Browsing by Author "Samruam Chongcharoen, advisor"
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A non-uniform bound on poisson approximation for dependent Bernoulli trials Kanint Teerapabolarn; Samruam Chongcharoen, advisor (National Institute of Development Administration, 2005)
A test for repeated measurements designs with high dimensional data Boonyarit Choopradit; Samruam Chongcharoen, advisor (National Institute of Development Administration, 2011)
Repeated measurements across time on the same subject are frequently observed in several scientific fields. A new challenge to statisticians today is dealing with conditions where the dimension of repeated measurements per subject is larger than the number of subjects, called high dimensional data. High dimensional repeated measurements data are increasingly encountered in various areas of modern science because classical multivariate statistics are not well defined. In this dissertation, test statistics for analyzing high dimensional one- and ...
Analysis of high dimensional multivariate repeated measurements designs Kannigar Hirunkasi; Samruam Chongcharoen, advisor (National Institute of Development Administration, 2011)
A multivariate repeated measurements design is a design applied to measurements of p response variables observed repeatedly over t times on each subject in g groups. There are two different approaches for analyzing multivariate repeated measurements, the Doubly Multivariate Model (DMM) and the Multivariate Mixed Model (MMM). These analyses are based on a classical multivariate test which requires the assumption of MANOVA in that the degrees of freedom of the sum of squares and cross product matrix (SSCP) due to error are larger than its dimension. ...
Tests for covariance matrices with high-dimensional data Saowapha Chaipitak; Samruam Chongcharoen, advisor (National Institute of Development Administration, 2012)
In multivariate statistical analysis, it is a necessity to know the facts regarding the covariance matrix of the data in hand before applying any further analysis. This study focuses on testing hypotheses concerning the covariance matrices of multivariate normal data having the number of variables larger than or equal to the sample size, called high-dimensional data. The two objectives of this study were: first, for one sample data, to develop a test statistic for testing the hypothesis for whether the covariance matrix equals a specified known ...
Two Robust estimators of the population total for sample surveys Kittima Prukpousana; Samruam Chongcharoen, advisor (National Institute of Development Administration, 2006)