Transparent and Efficient Financial Analysis
-
Updated
Dec 24, 2024 - Python
Transparent and Efficient Financial Analysis
👑 Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA
GPU-accelerated Factors analysis library and Backtester
an R package for structural equation modeling and more
An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.
多因子指数增强策略/多因子全流程实现
A Python module to perform exploratory & confirmatory factor analyses.
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, F…
psychometrics package, including MIRT(multidimension item response theory), IRT(item response theory),GRM(grade response theory),CAT(computerized adaptive testing), CDM(cognitive diagnostic model), FA(factor analysis), SEM(Structural Equation Modeling) .
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
A Java library for classical test theory, item response theory, factor analysis, and other measurement techniques. It provide tools commonly used in psychometrics and operational testing programs.
An R package for Bayesian structural equation modeling
Application and data for analyzing and structuring portfolios for climate investing.
Fast, linear version of CorEx for covariance estimation, dimensionality reduction, and subspace clustering with very under-sampled, high-dimensional data
Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales
Object-oriented diagram plots with ggplot2
Scalable Ultra-Sparse Bayesian PCA
Descriptive probabilistic marker gene approach to single-cell pseudotime inference
From the given database Find out the personality using this personality traits. Applications in psychology Factor analysis has been used in the study of human intelligence and human personality as a method for comparing the outcomes of (hopefully) objective tests and to construct matrices to define correlations between these outcomes, as well as…
Add a description, image, and links to the factor-analysis topic page so that developers can more easily learn about it.
To associate your repository with the factor-analysis topic, visit your repo's landing page and select "manage topics."