Bayesian Factor Analysis using Gibbs sampling
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Updated
Dec 21, 2018 - C++
Bayesian Factor Analysis using Gibbs sampling
Simple-Supervised Factor Analysis
Factor Analysis for survey data
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.
A lavaan-like syntax for structural equation models with OpenMx
Kmeans, EM and Neural Networks applied on reduced dataset using different dimensionality reduction algorithms.
An R package providing multiple Imputation of covariance matrices in order to perform factor analysis.
ML algorithms implemented in Python
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…
Implementation of Factor-augmented Vector Autoregressive process (FAVAR(p)).
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.
Mini project on Dimensionality Reduction
Factor analysis of multi-neuron spike trains in R
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