Metadata-Version: 2.1
Name: PyTimeVar
Version: 0.0.7
Summary: 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.
Home-page: https://github.com/bpvand/PyTimeVar
Author: Mingxuan Song, Bernhard van der Sluis, Yicong Lin
Author-email: 678270ms@eur.nl, vandersluis@ese.eur.nl, yc.lin@vu.nl
License: GPLv3+
Keywords: time-varying,bootstrap,nonparametric estimation,filtering
Requires-Python: >=3.9
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: scipy
Requires-Dist: statsmodels
Requires-Dist: tqdm

# 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
```
