{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
-
Updated
May 14, 2024 - R
{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
Ecological forecasting using Dynamic Generalized Additive Models with R 📦's {mvgam} and {brms}
Toolbox to estimate Generalized Additive Mixed Models and their Markov-switching extensions in Python
Tutorials for the mssm toolbox!
A function that takes as input a cropped text line image, and outputs the dewarped image.
ggplot-based graphics and useful functions for GAMs fitted using the mgcv package
Bindings for Additive TidyModels
R package for calculating survey indices by age from DATRAS exchange data. Adapted from Casper W. Berg @casperwberg.
To help identify ecosystem and climate influences on Atlantic cod, generalized additive models were used to examine associations between Atlantic cod population dynamics and environmental variables in the Northwest Atlantic region.
An R package for estimating generalized additive mixed models with latent variables
To analyse COVID data-set in Peru which provides by government.
The dataset used for the "A non-contact SpO2 estimation using video magnification and infrared data" publication
This is a paleolimnological analysis using tidypaleo in R. View the Github page to walk through each step of the analysis.
Smooth Hazard Ratio Curves Taking a Reference Value
Analyze and forecast time series data on the number of visitors to various Italian museums using techniques such as TimeGPT, SARIMAX, Holt-Winters, Lasso, Gradient Boosting, GAM, etc.
The dataset used for the "Non-Contact Blood Pressure Estimation using infrared motion magnified facial video" publication. The code developed is to fit the data to the reference Blood Pressure values.
Houses a series of projects I worked on for a course in Data Mining that I took in my Ph.D. Data Science program at UTEP in the Fall of 2022. Covers areas such as Regularized Logistic Regression, Optimization, Kernel Methods, PageRank, Kernel PCA, Association Rule Mining, Anomaly Detection, Parametric/Nonparametric Nonlinear Regression, etc.
A document introducing generalized additive models.📈
This repository contains the code required to perform the data processing and analysis associated with the manuscript submitted to Nature under the name "Maladaptive Genetic Assortment in Humans
Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer
Add a description, image, and links to the generalized-additive-models topic page so that developers can more easily learn about it.
To associate your repository with the generalized-additive-models topic, visit your repo's landing page and select "manage topics."