factor-analysis

There are 187 repositories under factor-analysis topic.

  • FinanceToolkit

    JerBouma/FinanceToolkit

    Transparent and Efficient Financial Analysis

    Language:Python3k6787359
  • prince

    MaxHalford/prince

    :crown: Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

    Language:Python1.3k25133184

  • Heerozh/spectre

    GPU-accelerated Factors analysis library and Backtester

    Language:Python6472024108

  • yrosseel/lavaan

    an R package for structural equation modeling and more

    Language:R4384424899

  • jerryxyx/AlphaTrading

    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.

    Language:Jupyter Notebook345131140
  • MOFA2

    bioFAM/MOFA2

    Multi-Omics Factor Analysis

    Language:R3081413752

  • phonegapX/alphasickle

    多因子指数增强策略/多因子全流程实现

    Language:Python26952119

  • EducationalTestingService/factor_analyzer

    A Python module to perform exploratory & confirmatory factor analyses.

    Language:Python235197368
  • machine-learning

    je-suis-tm/machine-learning

    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, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

    Language:Jupyter Notebook2295151

  • inuyasha2012/pypsy

    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) .

    Language:Python21419871
  • Miscellaneous-R-Code

    m-clark/Miscellaneous-R-Code

    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**.

    Language:R19322282

  • meyerjp3/psychometrics

    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.

    Language:Java95161046

  • ecmerkle/blavaan

    An R package for Bayesian structural equation modeling

    Language:R8796123

  • opentaps/open-climate-investing

    Application and data for analyzing and structuring portfolios for climate investing.

    Language:JavaScript4753015

  • gregversteeg/LinearCorex

    Fast, linear version of CorEx for covariance estimation, dimensionality reduction, and subspace clustering with very under-sampled, high-dimensional data

    Language:Python4225213

  • ashish-kamboj/Market-Mix-Modeling

    Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales

    Language:R404128

  • mancusolab/susiepca

    Scalable Ultra-Sparse Bayesian PCA

    Language:Python291145

  • kieranrcampbell/ouija

    Descriptive probabilistic marker gene approach to single-cell pseudotime inference

    Language:R286123

  • wjschne/ggdiagram

    Object-oriented diagram plots with ggplot2

    Language:R25200

  • Sagar-Darji/Personality-prediction

    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 finding the factors for these results. The field of psychology that measures human intelligence using quantitative testing in this way is known as psychometrics (psycho=mental, metrics=measurement). Advantages 1)Offers a much more objective method of testing traits such as intelligence in humans 2)Allows for a satisfactory comparison between the results of intelligence tests 3)Provides support for theories that would be difficult to prove otherwise

    Language:Jupyter Notebook21105

  • bmcmenamin/fa_kit

    Factor Analysis Kit

    Language:Python19325

  • xinhe-lab/GSFA

    R package that performs sparse factor analysis and differential gene expression discovery simultaneously on single-cell CRISPR screening data.

    Language:C++19362

  • JBris/multivariate_analysis_examples

    Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.

    Language:Python18203

  • cjurban/deepirtools

    Deep learning-based estimation and inference for item response theory models.

    Language:Python17203

  • phonegapX/sustecher

    Alpha研究平台

    Language:Python172012

  • YasPHP/The-Five-Factor-Personality-Test

    Unsupervised learning coupled with applied factor analysis to the five-factor model (FFM), a taxonomy for personality traits used to describe the human personality and psyche, via descriptors of common language and not on neuropsychological experiments. Used kmeans clustering and feature scaling (min-max normalization).

    Language:Jupyter Notebook15125

  • bghojogh/Generative-LLE

    The code for Generative Locally Linear Embedding (GLLE).

    Language:Python14101

  • cuiruifei/CopulaFactorModel

    Inference for Gaussian copula factor models and its application to causal discovery.

    Language:R14218

  • neil-gallagher/CSFA

    Codebase for Cross-Spectral Factor Analysis (Gallagher et al., 2017)

    Language:MATLAB12826

  • CFWP/FMradio

    Factor Modeling for radiomics

    Language:R11304

  • ZechangSun/QFA

    Quasar Factor Analysis – An Unsupervised and Probabilistic Quasar Continuum Prediction Algorithm with Latent Factor Analysis

    Language:Jupyter Notebook11301

  • luca590/High-Dimensional-Statistics

    PCA, Factor Analysis, CCA, Sparse Covariance Matrix Estimation, Imputation, Multiple Hypothesis Testing

    Language:R10304

  • at-tan/Latent_Factors_in_Stocks

    Dynamic factor modeling to uncover the key latent factors driving the price behavior of some of the largest American large-cap equities. We examine how these factors affect individual stock prices, what they represent, and how they have fluctuated in the sample period. As published in the Data Driven Investor on Medium.com.

    Language:Jupyter Notebook9203

  • TatevKaren/multivariate-statistics

    Case Study in ranking U.S. cities based on a single linear combination of rating variables. Dimensionality techniques used in the analysis are Principal Component Analysis (PCA), Factor Analysis (FA), Canonical Correlation Analysis (CCA)

    Language:R8102

  • xmc2/FAtools

    R package for factor analysis visualization

    Language:R8566

  • p-gw/FactorRotations.jl

    Rotation methods for factor analysis and principal component analysis in Julia

    Language:Julia71392