variation coefficient

Intel® Summary Statistics Library: what is new in the Update?

Intel® Summary Statistics Library 1.0 Update is available for downloading. It includes several features and benefits:

Algorithm for parameterization of correlation matrix. The algorithm transforms the input which lacks property of positive semidefiniteness into the output meeting properties of correlation matrix. The algorithm is based on spectral decomposition method and can be used in financial computations.

Intel® Summary Statistics Library: why not to use multi-core advantages?

In my previous posts I described some features and usage model of Intel® Statistics Library. However, there are many available statistical packages that provide good similar functionality. Does Intel® Summary Statistics Library deliver difference, bring something new and specific? The answer is yes. 

Intel® Summary Statistics Library: how to process data in chunks?

In my previous post I considered computation of statistical estimates for in-memory datasets using tools available in Intel® Summary Statistics Library. New days bring new problems, and today I need to compute the same estimates for data which can not fit into memory of a computer.

Intel® Summary Statistics Library: Several Estimates at One Stroke

Today it was necessary for me to compute statistical estimates for a dataset. The observations are weighted, and only several components of the random vector had to be analyzed. How often do we solve such tasks and how do we solve them in our every day life? If we meet such problems rarely or their size is small then use of a popular statistical package or development of a data processing program will be a proper way to address the problem. What if I need to process huge data arrays regularly analyzing gene expression levels for example?

Intel® Summary Statistics Library: How to Manage With Oceans of Information?

Welcome to Intel® Summary Statistics Library, solution for parallel statistical processing of multi-dimensional datasets. It contains functions for initial statistical analysis of raw data which allow investigating structure of datasets and get their basic characteristics, estimates, and internal dependencies.


The library provides rich set of tools intended to compute various statistical estimates for datasets:

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