Research ArticleOpen accessIn the author namesEstimation of the Extreme Value Type I Distribution by the Method of LQ-MomentsAni Shabri, Abdul Aziz JemainProblem statement: The study evaluated the effectiveness of the various quantile estimators of the LQ-moments method for estimating parameters of the Extreme Value Type 1 (EV1) distribution. Approach: The performances of the LQ-moments were analyzed and compared against a widely used method of L-moments by using simulated samples of both EV1 and generalized Lambda distribution, focusing on small and moderate … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 7,043 accessesView PDFCite
Research ArticleOpen accessIn the author namesForecasting Gold Prices Using Multiple Linear Regression MethodZ. Ismail, A. Yahya, A. ShabriProblem statement: Forecasting is a function in management to assist decision making. It is also described as the process of estimation in unknown future situations. In a more general term it is commonly known as prediction which refers to estimation of time series or longitudinal type data. Gold is a precious yellow commodity once used as money. It was made … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 11,099 accessesView PDFCite
Research ArticleOpen accessIn the author namesLQ-Moments: Application to the Log-Normal distributionAni Shabri, Abdul A. JemainMudolkar and Hutson (1998) extended L-moments to new moment like entitles called LQmoments (LQMOM). The LQMOM are constructed by using functional defining the quick estimators, where the parameters of quick estimator take the values p = 0, α = 1 for the median, p = 1/4, α = 1/4 for the trimean and p = 0.3, α = 1/3 for … …Journal of Mathematics and Statistics, Vol. 2, Issue 3 · 30 Sep 2006 · 7,000 accessesView PDFCite