README.Rmd

---
output: github_document
---

```{r, echo = FALSE}
version <- as.vector(read.dcf('DESCRIPTION')[, 'Version'])
version <- gsub('-', '.', version)
```

[![R-CMD-check](https://github.com/tsmodels/tsgam/workflows/R-CMD-check/badge.svg)](https://github.com/tsmodels/tsgam/actions)
[![Last-changedate](https://img.shields.io/badge/last%20change-`r gsub('-', '--', Sys.Date())`-yellowgreen.svg)](/commits/master)
[![packageversion](https://img.shields.io/badge/Package%20version-`r version`-orange.svg?style=flat-square)](commits/master)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/tsgam)](https://cran.r-project.org/package=tsgam)


```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

# tsgam
Wrapper for the Generalized Additive Model in package mgcv to conform with tsmodels
output and framework.  It is a more abstract/general layer than other models in
tsmodels due to the nature of GAMs.

## Installation

The package can be installed from the tsmodels github repo. 

```{r,eval=FALSE}
remotes::install_github("tsmodels/tsgam", dependencies = TRUE)
```

A short vignette is available [here](https://www.nopredict.com/packages/tsgam.html).

## Updates

* ver 0.3.0: added a multi-GAM model (mgam) with optional pooling argument and
custom predict function to include copula based dependency in the
predictive distribution. The input for this type of model is a data.table with
series and index identifiers.