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On the Normalization of Interval Data [PDF]
Mathematics, 2020 The impreciseness of numeric input data can be expressed by intervals. On the other hand, the normalization of numeric data is a usual process in many applications. How do we match the normalization with impreciseness on numeric data?
Regivan Santiago +5 more
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Ontology of Mathematical Modeling Based on Interval Data
Complexity, 2022 An ontological approach as a tool for managing the processes of constructing mathematical models based on interval data and further use of these models for solving applied problems is proposed in this article.
Mykola Dyvak +4 more
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Boundary Data Maps for Schrodinger Operators on a Compact Interval [PDF]
, 2010 We provide a systematic study of boundary data maps, that is, 2 \times 2 matrix-valued Dirichlet-to-Neumann and more generally, Robin-to-Robin maps, associated with one-dimensional Schrodinger operators on a compact interval [0,R] with separated boundary
Stephen Clark +2 more
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Exact and Asymptotic Weighted Logrank Tests for Interval Censored Data: The interval R Package [PDF]
Journal of Statistical Software, 2010 For right-censored data perhaps the most commonly used tests are weighted logrank tests, such as the logrank and Wilcoxon-type tests. In this paper we review several generalizations of those weighted logrank tests to interval-censored data and present an
Michael P. Fay, Pamela A. Shaw
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Statistical Interval for Data Envelopment Analysis
Journal of Basic and Applied Research in Biomedicine, 2022 The techniques of data envelopment analysis (DEA) were largely studied. Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple ...
Asmaa Zeidan +2 more
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Quantile regression with interval data [PDF]
Econometric Reviews, 2021 This paper investigates the identification of quantiles and quantile regression parameters when observations are set valued. We define the identification set of quantiles of random sets in a way that extends the definition of quantiles for regular random variables.
Beresteanu, Arie, Sasaki, Yuya
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A new multi-attribute decision-making method for interval data using support vector machine [PDF]
Big Data and Computing Visions, 2023 There are numerous and various methods for solving the Multi-Attribute Decision-Making (MADM) problems in the literature, such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Elimination and Choice Expressing Reality ...
Ghassem Farajpour Khanaposhtani
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TOPSIS-RTCID for range target-based criteria and interval data
International Journal of Production Management and Engineering, 2021 The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is receiving considerable attention as an essential decision analysis technique and becoming a leading method. This paper describes a new version of TOPSIS with interval data and
A. Jahan, M. Yazdani, K.L. Edwards
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Interval Data Analysis by Revised Interval Regression Model
Transactions of the Society of Instrument and Control Engineers, 1989 Hisao Ishibuchi +2 more
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