing) against positive ageing which is captured by the fairly large class of new better than used in expectation (NBUE) distributions. These tests of exponentiality against NBUE alternatives are discussed and compared. The empirical size of the tests is obtained by simulations. Power comparisons for different popular alternatives are done using Monte Carlo simulations. These comparisons are made for both small and large sample sizes. The paper concludes with a discussion in which suggestions are made regarding the choices of the test when a particular alternative is suspected.

The exact null distribution of the generalized Hollander–Proschan type test for NBUE alternatives

In this note we derive the exact null distribution for the test statistic proposed by Anis and Mitra (2011) for testing exponentiality against NBUE alternatives. As a special case, we obtain the exact null distribution for the test statistic K* proposed by Hollander and Proschan (1975). Selected critical values for different sizes are tabulated for these two statistics. Some remarks concerning the benefits of using the exact distribution are made.

On Testing Exponentiality against NBAFR Alternatives

In this article, we propose an interesting approach for testing exponentiality against NBAFR alternatives. A measure of deviation from exponentiality has been derived on the basis of an inequality which we have proved. A test statistic has been constructed using density estimators and its asymptotic normality established. The consistency of the said test is also proved.

On C pk Assessment in the Presence of Tool Wear

Process capability indices are routinely used in manufacturing industries for process monitoring. A basic assumption while using process capability indices is that there are no assignable causes of variation present. However, when variation due to an assignable cause is present and is tolerated, the conventional methods of capability measurement become inaccurate. In this article, we suggest an estimate of Cpk assuming that the process capability changes dynamically. We obtain an exact form of the sampling distribution in the presence of a systematic assignable cause. We discuss the problem of testing whether a given process is capable. The critical values for different sample sizes are obtained based on the sampling distribution. An example involving tool wear problem is presented.

A simple test of exponentiality against NWBUE family of life distributions: Research Articles

This article examines monthly U.S. inflation rates by means of fractionally integrated time series techniques. We use a procedure of Robinson (J Am Statist Assoc 1994; 89:1420) that permits us to simultaneously test the degrees of integration at both the zero and the seasonal frequencies. The results show that long memory takes place at both frequencies, the orders of integration being in both cases higher than 0 but smaller than 0.5, implying stationarity but long memory behaviour. In addition, the root at the long run or zero frequency seems to play a much more important role than the seasonal one, with shocks affecting the latter component decaying faster than in the former case. Copyright