Data Science, considered as a science by itself, is in general terms, the extraction of
knowledge from data. Symbolic data analysis (SDA) gives a new way of thinking in Data …

The fuzzy rating method has been introduced in psychometric studies as a tool, which allows
the capture of and accurate reflection of the diversity, subjectivity, and imprecision inherent …

Fault detection (FD) is essential for monitoring various chemical processes. Many chemical
processes can be described by input-output models. Partial least squares (PLS) method is …

Along recent years, interval-valued rating scales have been considered as an alternative to
traditional single-point psychometric tools for human evaluations, such as Likert-type or …

Two versions of the generalized sign test and the signed‐rank test for interval‐valued data
(both for one‐sample and paired two‐sample problem) are proposed. These two versions …

In this paper, we discuss the problem of regression analysis in a fuzzy domain. By
considering an iterative Weighted Least Squares estimation approach, we propose a …

A constrained center and range joint model to fit linear regression to interval-valued
symbolic data is introduced. This new method applies both the center and range of the …

Interval‐valued data refers to collection of observations in the form of intervals, rather than
single numbers. It originally arose from situations of imprecision due to factors such as …

Stationarity is a key tool in classical time series. In order to analyze the set-valued time
series, it must be extended to the set-valued case. In this paper, stationary set-valued time …

Interval-valued observations arise in many real-life situations as either the precise
representation of the objective entity or the representation of incomplete knowledge. Thus …