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Principal Components Analysis

2008
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns in multivariate data. It aims to graphically display the relative positions of data points in fewer dimensions while retaining as much information as possible, and explore relationships between dependent variables. It is a hypothesis-generating technique
openaire   +2 more sources

The Affordable Care Act and access to care across the cancer control continuum: A review at 10 years

Ca-A Cancer Journal for Clinicians, 2020
Jingxuan Zhao   +2 more
exaly  

Principal Components Analysis

1989
Introduction Basic Concepts of Principal Components Geometrical Properties of Principal Components Decomposition Properties of Principal Components Principal Components of Patterned Correlation Matrices Rotation of Principal Components Using Principal Components to Select a Subset of Variables Principal Components Versus Factor Analysis Uses of ...
openaire   +1 more source

Analysis of heavy metal sources in soil using kriging interpolation on principal components.

Environmental Science and Technology, 2014
Hoehun Ha   +3 more
semanticscholar   +1 more source

Practical clinical interventions for diet, physical activity, and weight control in cancer survivors

Ca-A Cancer Journal for Clinicians, 2015
Wendy Demark-Wahnefried   +2 more
exaly  

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