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Aug 17, 2024
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add sim plots #21

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5 changes: 4 additions & 1 deletion README.md
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Expand Up @@ -70,7 +70,10 @@ prediction = exp.(prediction_log)

plot(airp.passengers, w=2 , color = "Black", lab = "Historical", legend = :outerbottom)
plot!(vcat(ones(length(log_air_passengers)).*NaN, prediction), lab = "Forecast", w=2, color = "blue")
```
![quick_example_airp](./docs/assets/quick_example_airp.PNG)

```julia
N_scenarios = 1000
simulation = StateSpaceLearning.simulate(output, steps_ahead, N_scenarios) # arguments are the output of the fitted model, number of steps ahead the user wants to forecast and number of scenario paths

Expand All @@ -81,7 +84,7 @@ end
plot!(vcat(ones(length(log_air_passengers)).*NaN, exp.(simulation[:, N_scenarios])), lab = "Scenarios Paths", α = 0.1 , color = "red")

```
![quick_example_airp](./docs/assets/quick_example_airp.PNG)
![airp_sim](./docs/assets/airp_sim.svg)

### Component Extraction
Quick example on how to perform component extraction in time series utilizing StateSpaceLearning.
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