• The Korean Journal of Applied Statistics
• /
• v.23 no.6
• /
• pp.1125-1145
• /
• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• Communications for Statistical Applications and Methods
• /
• v.17 no.4
• /
• pp.493-505
• /
• 2010

Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

• Journal of the Korean Statistical Society
• /
• v.18 no.2
• /
• pp.125-134
• /
• 1989

This paper presents optimum simple step-stress accelerated life test plans for the case where the test process is observed periodically at intervals of the same length. Two types of failure data, periodically observed complete data and periodically observed censored data, are considered. An exponential life distribution with a mean that is a log-linear function of stress, and a cumulative exposure model for the effect of changing stress are assumed. For each type of data, the optimum test plan which minimizes the asymptotic variance of the maximum likelihood estimator of the mean life at a design stress is obtained and its behaviors are studied.

• Communications for Statistical Applications and Methods
• /
• v.6 no.2
• /
• pp.443-456
• /
• 1999

The estimation of mean lifetimes in presence of interval censoring with mixed replacement procedure are examined when the distribution s of lifetimes are exponential. it is assumed that due to physical restrictions and/or economic constraints the number of failures is investigated only at several inspection times during the lifetime test; thus there is interval censoring. Comparisons of mixed replacement designs are made with those with and without replacement The maximum likelihood estimator is found in an implicit form. The Cramer-Rao lower bound which is the asymptotic variance of the estimator is derived. The test conditions for minimizing the Cramer-Rao lower bound and minimizing the test costs within a desired width of the Cramer-Rao bound have been studied.

• The Korean Journal of Applied Statistics
• /
• v.7 no.1
• /
• pp.19-34
• /
• 1994

In this paper we propose nonparametric tests of parallelism against umbrella alternatives of slopes in k-regression lines and investigate the asymptotic properties of the proposed test statistics. For the known peak and unknown peak, we suggest the test statistics and show that, from Monte Carlo study, the proposed test statistics have good empirical powers for heavy tailed distributions than the likelihood ratio tests.

• Journal of applied mathematics & informatics
• /
• v.6 no.1
• /
• pp.31-50
• /
• 1999

We revisit the problems of testing three-factor classifica-tion models with a single observation per cell. A common approach in analyzing such nonreplicated data is to omit the highest order in-teraction and regard it as error. This paper discusses the use of a multiplicative model(See and Smith 1996 and 1998) which is applied on residuals in order to separate the variablility due to three-factor interaction from what is counted as random error. in particualr to test the significance of the interaction term we derived an approxi-mated distribution of the likelihood ratio test statistic based on the quadrilinear model known as Tucher's three-mode principal compo-nent model. The derivation utilizes the distribution of the eignevalues of the Wishart matrix.

• International Journal of Reliability and Applications
• /
• v.9 no.1
• /
• pp.31-52
• /
• 2008

In this paper generalized version of the geometric distribution is introduced. This distribution can be considered as a two-parameter generalization of the discrete geometric distribution. The main statistical and reliability properties of this distribution are discussed. Two methods of estimation, namely maximum likelihood method and the method of moments are used to estimate the parameters of this distribution. Simulation is utilized to calculate these estimates and to study some of their properties. Also, asymptotic confidence limits are established for the maximum likelihood estimates. Finally, the appropriateness of this new distribution for a set of real data, compared with the geometric distribution, is shown by using the likelihood ratio test and the Kolmogorove-Smirnove test.

• Journal of Applied Reliability
• /
• v.13 no.2
• /
• pp.87-98
• /
• 2013

Accelerated degradation tests (ADTs) measuring failure-related degradation characteristic at the accelerated condition are widely used to assess the reliability of highly reliable products. Often, however, little degradation could be observed even in single-stress ADTs due to the high reliability of test unit, and as a result poor estimate of the reliability may be obtained. ADTs with multiple stress variables can be employed to overcome such difficulties. In this paper, optimal ADT plans with two stress variables are developed assuming that the degradation characteristic follows Weibull distribution by determining the stress levels, the proportion of test units allocated to each stress level such that the asymptotic variance of the maximum likelihood estimator of the q-th quantile of the lifetime distribution at the use condition is minimized.

• International Journal of Reliability and Applications
• /
• v.5 no.4
• /
• pp.105-113
• /
• 2004

The exponential better (worse) than used EBU (EWU) class of life distributions is considered. A moment inequality is derived for EBU (EWU) distributions which demonstrate that if the mean life is finite, then all moments exist. Based on this inequality, a new test statistic for testing exponentiality against EBU (EWU) is introduced. It is shown that the proposed test is simple, enjoys good power and has high relative efficiency for some commonly used alternatives. Critical values are tabulated for sample sizes n = 5(1)40. A set of real data is used as a practical application of the proposed test in the medical science.

• Journal of the Korean Statistical Society
• /
• v.19 no.2
• /
• pp.128-138
• /
• 1990

In this paper we study the properties of nonparametric tests for testing the null hypothesis of no changes against one sided and two sideds alternatives in scale parameter at unknown point. We first propose two types of nonparametric tests based on linear rank statistics and rank-like statistics, respectively. For these statistics, we drive the asymptotic distributions under the null and contiguous alternatives. The main theoreticla tools used for derivation are the stochastic process representation of the test staistic and the Brownian bridge approximation. We evaluate the Pitman efficiencies of the test for the contiguous alternatives, and also compute empirical power by Monte Carlo simulation.