Skip to main content
# BATS and TBATS time series forecasting

Package provides BATS and TBATS time series forecasting methods described in:

> De Livera, A.M., Hyndman, R.J., & Snyder, R. D. (2011), Forecasting time series with complex seasonal patterns using exponential smoothing, Journal of the American Statistical Association, 106(496), 1513-1527.


## Installation

From pypi:

```bash
pip install tbats
```

Import via:

```python
from tbats import BATS, TBATS
```

## Minimal working example:

```python
from tbats import TBATS
import numpy as np

np.random.seed(2342)
t = np.array(range(0, 160))
y = 5 * np.sin(t * 2 * np.pi / 7) + 2 * np.cos(t * 2 * np.pi / 30.5) + \
((t / 20) ** 1.5 + np.random.normal(size=160) * t / 50) + 10

# Create estimator
estimator = TBATS(seasonal_periods=[14, 30.5])

# Fit model
fitted_model = estimator.fit(y)

# Forecast 14 steps ahead
y_forecasted = fitted_model.forecast(steps=14)

# Summarize fitted model
print(fitted_model.summary())
```

Reading model details

```python
# Time series analysis
print(fitted_model.y_hat) # in sample prediction
print(fitted_model.resid) # in sample residuals
print(fitted_model.aic)

# Reading model parameters
print(fitted_model.params.alpha)
print(fitted_model.params.beta)
print(fitted_model.params.x0)
print(fitted_model.params.components.use_box_cox)
print(fitted_model.params.components.seasonal_harmonics)
```

See **examples** directory for more details

## For Contributors

Building package:

```bash
pip install -e .[dev]
```

Unit and integration tests:

```bash
python setup.py test
```

R forecast package comparison tests. Those DO NOT RUN with default test command, you need R forecast package installed:
```bash
python setup.py test_r
```

## Comparison to R implementation

Python implementation is meant to be as much as possible equivalent to R implementation in forecast package.

- BATS in R https://www.rdocumentation.org/packages/forecast/versions/8.4/topics/bats
- TBATS in R: https://www.rdocumentation.org/packages/forecast/versions/8.4/topics/tbats








Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tbats-1.0.2.tar.gz (29.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tbats-1.0.2-py3-none-any.whl (41.9 kB view details)

Uploaded Python 3

File details

Details for the file tbats-1.0.2.tar.gz.

File metadata

  • Download URL: tbats-1.0.2.tar.gz
  • Upload date:
  • Size: 29.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.6

File hashes

Hashes for tbats-1.0.2.tar.gz
Algorithm Hash digest
SHA256 f638e93ac9d275ea6f261307119a9bb7a557399baa92e7458f75f286bdbebd76
MD5 bc1df5e1c6af1bfb0b9834095fe56a6e
BLAKE2b-256 904ce5bfb1ac294c9fb282c2322beb972fee12ae88f56d56044730eee1d7b715

See more details on using hashes here.

File details

Details for the file tbats-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: tbats-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 41.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.6

File hashes

Hashes for tbats-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 f58aec83c679ed976a29cbaf62c779f8eaca5c8c11d276044c7798c94e0becff
MD5 397e6c7df8c097af95fbe7a9bb2a3ce9
BLAKE2b-256 1988edd993852b27e4cb3dff526d2c18ab367b0807e78be0ebcc76d350ff4403

See more details on using hashes here.

Release history Release notifications | RSS feed

1.1.3

2 files

1.1.2

2 files

1.1.1

2 files

1.1.0

2 files

1.0.10

2 files

1.0.9

2 files

1.0.8

2 files

1.0.7

2 files

1.0.6

2 files

1.0.5

2 files

1.0.4

2 files

1.0.3

2 files

This release

1.0.2 This release

2 files

1.0.1

2 files

1.0.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page