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bayesmodels

A parsnip backend for Bayesian models in the tidymodels framework.

Tutorials

Installation

CRAN version

install.packages("bayesmodels")

Development version:

# install.packages("devtools")
devtools::install_github("AlbertoAlmuinha/bayesmodels")

Why Bayesmodels?

Bayesmodels unlocks multiple bayesian models in one framework.In addition, it allows you to integrate these models with the Modeltime and the Tidymodels ecosystems.

In a single framework you will be able to find:

  • Sarima: bayesmodels connects to the bayesforecast package.

  • Garch: bayesmodels connects to the bayesforecast package.

  • Random Walk (Naive): bayesmodels connects to the bayesforecast package.

  • State Space Model: bayesmodels connects to the bayesforecast and bsts packages.

  • Stochastic Volatility Model: bayesmodels connects to the bayesforecast package.

  • Generalized Additive Models (GAMS): bayesmodels connects to the brms package.

  • Adaptive Splines Surface: bayesmodels connects to the BASS package.

  • Exponential Smoothing: bayesmodels connects to the Rglt package.

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Version

Install

install.packages('bayesmodels')

Monthly Downloads

13

Version

0.1.1

License

MIT + file LICENSE

Issues

6

Pull Requests

0

Stars

55

Forks

10

Maintainer

Alberto Almuic3<b1>a

Last Published

June 28th, 2021

Functions in bayesmodels (0.1.1)

adaptive_spline_stan_predict_impl

Bridge prediction function for ARIMA models
Sarima_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
bayesian_structural_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
adaptive_splines_params

Tuning Parameters for Adaptive Splines Surface Models
adaptive_spline

General Interface for Adaptive Spline Surface Models
additive_state_space

General Interface for Additive Linear State Space Regression Models
Sarima_stan_predict_impl

Bridge prediction function for ARIMA models
adaptive_spline_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
bayesian_structural_reg

General Interface for Bayesian Structural Time Series Models
bayesian_structural_stan_predict_impl

Bridge prediction function for ARIMA models
exp_smoothing_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
exponential_smoothing

General Interface for Exponential Smoothing Models
garch_params

Tuning Parameters for GARCHA Models
ssm_params

Tuning Parameters for Additive Linear State Space Regression Models
ssm_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
tidyeval

Tidy eval helpers
garch_reg

General Interface for GARCH Regression Models
naive_params

Tuning Parameters for Random Walk Models
exp_smoothing_stan_predict_impl

Bridge prediction function for ARIMA models
svm_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
gen_additive_stan_predict_impl

Bridge prediction function for ARIMA models
exponential_smoothing_params

Tuning Parameters for Exponential Smoothing Models
random_walk_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
random_walk_stan_predict_impl

Bridge prediction function for ARIMA models
garch_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
ssm_stan_predict_impl

Bridge prediction function for ARIMA models
garch_stan_predict_impl

Bridge prediction function for ARIMA models
svm_stan_predict_impl

Bridge prediction function for ARIMA models
gen_additive_stan_fit_impl

Low-Level ARIMA function for translating modeltime to forecast
gen_additive_reg

Interface for Generalized Additive Models (GAM)
svm_reg

General Interface for Stochastic Volatility Regression Models
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Pipe operator
random_walk_reg

General Interface for Naive and Random Walk models Regression Models
sarima_reg

General Interface for ARIMA Regression Models
sarima_params

Tuning Parameters for SARIMA Models