bayesian
modeltime.ensemble
| bayesian | modeltime.ensemble | |
|---|---|---|
| 1 | 1 | |
| 42 | 71 | |
| - | - | |
| 7.7 | 7.6 | |
| 8 days ago | 4 months ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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bayesian
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How do you train a Bayesian model
There's MLMod and Bayesian which are TidyModels wrappers for stan_glm and brms (brms is my go to) but I haven't seen anything that indicates how to tune them.
modeltime.ensemble
What are some alternatives?
multilevelmod - Parsnip wrappers for mixed-level and hierarchical models
fable - Tidy time series forecasting
brms - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
modeltime.resample - Resampling Tools for Time Series Forecasting with Modeltime
boostime - The Tidymodels Extension for Time Series Boosting Models
forecast - Forecasting Functions for Time Series and Linear Models
timetk - Time series analysis in the `tidyverse`
modeltime - Modeltime unlocks time series forecast models and machine learning in one framework
Econometrics-on-Stock-Data - R finance guide - Algotrading101
modeltime.h2o - Forecasting with H2O AutoML. Use the H2O Automatic Machine Learning algorithm as a backend for Modeltime Time Series Forecasting.