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11 results for “Covariance Test”
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Research ArticleOpen accessEvery word in the titleA Test on the Multivariate Behrens–Fisher Problem in High–Dimensional Data by Block Covariance EstimationParanut Sukcharoen, Samruam ChongcharoenIn this paper, we proposed a new testing statistic for testing the equality of mean vectors from two multivariate normal populations when the covariance matrices are unknown and unequal in high–dimensional data. A new test is proposed based on the idea of keeping more information from the sample covariance matrices as much as possible. A proposed test is invariant under … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 2 Apr 2019 · 7,369 accessesView PDFCite
Research ArticleOpen accessIn the keywordsValidation of Global Financial Crisis on Bursa Malaysia Stocks Market Companies via Covariance StructureShamshuritawati Sharif, Suzilah Ismail, Zurni Omar, Low Huey ThengThe global financial crisis of 2007 to 2009 affects the economic development around the world. It started with US in 2007 and followed by Malaysia in 2008. The purpose of this study is to validate the impact before and beginning of the crisis on seventy seven Bursa Malaysia stocks market companies. Two data sets of 2007 and 2008 were used … …American Journal of Applied Sciences, Vol. 13, Issue 11 · 27 Oct 2016 · 7,568 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Test for Two-Sample Repeated Measures Designs: Effect of High-Dimensional DataBoonyarit Choopradit, Samruam ChongcharoenProblem statement: High-dimensional repeated measures data are increasingly encountered in various areas of modern science since classical multivariate statistics, e.g,. Hotelling’s T2, are not well defined in the case of high-dimensional data. Approach: In this study, the test statistics with no specific form of covariance matrix for analyzing high-dimensional two-sample repeated measures designs with common equal covariance are proposed. The … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 28 Oct 2011 · 7,328 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIdentification of Flutter Derivatives of Bridge Decks in Wind Tunnel Test by Stochastic Subspace IdentificationT. Janesupasaeree, V. BoonyapinyoProblem statement: Flutter derivatives are the essential parameters in the estimations of the flutter critical wind velocity and the responses of long-span cable supported bridges. These derivatives can be experimentally estimated from wind tunnel test results. Generally, wind tunnel test methods can be divided into free decay test and buffeting test. Compared with the free decay method, the buffeting test … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 2 · 30 Jun 2009 · 8,133 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Probit and Logistic Regression Models in the Analysis of Dichotomous OutcomesAmrutha Jose, Mariyamma Philip, Lavanya Tumkur Prasanna, M. ManjulaProbit and logistic regression models are members of the family of generalized linear models, used for estimating the functional relationship between the dichotomous dependent and independent variables. The current study is designed to find the performance of logistic and probit regression models in different conditions under multivariate normality. The objective of the study is to compare the performance of probit … …Current Research in Biostatistics, Vol. 10, Issue 1 · 26 Mar 2020 · 17,036 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust Linear Discriminant AnalysisSharipah Soaad Syed Yahaya, Yai-Fung Lim, Hazlina Ali, Zurni OmarLinear Discriminant Analysis (LDA) is the most commonly employed method for classification. This method which creates a linear discriminant function yields optimal classification rule between two or more groups under the assumptions of normality and homoscedasticity (equal covariance matrices). However, the calculation of parametric LDA highly relies on the sample mean vectors and pooled sample covariance matrix which are sensitive … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 4 Jan 2017 · 7,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractModelling the Error Term of Australia Gross Domestic ProductAyodele Abraham Agboluaje, Suzilah Ismail, Chee Yin YipThe main aim of this study is to model the Gross Domestic Product (GDP) with the new Combine White Noise (CWN) Model and compare the results with the Vector Autoregressive (VAR) Model and Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) Model which are the existing models. The CWN model estimation yields best results with least information criteria and high log likelihood … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 2 Nov 2016 · 6,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractOne-Sided Multivariate Tests for High Dimensional DataSamruam ChongcharoenProblem statement: For a multivariate normal population with size smaller than dimension, n<p, the likelihood ratio tests of the null hypothesis that the mean vector was zero with a one-sided alternative were no longer valid because they involved with sample covariance matrix which was singular. Approach: The test statistics for one-sided multivariate hypotheses with n<p were proposed. Results: The simulation … …Journal of Mathematics and Statistics, Vol. 8, Issue 2 · 20 Jun 2012 · 7,261 accessesView PDFCite
Research ArticleOpen accessIn the abstractInversion of Covariance Matrix for High Dimension DataSamruam ChongcharoenProblem statement: In the testing statistic problem for the mean vector of independent and identically distributed multivariate normal random vectors with unknown covariance matrix when the data has sample size less than the dimension n≤p, for example, the data came from DNA microarrays where a large number of gene expression levels are measured on relatively few subjects, the p×p sample … …Journal of Mathematics and Statistics, Vol. 7, Issue 3 · 27 Jul 2011 · 7,869 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Shuffle Image-Encryption AlgorithmA. A. Yahya, A. M. AbdallaProblem statement: Image encryption needs to be secure by resisting statistical attacks and other types of attacks. Approach: The new algorithm, call it the Shuffle Encryption Algorithm (SEA), applies nonlinear s-box byte substitution. Then, it performed a shuffling operation partially dependent on the input data and uses the given key. Results: SEA was implemented and tested with different data, mainly … …Journal of Computer Science, Vol. 4, Issue 12 · 31 Jul 2009 · 8,353 accessesView PDFCite