Creating different forecast paths for forecast objects (when applicable), by utilizing the underline model distribution with the simulate function

forecast_sim(model, h, n, sim_color = "blue", opacity = 0.05,
plot = TRUE)

## Arguments

model A forecasting model supporting Arima, auto.arima, ets, and nnetar models from the **forecast** package An integer, defines the forecast horizon An integer, set the number of iterations of the simulation Set the color of the simulation paths lines Set the opacity level of the simulation path lines Logical, if TRUE will desplay the output plot

## Value

The baseline series, the simulated values and a plot

## Examples

 # NOT RUN {
library(forecast)
data(USgas)

# Create a model
fit <- auto.arima(USgas)

# Simulate 100 possible forecast path, with horizon of 60 months
forecast_sim(model = fit, h = 60, n = 100)
# }