Correlation Analysis for Exploring Multivariate Data Sets
نویسندگان
چکیده
منابع مشابه
� Amap Interface for Exploring Multivariate Paleoclimate Data
We begin with an abbreviated review of recent approaches to the display of three or more geographically-referenced data variables from the literatures of statistics, computer graphics and cartography. In comparison we describe a method we have developed for exploring relationships among multivariate paleoclimate data pro duced by a global circulation model at Penn State's Earth System Science ...
متن کاملDynamical Correlation for Multivariate Longitudinal Data
Nonparametric methodology for longitudinal data analysis is becoming increasingly popular. The analysis of multivariate longitudinal data, where data on several time courses are recorded per subject, has received considerably less attention, in spite of its importance for practical data analysis. In particular, there is a need for measures and estimates to capture dependency between the compone...
متن کاملMultivariate Maximal Correlation Analysis
Correlation analysis is one of the key elements of statistics, and has various applications in data analysis. Whereas most existing measures can only detect pairwise correlations between two dimensions, modern analysis aims at detecting correlations in multi-dimensional spaces. We propose MAC, a novel multivariate correlation measure designed for discovering multidimensional patterns. It belong...
متن کاملUnbiased Multivariate Correlation Analysis
Correlation measures are a key element of statistics and machine learning, and essential for a wide range of data analysis tasks. Most existing correlation measures are for pairwise relationships, but real-world data can also exhibit complex multivariate correlations, involving three or more variables. We argue that multivariate correlation measures should be comparable, interpretable, scalable...
متن کاملMultivariate image analysis methods applied to XPS imaging data sets
Recent improvements in imaging photoelectron spectroscopy enhance lateral and vertical characterization of heterogeneous samples at the cost of increasing complexity in the XPS data sets acquired. These imaging data sets require more sophisticated analysis methods than visual inspection if the data are to be interpreted effectively. Multivariate analysis (MVA) methods are increasingly utilized ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2864685