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---
title: "Plotting GAMs"
author: "Stefano Coretta"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Vignette Title}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
out.width = "300px", fig.align = "center", dpi = 300
)
library(tidyverse)
theme_set(theme_bw())
library(itsadug)
library(tidymv)
```

To illustrate how to use `plot_smooths()`, let's first prepare some dummy data with a factor variable and run `gam()` on this data. The `gam` model includes a reference smooth `s(x2)`, a by-factor difference smooth `s(x2, by = fac)`, and a smooth `s(x0)`.

```{r gam}
set.seed(10)
data <- gamSim(4)
model <- gam(
y ~
fac +
s(x2) +
s(x2, by = fac) +
s(x0),
data = data
)
```

We can now plot the estimated smooths for the two levels of `fac`.
The function supports factors with more than 2 levels.

```{r plot-1-2}
plot_smooths(
model = model,
time_series = x2,
comparison = fac
) +
theme(legend.position = "top")
```