High-dimensional data

被引：4

作者：

Amaratunga, Dhammika ^{[1
]}

Cabrera, Javier ^{[2
]}

机构：

[1] Johnson & Johnson Pharmaceut Res & Dev, Raritan, NJ USA

[2] Rutgers State Univ, Sch Arts & Sci, Dept Stat & Biostat, Piscataway, NJ 08855 USA

来源：

JOURNAL OF THE NATIONAL SCIENCE FOUNDATION OF SRI LANKA | 2016年 / 44卷 / 01期

关键词：

Big Data; biplot; conditional t; false discovery rate; lasso; visualisation; FALSE DISCOVERY RATE; REGRESSION; BOOTSTRAP; ERROR;

D O I：

10.4038/jnsfsr.v44i1.7976

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This paper provides a brief introduction to high dimensional data, a form of 'Big Data', and gives an overview of several data analysis concepts and techniques that could be used to explore and analyse such data. An example that involves genomics data from several Sri Lankan and United Kingdom oral cancer patients is used to illustrate the methods.

引用

页码：3 / 9

页数：7

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