LibGuides: TIM-8515 V1: Lesson 7 Resources

Lesson 7 Resources

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
Hsing, T., & Eubank, R. (2015). Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators. Wiley.
Read Chapter 10 - Section 10.3 (Canonical Correlation Analysis)
This chapter explains the concept of canonical correlations. The area of point estimation of the canonical correlations and canonical scores is explored from a theoretical and mathematical perspective.

Insect Study
insect_study.csv
This hypothetical dataset represents different species of insects and environmental variables (sites with different characteristics such as altitude, humidity level, and distance to a lake).

Lesson 7 Code Samples
Lesson7-CanonicalPalmerPenguins.ipynb
Horst AM, Hill AP, Gorman KB (2020). palmerpenguins: Palmer Archipelago (Antarctica) penguin data. R package version 0.1.0, https://allisonhorst.github.io/palmerpenguins/

Finding the Needle in High-Dimensional Haystack: A tutorial on Canonical Correlation Analysis
Wang, H., Smallwood, J., Mourao-Miranda, J., Xia, C. H., Satterwaite, T. D., Bassett, D. S., & Bzdok, D. (n.d.)
This paper explains the process of using canonical correlation analysis to quantify the variance for sets of variables.
Data Analytics Using Canonical Correlation Analysis and Monte Carlo Simulation
Rickman, J. M., Wang, Y., Rollett, A. D., Harmer, M. P., & Compson, C. (2017). NPJ Computational Materials, (3) 26.
This article describes a Monte Carlo methodology used in the context of canonical correlation analysis (CCA) to identify non-linear functions of the variables that lead to strong input/output correlations.