Mulreg is an interactive computing environment for data exploration, regression modeling, and the visualization and use of regression results. It is designed to allow both statisticians and nonstatisticians easy acces...
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We describe concepts and software for the auditing of data analyses. Auditing begins with the record of a dataanalysis session. The record tells what statements were executed and what objects were accessed or changed...
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We describe concepts and software for the auditing of data analyses. Auditing begins with the record of a dataanalysis session. The record tells what statements were executed and what objects were accessed or changed, and can be processed to recreate chosen statements in the analysis for purposes of verification. It can also be the starting point for asking a variety of questions about the analysis, through an interactive, exploratory interface, as a data analyst’s assistant.
Standard clustering algorithms can completely fail to identify clear cluster structure if that structure is confined to a subset of the variables. A forward selection procedure for identifying the subset is proposed a...
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Standard clustering algorithms can completely fail to identify clear cluster structure if that structure is confined to a subset of the variables. A forward selection procedure for identifying the subset is proposed and studied in the context of complete linkage hierarchical clustering. The basic approach can be applied to other clustering methods, too.
A microcomputer system has been designed to promote uniform and correct epidemiological data handling in the Local Health Units of the National Health Service in Italy. The system allows to define files of any format,...
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This paper proposes using picture processing techniques in the automatic analysis of bathythermograph records. It is shown that by treating and displaying this type of data as a digital picture a much more extensive a...
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This paper proposes using picture processing techniques in the automatic analysis of bathythermograph records. It is shown that by treating and displaying this type of data as a digital picture a much more extensive and useful analysis is possible than with conventional techniques. A description is given of results obtained with an interactive program developed to implement such processing. This program, amongst other things, allows the operator to suppress noise, sharpen edges, enhance various structures and detect events of particular interest.
The unsupervised estimation problem has been conveniently formulated in terms of a mixture density. It has been shown that a criterion naturally arises whose maximum defines the Bayes minimum risk solution. This crite...
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The unsupervised estimation problem has been conveniently formulated in terms of a mixture density. It has been shown that a criterion naturally arises whose maximum defines the Bayes minimum risk solution. This criterion is the expected value of the natural log of the mixture density. By making the assumptions that the component densities in the mixture are truncated Gaussian, the criterion has a greatly simplified form. This criterion can be used to resolve mixtures when the number of classes as well as the class covariances are unknown. In this paper a technique is presented where an assumed test covariance is supplied by an experimenter who uses a test function as a "portable magnifying glass" to examine data. Because the experimenter supplies the covariance and thus the test function, the technique is especially suited for interactive data analysis.
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