Browsing by Subject "Regression analysis"
Now showing items 1-11 of 11
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(Texas A&M University. Libraries, 1980)Consistent with the emerging trend in the educational literature to discount, or in some cases, overlook the unanticipated consequences of model selection on study findings, the intent of this inquiry is to compare and ...
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(Texas A&M University. Libraries, )Parzen (1979) has shown that the estimation of location and scale parameters by linear systematic statistics may be formulated as a problem in regression analysis of a smoothed sample quantile process. In this dissertation, ...
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(Texas A&M University. Libraries, 1990)The problem concerns the analysis of assay data when there have been previous similar experiments. Assay data usually fall under the framework of nonlinear regression when the variability about the regression line is ...
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(Texas A&M University. Libraries, 1981)The focus of this research was on developing a technique for forecasting prices to use in making inventory purchase decisions. The basic tool used to develop the forecasts was multiple regression analysis. The technique ...
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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, 1986)
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(Texas A&M University. Libraries, 1981)In this dissertation a procedure for estimating the parameters of a quantile regression function is investigated. The procedure is based on the work of Parzen (1979a) in the theory of quantile functions and is applicable ...
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(Texas A&M University. Libraries, 1982)The problems of detecting influential observations and collinearity in multiple linear regression are discussed. The commonly used diagnostics of influential observations and collinearity are critically appraised and ...
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(Texas A&M University. Libraries, 1976)In this dissertation the following problems I the area of regression and discriminant analysis have been discussed. (1) Suppose there are m groups or populations and the regression lines of y on k independent variables ...
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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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(Texas A&M University. Libraries, 1989)Tail estimators are proposed which make minimal assumptions and let the data dictate the form of the probability model. These estimators use only the observations in the tail and are based on a unifying density-quantile ...