Multivariate Data AnalysisExplorations – The Journal of Undergraduate Research, Scholarship and Creativity at Wright State
AbstractThe study of biology, computer science, and information technology all combine to form the science of bioinformatics . This field was created to make discoveries on new biological insights . Bioinformatics has several important task one of them being able to analyze and interpret different types of data and this includes multivariate data analysis. Multivariate data analysis can use linear projection methods such as linear discriminant analysis (LDA), principal component analysis (PCA), and projection to latent structures (PLS). I have created a Java program that can manipulate multivariate data by manual rotation and will be comparing my results to the results of PCA generated by MATLAB. I will be analyzing them to see which of the two can create the best rotations and by best rotations, it is only better if the separation of the variables is better. The results of my study is the manual rotation tool does provide better rotations than PCA.
Citation InformationDiana Copeland and Michael Raymer. "Multivariate Data Analysis"
Available at: http://works.bepress.com/michael_raymer/61/