Discrimination Between Logistic and Gumbel Distribution

When two distributions have ,approximately ,the  same characteristics, it is often difficult to discriminate between them. In this study, we use the ratio of likelihoods for selecting between the logistic and Gumbel distributions for describing a set of data. The parameters for the logistic and Gumbel distributions are estimated by using maximum likelihood (ML), moments (MOM) and order statistic (OS) methods.  In addition, by using Monte Carlo simulations, discriminating between the two distributions is investigated in terms of the probability of correct selection (PCS) as found based on the different methods of estimation. In general, it is found that the method of ML outperforms all the other methods when the estimators considered are compared in term of efficiency

Modified EDF Goodness of Fit Tests for Logistic Distribution under SRS and RSS

Modified forms of goodness of fit tests are presented for the logistic distribution using statistics based on the empirical distribution function (EDF). A method to improve the power of the modified EDF goodness of fit tests is introduced based on Ranked Set sampling (RSS). Data are collected via the Ranked Set Sampling (RSS) technique (McIntyre, 1952). Critical values for the logistic distribution with unknown parameters are provided and the powers of the tests are given for a number of alternative distributions. A simulation study is presented to illustrate the power of the new method

Bayesian Threshold Moving Average Models

A Bayesian approach in threshold moving average model for time series with two regimes is provided. The posterior distribution of the delay and threshold parameters are used to examine and investigate the intrinsic characteristics of this nonlinear time series model. The proposed approach is applied to both simulated data and a real data set obtained from a chemical system. Key words: Threshold time series, moving average model, Bayesia

Empirical Characteristic Function Approach to Goodness of Fit Tests for the Logistic Distribution under SRS and RSS

The integral of the squares modulus of the difference between the empirical characteristic function and the characteristic function of the hypothesized distribution is used by Wong and Sim (2000) to test for goodness of fit. A weighted version of Wong and Sim (2000) under ranked set sampling, a sampling technique introduced by McIntyre (1952), is examined. Simulations that show the ranked set sampling counterpart of Wong and Sim (2000) is more powerful

Antioxidant and antihypertensive properties of phenolic-protein complexes in extracted protein fractions from Nigella damascena and Nigella arvensis

The study involved the investigation of the antioxidant and antihypertensive properties of the phenolic eprotein complexes obtained from isolated protein fractions from Nigella damascena and Nigella arvensis. Protein fractions from flours made from the seeds of Nigella species were isolated and included albumin, globulin, glutelin-1, glutelin-2 and prolamin. Albumin and glutelin-1 fractions were the predominant proteins in the two Nigella species studied in terms of protein content and percent protein yield. Free phenolics were extracted from the isolated protein fractions by methanol treatment at either 25 C or 60 C followed by acid and base hydrolysis to obtain bound phenolics. The free and bound phenolic composition was assessed by RP-HPLC. The highest phenolic content was observed in the free phenolic extract at 25 C (FP-25 C) in glutelin-2 of both Nigella species. The free and bound phenolics of the protein fractions were tested for angiotensin converting enzyme (ACE) inhibitory and antioxidant activities. The greatest ACE inhibitory activities were seen for the free and bound phenolic extracts obtained from glutelin-2 and globulin fractions of both Nigella species. The highest antioxidant activities were observed in the extracted phenolics from glutelin-1 and globulin from N. damascena and albumin from N. arvensis. Only a weak correlation was seen between the phenolic content of the isolated protein fractions and the ACE inhibitory and antioxidant activities. The present study indicates that phenolic eprotein complexes in the Nigella species have significant antioxidant and ACE inhibitory properties although the bioactivities of the protein fractions are not closely related to their total phenolic content