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

Weighting Methods In The Construction Of Area Deprivation Indices

This study applies and compares several weighted average (WA) methods and Principal Component Analysis (PCA) for the construction of composite area-based deprivation index. The WA methods are based on weights that depend on standard deviation, correlation and data entropy. This paper also proposes three new approaches of WA method by suggesting their respective weights to depend on mean absolute deviation, inter-quartile range and data entropy where the probability is estimated by empirical density function and Gaussian kernel function. The deprivation indices produced by WA methods and PCA are then utilized to rank deprivation level of eighty-one administrative districts in Peninsular Malaysia

Trends in Peninsular Malaysia rainfall data during the Southwest monsoon and Northeast monsoon seasons: 1975-2004

This study investigated the spatial pattern and trends of the daily rainfall data in Peninsular Malaysia based on seasonal rainfall indices. Five rainfall indices which describe the main characteristics of rainfall, the total amount of rainfall, frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity, were employed in this study. The statistics of rainfall indices were calculated in terms of their means for four regions in Peninsular Malaysia for the period 1975 to 2004. The findings indicate that the southwest monsoon had the greatest impact on the western part of the Peninsula, particularly in characterizing the rainfall pattern of the northwest region. During this season, the northwest region could be considered as the wettest region since all rainfall indices tested are higher than in other regions of the Peninsula. Otherwise, the northwest region is denoted as the driest part of the Peninsula during the northeast monsoon period. The northwest region is less influenced by the northeast monsoon because of the existence of the Titiwangsa Range, which blocks the region from receiving heavy rainfall. On the other hand, it is found that the lowlands areas such as the eastern part of the Peninsula are strongly characterized by the northeast monsoonal flow. Based on the results of the Mann-Kendall test, as the trend of the total amount of rainfall and the frequency of wet days during the southwest monsoon decrease at most of the stations, the rainfall intensity increases. In contrast, increasing trends in both the total amount of rainfall and the frequency of wet days were observed at several stations during the northeast monsoon, which give rise to the increasing trend of rainfall intensity. The results for both seasons indicate that there are significantly decreasing trends in the frequency of wet days during the extreme events for most of the stations on the peninsula. However, a smaller number of significant trends was found for extreme intensity

A Robust Firearm Identification Algorithm of Forensic Ballistics Specimens

There are several inherent difficulties in the existing firearm identification algorithms, include requiring the physical interpretation and time consuming. Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. The proposed algorithm comprises Laplacian sharpening filter, clustering-based threshold selection, unweighted least square estimator, and segment a square ROI from the noisy images. A total of 250 simulated noisy images collected from five different pistols of the same make, model and caliber are used to evaluate the robustness of the proposed algorithm. This study found that the proposed algorithm is able to perform the identical task on the noisy images with noise levels as high as 70%, while maintaining a firearm identification accuracy rate of over 90%

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

Perbandingan beberapa ujian kebagusan penyuaian untuk taburan normal dan taburan logistik

Goodness of fit (GOF) test is a statistical technique that can be used to determine whether or not a data set follows certain statistical distributions. There are various GOF statistics that can be applied such as Kolmogorov Smirnov (KS), Anderson-Darling (AD) and Cramer- von- Mises (CV). In this paper a study is conducted to investigate the performance of several selected goodness of fit tests which include KS, AD, CV, three test statistics of Zhang and a proposed modified GOF test which incorporates a variance stabilising transformation. The performance of these tests is studied for testing normal and logistic distributions for various sample sizes. It is found that Zhang’s test is the most powerful and followed closely by our proposed GOF tes