Mohd T. Alodat

This paper extends the work of Elal-Olivero (2010) on the alpha-skew normal distribution. The extension is a multivariate version of Elal-Olivero’s univariate case. Then we study the statistical properties of the new extension such as marginal and conditional distribution, closure under convolution with normal random variate. Furthermore, we illustrate the performance of the distribution using simulated data obtained from the generalized distribution via the Metropolis-Hasting algorithm...

In this paper, a new sampling technique is proposed that carries more information than contained in ranked set sample (RSS). The proposed sampling technique is defined by making the use for the idea of visual grouping of population units with respect to a fixed threshold and RSS. We refer to it as RSS-Grouping technique. Under the best informative RSS-Grouping technique, the maximum likelihood estimator (MLE) of the mean of an exponential distribution is derived...

SUMMARY In the ranked set sampling with set size equal to m, there are mm different possible sampling schemes. The aim of this paper is to characterize the optimal sampling scheme via the Fisher information numbers for normal distribution with known coefficient of variation. Moreover, we use the optimal sampling schemes to obtain unbiased estimators for the mean. Also we compare the estimators to their counterparts under the McIntyre’s ranked set sampling scheme. We show that the MLE under optimal sampling scheme is asymptotically more efficient than its counterpart under McIntyre’s RSS. Keywords: Ranked Set Sampling, Fisher Information, Maximum Likelihood, Normal Distribution, Coefficient of Variation.

In this paper, we introduce a new method to improve the power of the chi-square test for goodness of fit (GOF) of logistic distribution under selective order ranked Set sampling (RSS) based on minimum, median and maximum as compared to simple random sampling (SRS). Based on a simulation study, we illustrate that the chi-square test is found to be more powerful under selective order RSS when compared to SRS, particularly for minimum and maximum. However, for the case of median RSS, the test is found to be more powerful under SRS. To investigate these results further, the Kullback- Leibler information (KLI) is applied and similar results are found. Keywords: Goodness of fit test, chi-square test, logistic distribution, ranked set sample, simple random sample.

In this paper, we consider the problem of constructing confidence intervals for the normal population mean when the coefficient of variation is known. We obtain 13 confidence intervals using different pivots. Also we conduct a simulation study to compare the expectations as well as the standard deviations of the intervals lengths. Keywords: Coefficient of Variation, Normal Distribution, Pivotal Method, Confidence Interval.

The moving extreme ranked set sampling, introduced by Alodat and Al-Saleh (2001), is a modification of the well known ranked set sampling approach that was proposed by McIntyre (1952). In this paper, we suggest new estimators for the simple linear regression parameters under the moving extreme ranked set sampling scheme. Moreover, we show that the proposed estimators are more efficient than their counterparts using the simple random sampling approach. We illustrate our ideas and thoughts via simulation and data analysis and conduct a comparison between our approach and the traditional ones. Keywords: Moving ranked set sampling, Ranked set sampling, Simple linear regression.