Metadata-Version: 2.1
Name: PyTimeVar
Version: 0.0.2
Summary: A Python package for Trending Time-Varying Time Series Models
Author: Mingxuan Song
Author-email: 678270ms@eur.nl
Maintainer: Mingxuan Song
Maintainer-email: 678270ms@eur.nl
Requires-Python: >=3.8,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Description-Content-Type: text/markdown

# PyTimeVar

A Python package for Trending Time-Varying Time Series Models

## Purpose of the Package

The PyTimeVar package offers state-of-the-art estimation and statistical inference methods for time series regression models with flexible trends and/or time-
varying coefficients.

## Features

- Nonparametric estimation of time-varying time series models, along with multiple bootstrap-assisted inference methods
- Alternative estimation methods for modelling trend and time-varying relationships.
- Unified framework for comparison of methods.
- Four datasets for illustration.

## Getting Started

The PyTimeVar can implemented as a PyPI package. To download the package in your Python environment, use the following command:
```python 
pip install PyTimeVar
```

