> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fincept.in/llms.txt
> Use this file to discover all available pages before exploring further.

# Multiple seasonality

> Models for series with several seasonal cycles (daily data with weekly and yearly patterns, hourly data with daily and weekly ones): TBATS, MSTL decomposition with a trend model, and gradient-boosted decomposition; components, harmonics, Box-Cox and forecasts with intervals.

Toolset `tsforecast_seasonal`: 3 tools.

| Tool | What it does | Notes |
| - | - | - |
| `tsforecast_tbats` | Fits TBATS (trigonometric seasonality, Box-Cox, ARMA errors, trend and seasonal components) to one series (y) or every series of a panel (data), for one or several seasonal periods that may be long (e.g. \[7, 365] for daily data). | |
| `tsforecast_mfles` | Fits the gradient-boosted decomposition model to one series (y) or every series of a panel (data): rounds of median, Fourier seasonality (several periods), piecewise-linear trend with changepoints, exogenous regression and smoothing, each shrunk by its learning rate; auto\_mfles picks the settings by a backtest search. | |
| `tsforecast_mstl` | Multiple seasonal-trend decomposition by LOESS (MSTL) of one series (y) or every series of a panel (data) for one or several periods (e.g. \[7, 365] for daily data, \[24, 168] for hourly), forecasting each seasonal component by seasonal naive and the trend plus remainder with a chosen non-seasonal model (automatic ETS by default, or ARIMA, Theta, CES, ...). | |

Inputs, limits and outputs are described in [Fincept TS Forecast](/guides/fincept-ts-forecast). Full schemas: `fincept_describe_tool`.


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