Predict Observations for Future Time Steps

This function is used to predict future observations based on a tsd_onset object. It uses the time_interval attribute from the tsd_onset object to make predictions.

Usage

# S3 method for class 'tsd_onset'
predict(object, n_step = 3, ...)

Arguments

object

A tsd_onset object created using the seasonal_onset() function.

n_step

An integer specifying the number of future time steps for which you want to predict observations.

...

Additional arguments (not used).

Value

A tibble-like object called tsd_predict containing the predicted observations, including reference time, lower confidence interval, and upper confidence interval for the specified number of future time steps.

Examples

# Generate predictions of time series data
set.seed(123)
time_series <- generate_seasonal_data(
  years = 1,
  time_interval = "day"
)
# Apply `seasonal_onset` analysis
time_series_with_onset <- seasonal_onset(
  tsd = time_series,
  k = 7
)
# Predict observations for the next 7 time steps
predict(object = time_series_with_onset, n_step = 7)
#> # A tibble: 8 × 5
#>       t reference_time estimate lower upper
#>   <int> <date>            <dbl> <dbl> <dbl>
#> 1     0 2022-05-25         100  100    100 
#> 2     1 2022-05-26         102.  98.0  106.
#> 3     2 2022-05-27         104.  96.1  112.
#> 4     3 2022-05-28         106.  94.2  118.
#> 5     4 2022-05-29         107.  92.3  125.
#> 6     5 2022-05-30         109.  90.5  132.
#> 7     6 2022-05-31         111.  88.7  140.
#> 8     7 2022-06-01         113.  87.0  148.