---
title: "Simple Case Studies"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Simple Case Studies}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(fastTS)
library(magrittr) # for pipe
```


# Lake Huron data set

```{r lakehuron}
data("LakeHuron")

fit_LH <- fastTS(LakeHuron)

fit_LH
coef(fit_LH)
```

# EuStockMarkets

If you have a univariate time series with suspected trend, such as the EuStockMarkets data set,

```{r stocks}
data("EuStockMarkets")
X <- as.numeric(time(EuStockMarkets))
X_sp <- splines::bs(X-min(X), df = 9)

fit_stock <- fastTS(log(EuStockMarkets[,1]), n_lags_max = 400, X = X_sp, w_exo = "unpenalized")
fit_stock
tail(coef(fit_stock), 11)

# insert plot? 
```

# Seasonal examples

## Nottem 

```{r nottem}
data("nottem")
fit_nt <- fastTS(nottem, n_lags_max = 24)
fit_nt
coef(fit_nt)

```

## UKDriverDeaths

```{r UKDriverDeaths}
data("UKDriverDeaths")
fit_ukdd <- fastTS(UKDriverDeaths, n_lags_max = 24)
fit_ukdd
coef(fit_ukdd)

```

## sunspot

```{r sunspot}

data("sunspot.month")
fit_ssm <- fastTS(sunspot.month)
fit_ssm
```

Model summaries

```{r sunspot2}
summary(fit_ssm)
```