Time series forecasting plays a key role in many fields such as business, energy or environment. Traditionally, statistical or machine learning models for time series forecasting are trained with the ...

Although current time-series forecasting methods have significantly improved the state-of-the-art (SOTA) results for long-sequence time-series forecasting (LSTF), they still have difficulty in ...

This repository contains the implementation of the paper "Pre-training Time Series Models with Stock Data Customization." ...

The purpose of this repo is to have an up-to-date and user-friendly Python implementation of Singular Spectrum Analysis (SSA) for time series forecasting, so that anyone could easily experiment with ...

A time series is a sequence of numerical data points in successive order. In investing, it tracks the movement of the chosen data points at regular intervals and over a specified period of time.

Regression is one of the most powerful statistical tools for finding relationships in data. Python makes it easy, and it's much more flexible than a spreadsheet.