Bayesian Factor Analysis using Gibbs sampling

Simple-Supervised Factor Analysis

In this repository through advanced data analytics and market research assessed financial viability, customer behaviors, and market trends to form a strategic game acquisition recommendation. Process included market share simulation, cluster and factor analysis, GaborGranger pricing strategy, and customer segmentation.

Segmentation of Credit Card Customers

Case Study- Segmentation

Factor analytics techniques employed in R, including EFA and CFA, to analyze Martin & Doris's (2003) research on the development of a psychometric instrument measuring individual styles of humor.

Variance Identification for Sparse Factor Analyses

This is a project I developed during my MSc. in UC3M. It is an R project that engages with commands on data visualisation, PCA, clustering and regression.

Exploring Gene Expression Features through Factor and Cluster Analysis in Breast Cancer Patients.

Kmeans, EM and Neural Networks applied on reduced dataset using different dimensionality reduction algorithms.

This is analysis done to study the canine species based on the Skull measurements obtained for the different species of the canines. All kinds of multivariate analyses are done on this species.

The model tries to predict the number of sales calls that a maintenance company might be receiving based on climatic and weather conditions. The age of the car and the duration of connection with the company are also to be considered. The model tries to explore the important factors which are significant and help in getting a high accuracy of pr…

Repo for analisis faktor

Segmentation of the clients of an insurance company based on the survey data received from the clients. The data contains variables such as trust, experience, hospitality, service and other such customer based information. The model uses factor analysis to find the most significant factors and then used them for the Hierarchical and K-means clus…

Apply traditional statistical methods such as PCA and FA to characterize political opinions within survey research data

In this project I utilized K-fold cross validation with Linear Discriminant Analysis and Logistic Regression to generate a prediction model that can predict whether a Swiss Bank Note was genuine or counterfeit. I also performed factor analysis to see if lowering dimensionality would produce a better prediction model.

Spearman's 1904 work on 'General Intelligence' launched the field of factor analysis into existence. This slide-deck discusses the details and aftermath.

📊 Contains code used to analyze data about HCL-32 instrument (Hypomania Checklist). Functions related to confirmatory factor analysis and internal consistency.

Factor analysis of multi-neuron spike trains in R

Factor Analysis of BDSM