### Install tsEMOS from GitHub

Source: https://github.com/jobstdavid/tsemos/blob/main/README.md

Installs the development version of the tsEMOS package from GitHub. Ensure the 'remotes' package is installed first.

```r
# install.packages("remotes")
remotes::install_github("jobstdavid/tsEMOS")
```

--------------------------------

### Load R-package and data for tsEMOS

Source: https://github.com/jobstdavid/tsemos/blob/main/README.md

Loads the tsEMOS package and prepares sample station data. Splits the data into training and testing sets based on a date threshold.

```r
# load package
library(tsEMOS)
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo

# load data for station Hannover
data(station)

# select data for lead time 24 hours
data <- station[station$lt == 24, ]

# split data in training and test data
train <- data[data$date <= as.Date("2019-12-31"), ]
test <- data[data$date > as.Date("2019-12-31"), ]
```

--------------------------------

### Fit DAR-GARCH-SEMOS (additive) model

Source: https://github.com/jobstdavid/tsemos/blob/main/README.md

Fits an additive deseasonalized autoregressive smooth EMOS with GARCH (DAR-GARCH-SEMOS (+)) model. Requires training and testing data, and column indices for day of year, observations, mean, and standard deviation.

```r
fit <- dargarchadd_semos(train = train,
                         test = test,
                         doy_col = 3,
                         obs_col = 9,
                         mean_col = 10,
                         sd_col = 11,
                         n_ahead = 0)
```

--------------------------------

### Fit DAR-GARCH-SEMOS (multiplicative) model

Source: https://github.com/jobstdavid/tsemos/blob/main/README.md

Fits a multiplicative deseasonalized autoregressive smooth EMOS with GARCH (DAR-GARCH-SEMOS ($\cdot$)) model. Uses specified training and testing data and column mappings.

```r
fit <- dargarchmult_semos(train = train,
                          test = test,
                          doy_col = 3,
                          obs_col = 9,
                          mean_col = 10,
                          sd_col = 11,
                          n_ahead = 0)
```

--------------------------------

### Fit SEMOS model

Source: https://github.com/jobstdavid/tsemos/blob/main/README.md

Fits a smooth EMOS (SEMOS) model using provided training and testing data. Specifies column indices for day of year, observations, mean, and standard deviation.

```r
fit <- semos(train = train,
             test = test,
             doy_col = 3,
             obs_col = 9,
             mean_col = 10,
             sd_col = 11,
             n_ahead = 0)
```

--------------------------------

### Fit SAR-SEMOS model

Source: https://github.com/jobstdavid/tsemos/blob/main/README.md

Fits a standardized autoregressive smooth EMOS (SAR-SEMOS) model using the provided training and testing datasets. Column indices for key variables must be specified.

```r
fit <- sar_semos(train = train,
                 test = test,
                 doy_col = 3,
                 obs_col = 9,
                 mean_col = 10,
                 sd_col = 11,
                 n_ahead = 0)
```

--------------------------------

### Fit DAR-SEMOS model

Source: https://github.com/jobstdavid/tsemos/blob/main/README.md

Fits a deseasonalized autoregressive smooth EMOS (DAR-SEMOS) model. Requires training and testing data, along with column indices for relevant variables.

```r
fit <- dar_semos(train = train,
                 test = test,
                 doy_col = 3,
                 obs_col = 9,
                 mean_col = 10,
                 sd_col = 11,
                 n_ahead = 0)
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.