Browsing by Subject "Nonparametric statistics"
Now showing items 1-11 of 11
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(2011-10-21)The protein structure prediction problem consists of determining a protein’s three-dimensional structure from the underlying sequence of amino acids. A standard approach for predicting such structures is to conduct a ...
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(Texas A&M University. Libraries, 1989)The focus of this work is to derive functional and graphical statistical techniques for the two sample problem suitable for implementation in modern computing environments. In the two sample problem, it is desired to test ...
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(Texas A&M University. Libraries, 1981)Parzen (1979) suggests a location and scale model for the quantile function (inverse distribution function) of a random variable. We extend this model to the two sample and k-sample problems and some results are given ...
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(Texas A&M University. Libraries, 1981)The development of quantitive research intergation for a large number of studies on a given topic leading to Glass's technique of meta-analysis using calculated effect size is examined. Nonparametric statistical data ...
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(Texas A&M University. Libraries, 1980)In this dissertation, an approach to representing the covariance structure of spatial random variables is presented. A number of methods for fitting polygonal functions to variograms are demonstrated. Techniques for ...
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(Texas A&M University. Libraries, 1982)In this dissertation, the Pyke-Shorack theorem for linear rank statistics is generalized to include testing for the equality of the marginal distributions in a bivariate population. This generalization is used to develop ...
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(Texas A&M University. Libraries, 1986)
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(Texas A&M University. Libraries, 1985)In this dissertation, weak convergence results for dependent sequences are used to derive the asymptotic distribution of linear rank statistics for the two sample problem. It is shown that the asymptotic variance of linear ...
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(Texas A&M University. Libraries, 1992)When one fits a parametric model to data it is advisable to test the adequacy of the model through goodness-of-fit techniques. A nuisance of many existing nonparametric tests is that they depend on a smoothing parameter ...
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(Texas A&M University. Libraries, 1990)In regression analysis, it is always important to test the validity of the assumed model prior to making inferences regarding the population of interest. In this investigaton, we utilize nonparametric regression techniques ...
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(2009-06-02)Functional data analysis (FDA) is an active field of statistics, in which the primary subjects in the study are curves. My dissertation consists of two innovative applications of functional data analysis in biology. The ...