• linux-ppc64le v1.1.4.2
• noarch v1.1.1

conda install

To install this package run one of the following:
conda install rocketce::orbit-ml
conda install rocketce/label/rocketce-1.10.0::orbit-ml
conda install rocketce/label/rocketce-1.11.2::orbit-ml
conda install rocketce/label/rocketce-1.8.0::orbit-ml
conda install rocketce/label/rocketce-1.9.1::orbit-ml

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Orbit is a Python package for Bayesian time series forecasting and inference. It provides a familiar and intuitive initialize-fit-predict interface for time series tasks, while utilizing probabilistic programming languages under the hood.

For details, check out our documentation and tutorials: - HTML (stable): https://orbit-ml.readthedocs.io/en/stable/ - HTML (latest): https://orbit-ml.readthedocs.io/en/latest/

Currently, it supports concrete implementations for the following models:

• Exponential Smoothing (ETS)
• Local Global Trend (LGT)
• Damped Local Trend (DLT)
• Kernel Time-based Regression (KTR)

It also supports the following sampling/optimization methods for model estimation/inferences:

• Markov-Chain Monte Carlo (MCMC) as a full sampling method
• Maximum a Posteriori (MAP) as a point estimate method
• Variational Inference (VI) as a hybrid-sampling method on approximate distribution

PyPI: https://pypi.org/project/orbit-ml/