Documentation Index
Fetch the complete documentation index at: https://nixtlaverse.nixtla.io/llms.txt
Use this file to discover all available pages before exploring further.
Automatic Forecasting
Automatic forecasting tools search for the best parameters and select
the best possible model for a series of time series. These tools are
useful for large collections of univariate time series.
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
AutoARIMA | ✅ | ✅ | ✅ | ✅ |
AutoETS | ✅ | ✅ | ✅ | ✅ |
AutoCES | ✅ | ✅ | ✅ | ✅ |
AutoTheta | ✅ | ✅ | ✅ | ✅ |
ARIMA Family
These models exploit the existing autocorrelations in the time series.
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
ARIMA | ✅ | ✅ | ✅ | ✅ |
AutoRegressive | ✅ | ✅ | ✅ | ✅ |
Theta Family
Fit two theta lines to a deseasonalized time series, using different
techniques to obtain and combine the two theta lines to produce the
final forecasts.
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
Theta | ✅ | ✅ | ✅ | ✅ |
OptimizedTheta | ✅ | ✅ | ✅ | ✅ |
DynamicTheta | ✅ | ✅ | ✅ | ✅ |
DynamicOptimizedTheta | ✅ | ✅ | ✅ | ✅ |
Multiple Seasonalities
Suited for signals with more than one clear seasonality. Useful for
low-frequency data like electricity and logs.
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
MSTL | ✅ | ✅ | ✅ | ✅ |
GARCH and ARCH Models
Suited for modeling time series that exhibit non-constant volatility
over time. The ARCH model is a particular case of GARCH.
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
GARCH | ✅ | ✅ | ✅ | ✅ |
ARCH | ✅ | ✅ | ✅ | ✅ |
Baseline Models
Classical models for establishing baseline.
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
HistoricAverage | ✅ | ✅ | ✅ | ✅ |
Naive | ✅ | ✅ | ✅ | ✅ |
RandomWalkWithDrift | ✅ | ✅ | ✅ | ✅ |
SeasonalNaive | ✅ | ✅ | ✅ | ✅ |
WindowAverage | ✅ | | | |
SeasonalWindowAverage | ✅ | | | |
Exponential Smoothing
Uses a weighted average of all past observations where the weights
decrease exponentially into the past. Suitable for data with clear trend
and/or seasonality. Use the SimpleExponential family for data with no
clear trend or seasonality.
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
SimpleExponentialSmoothing | ✅ | | | |
SimpleExponentialSmoothingOptimized | ✅ | | | |
Holt | ✅ | ✅ | ✅ | ✅ |
HoltWinters | ✅ | ✅ | ✅ | ✅ |
Sparse or Intermittent
Suited for series with very few non-zero observations
| Model | Point Forecast | Probabilistic Forecast | Insample fitted values | Probabilistic fitted values |
|---|
ADIDA | ✅ | | | |
CrostonClassic | ✅ | | | |
CrostonOptimized | ✅ | | | |
CrostonSBA | ✅ | | | |
IMAPA | ✅ | | | |
TSB | ✅ | | | |
