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

Detection of FLT3-ITDMutation in Twenty ChildwithAcuteMyeloidLeukemia in One Iraqi Teaching Hospital

Background:Pediatric acute myeloid leukemia (AML) has a poor prognosis, and novel therapies are needed. The FLT3 tyrosine kinase inhibitorsrepresents a promising target in pediatric AML. Objectives:This study was done to estimate the frequency of FLT3- ITD mutation in childhood acute myeloid leukemia using conventional PCR & correlate this mutation with the clinical presentation and response to induction therapy. Patients, Materials &Methods: Twenty children with AML, and 16 children with reactive bone marrow as negative control were enrolled in this study. Those patients were attending Child Welfare Teaching Hospital in Baghdad from March 2010 to July 2011 .For each patient hematological investigations including complete blood picture, and bone marrow aspiration were done.FLT3-ITD mutation was detected by conventional PCR technology using specific primers. Complete hematological remission achievement after induction chemotherapy was assessed by clinical examinations and full laboratory investigations. Results: Out of 20 AML children who participated in this study, 2 (10%) had FLT3-ITD mutation. The mean age of patients who had the mutation was higher than those without the mutation; and the mutated patientswere males, (P> 0.05).The FLT3-ITD mutation showed no correlation to clinical presentation.The peripheral blood & bone marrow blast cell percent werenon significantly higherin mutated patients as compared to non mutated patients. Regardingits relation to FAB classification, the FLT3-ITD mutation was only detected in M3(1/20) and M3v(1/20), and no mutation was found in other subtypes(M1,M2,M5). Furthermore, mutated patients showed lower response to inductiontherapy as compared to non mutated patients. Conclusions: This is a noval study in one Iraqi teaching hospital to detect FLT3-ITD mutation by using conventional PCR in children with AML. This mutation was detected in 10% of thosechildren , and since they were male,older age group,and presented with higher peripheral blood &bone marrow blast cell percent thus we may propose that it may be used as a marker for the aggressiveness of the disease and can be used to modulate the treatment strategy for those patients

Goodness of Fit Test for Gumbel Distribution Based on Kullback-Leibler Information Using Several Different Estimators

Abstract In this paper, our objective is to test the statistical hypothesis is a known distribution function. In this study, a goodness of fit test statistics for Gumbel distribution based on Kullback-Leibler information is studied. The performance of the test under simple random sampling is investigated using Monte Carlo simulation. The Gumbel parameters are estimated by using several methods of estimation such as maximum likelihood, order statistics, moments, and L-moments. Ten different distributions are considered under the alternative hypothesis. For all the distributions considered, it is found that the test statistics based on estimators found by moment and order statistic methods have the highest power, except for weibull and Lognormal distributions

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