Many statistical analyses can be undertaken to examine the relationship between two continuous variables within a group of subjects. Two of the main purposes of such analyses are: To assess whether the two variables are associated. There is no distinction between the two variables and no causation is implied, simply association. To enable the value of one variable to be predicted from any known...

In many (audio) processing algorithms, involving manipulation of discrete-time signals, the performance can vary strongly over the repertoire that is used. This may be the case when the signals from the various channels are allowed to be strongly positively or negatively correlated. We propose and analyze a general formula for tracking the (time-dependent) correlation between two signals. Some ...

The currently used techniques for the detection of esophageal cancer usually rely on pathological examination after sectioning and ultrasound imaging. Optical methods have the advantages of better spatial resolution and sensitivity with minimal invasion. Therefore, the development of optical techniques will be helpful for the diagnosis of esophageal cancer at the early stage. In this research, ...

Inference concerning the correlation coefficient of two random variables from the bivariate normal distribution has been investigated by many authors. In particular, Fisher [1915. Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population. Biometrika 10, 507–521] and Hotelling [1953. New light on the correlation coefficient and its trans...

The concordance correlation coefficient is commonly used to assess agreement between two raters or two methods of measuring a response when the data are measured on a continuous scale. However, the situation may arise in which repeated measurements are taken for each rater or method, e.g. longitudinal studies in clinical trials or bioassay data with subsamples. This paper proposes a coefficient...

Even when a healthy individual is studied, his/her erythrocytes in capillaries continually change their shape in a synchronized erratic fashion. In this work, the problem of characterizing the cell behavior is studied from the perspective of bounded correlated random walk, based on the assumption that diffractometric data involves both deterministic and stochastic components. The photometric re...

Feature selection is a fundamental problem in machine learning and data mining. How to choose the most problem-related features from a set of collected features is essential. In this paper, a novel method using correlation coefficient clustering in removing similar/redundant features is proposed. The collected features are grouped into clusters by measuring their correlation coefficient values....

Recently, Fullér et al. [Fuzzy Sets and Systems, 2010] introduced a new f -weighted index of interactivity, ρf (A,B), between marginal possibility distributions A and B of a joint possibility distribution C for any weighting function f . They also left two open questions in connection with the lower limit for f -weighted possibilistic correlation coefficient related to the improved index of int...

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. In this paper we analyze three different recommendation generation algorithms. We look into three different techniques for computing similarities for obtaining recommendations from them. On the basis of various parameters...

In this paper we introduce for the first time the concept of correlation coefficients of interval valued neutrosophic set (INS for short). Respective numerical examples are presented.