Results 261 to 270 of about 179,170 (301)
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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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On the Use of Ordinal Data in Data Envelopment Analysis
Journal of the Operational Research Society, 1993Summary: In many problems involving efficiency analysis using DEA, certain factors may be measurable only on an ordinal scale. Specifically, it may be possible only to rank order the DMUs according to a factor, rather than being able to assign a specific numerical value of that factor to each DMU.
Cook, Wade D. +2 more
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The Ordination of Incidence Data
The Journal of Ecology, 1978SUMMARY (1) Principal components analysis of incidence (presence and absence) data produces a horseshoe effect. A new method, called step-across, is described which removes this effect. (2) From a matrix of joint occurrences, distances are found directly for all positive values.
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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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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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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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Ridit Analysis on Ordinal Data
Western Journal of Nursing Research, 1996W, Sermeus, L, Delesie
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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
Ordinal regression: A review and a taxonomy of models
Wiley Interdisciplinary Reviews: Computational Statistics, 2022Gerhard Tutz
exaly