Results 291 to 300 of about 534,689 (331)
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2007
The standard Data Envelopment Analysis (DEA) method requires that the values for all inputs and outputs are known exactly. When some inputs and output are imprecise data, such as interval or bounded data, ordinal data, and ratio bounded data, the resulting DEA model becomes a non-linear programming problem.
Yao Chen, Joe Zhu
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The standard Data Envelopment Analysis (DEA) method requires that the values for all inputs and outputs are known exactly. When some inputs and output are imprecise data, such as interval or bounded data, ordinal data, and ratio bounded data, the resulting DEA model becomes a non-linear programming problem.
Yao Chen, Joe Zhu
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A Characterization of Ordinal Data
2000Ordinal data are looked at from two different points of view, the Coombs-type scaling and the Guttman-type quantification. Some mathematical relations of several methods within the Guttman-type methods are presented, showing them to be mathematically equivalent.
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1991
Convexity is a leading idea in data analysis, although it is mostly involved on an informal level; in particular, convexity in ordinal data has not been elaborated as a well defined tool. This paper presents a first discussion of convexity definitions in connection with examples of ordinal data.
Selma Strahringer, Rudolf Wille
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Convexity is a leading idea in data analysis, although it is mostly involved on an informal level; in particular, convexity in ordinal data has not been elaborated as a well defined tool. This paper presents a first discussion of convexity definitions in connection with examples of ordinal data.
Selma Strahringer, Rudolf Wille
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Correlations with ordinal data
Journal of Econometrics, 1974In most econometric analyses the data are uniquely defined except for a choice of units (e.g., physical quantities or value flows) and/or a location parameter (e.g., time). In some cases the cardinality of the data is less clear. For instance, building inspectors may rate various aspects of dwellings and neighborhoods on a one to five scale, the ...
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Ridit Analysis on Ordinal Data
Western Journal of Nursing Research, 1996W, Sermeus, L, Delesie
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The problem we aim to address in this dissertation is to develop a more straightforward method for examining correlation-related diagnostics in ordinal data. Analyzing data that falls between numerical and categorical types can be challenging, particularly when it involves ordinal variables.
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Convolutional Ordinal Regression Forest for Image Ordinal Estimation
IEEE Transactions on Neural Networks and Learning Systems, 2022Haiping Zhu +2 more
exaly
Relative margin induced support vector ordinal regression
Expert Systems With Applications, 2023Fa Zhu, Xingchi Chen, Shuo Chen
exaly
Performance of Estimators for Confirmatory Factor Analysis of Ordinal Variables with Missing Data
Structural Equation Modeling, 2020Pui-Wa Lei, Levi K Shiverdecker
exaly