https://github.com/earthinversion/exploratory-factor-analysis
Factor Analysis method used to search influential underlying factors or latent variables from a set of observed variables
https://github.com/earthinversion/exploratory-factor-analysis
exploratory-data-analysis factor-analysis
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Factor Analysis method used to search influential underlying factors or latent variables from a set of observed variables
- Host: GitHub
- URL: https://github.com/earthinversion/exploratory-factor-analysis
- Owner: earthinversion
- Created: 2019-08-18T12:49:08.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-08-18T13:02:03.000Z (almost 7 years ago)
- Last Synced: 2025-01-18T15:57:14.579Z (over 1 year ago)
- Topics: exploratory-data-analysis, factor-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 110 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Exploratory-Factor-Analysis
Data with large number of measured variables have the possibility of having some variables to “overlap” due to its inherent dependency. Factor Analysis (FA) is an exploratory data analysis method used to search influential underlying factors or latent variables from a set of observed variables. It is a method for investigating whether a number of variables of interest Y1, Y2,……., Yl, are linearly related to a smaller number of unobservable factors F1, F2,..……, Fk.
## The Factor Analysis Model
Factor analysis can statistically explain the variance among the observed variable and condense a set of the observed variable into the unobserved variable called factors. Observed variables are modeled as a linear combination of factors and error terms. Each factor explains a particular amount of variance in the observed variables and can help in data interpretations by reducing the number of variables.
## Installation
To install all the necessary packages:
`conda env create -f environment.yml`
## Data
can download more data from this
github link https://vincentarelbundock.github.io/Rdatasets/datasets.html
## References
1. https://www.cs.princeton.edu/~bee/courses/scribe/lec_10_02_2013.pdf
2. https://www.datacamp.com/community/tutorials/introduction-factor-analysis
3. http://www.yorku.ca/ptryfos/f1400.pdf
4. https://www.mathworks.com/help/stats/examples/factor-analysis.html
5. Rygel, L., O’sullivan, D., Yarnal, B., 2006. A Method for Constructing a Social Vulnerability Index: An Application to Hurricane Storm Surges in a Developed Country. Mitig Adapt Strat Glob Change 11, 741–764. doi:10.1007/s11027-006-0265-6
6. Brooks, N., Neil Adger, W., Mick Kelly, P., 2005. The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Global Environmental Change 15, 151–163. doi:10.1016/j.gloenvcha.2004.12.006