There are 7 repositories under multivariate-analysis topic.
Comparative analysis of pairwise interactions in multivariate time series.
Development repository for the Bioconductor package 'mixOmics '
Deep and Machine Learning for Microscopy
A Python package housing a collection of deep-learning multi-modal data fusion method pipelines! From data loading, to training, to evaluation - fusilli's got you covered 🌸
Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.
Explorative multivariate statistics in Python
Integrate your chemometric tools with the scikit-learn API 🧪 🤖
Comparing Long Term Short Memory (LSTM) & Gated Re-current Unit (GRU) during forecasting of oil price .Exploring multivariate relationships between West Texas Intermediate and S&P 500, Dow Jones Utility Avg, US Dollar Index Futures , US 10 Yr Treasury Bonds , Gold Futures.
energy package for R
Implementation of a Partial Least Squares Regressor
Estimate dynamic high-order correlations in multivariate timeseries data
lit-element components for fast and modular multivariate analysis
metaSEM package
R package for fitting joint models to time-to-event data and multivariate longitudinal data
Software for the analysis and interactive exploration of spectral imaging data
(Multiblock) Partial Least Squares Regression for Python
Arima, Sarima, LSTM, Prophet, DeepAR, Kats, Granger-causality, Autots
MFTE (Multi Feature Tagger of English) Python is the Python version based on Le Foll's MFTE written in Perl. It is extended to include semantic tags from Biber (2006) and Biber et al. (1999), including other specific tags.
A cloud-native data pipeline and visualization project analyzing Formula 1 racing data using Azure, Databricks, Delta Lake, Tableau, and Python for insightful EDA and interactive dashboards.
manage ordinations and render biplots in a tidyverse workflow
Julia and Python programs that implement some of the tools described in my book "Stochastic Methods in Asset Pricing" (SMAP), MIT Press 2017 (e.g., the method for computing the price of American call options and the construction of the early exercise premium in the Black-Scholes-Merton framework from section 18.4 in SMAP).
MoMA: Modern Multivariate Analysis in R
Markov random fields with covariates
This project implements a time series multivariate analysis using RNN/LSTM for stock price predictions. A deep RNN model was created and trained on five years of historical Google stock price data to forecast the stock performance over a two-month period.
Using fuzzy cognitive maps for multivariate data forecasting in Python 3.8.
Parkinson's disease data analysis from uci machine learning repository dataset.
metaUSAT is a data-adaptive statistical approach for testing genetic associations of multiple traits from single/multiple studies using univariate GWAS summary statistics.
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.
The project aims to perform various visualizations and provide various insights from the considered Indian automobile dataset by performing data analysis that utilizing machine learning algorithms in R programming language.