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The code to replicate the experiments in the paper "Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization"

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yiruiliu110/df2m

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Code for DF2M

This repository contains the code for DF2M

Requirements

This code is written in Python. The required libraries are:

  • pytorch==1.12.1
  • pyreadr==0.4.7
  • sklearn==1.2.1
  • pyro==1.8.4
  • numpy==1.21.6
  • seaborn==0.12.2
  • tqdm==4.64.1
  • scipy==1.10.0
  • skfda==0.8.1

Usage

To use the code, navigate to the directory where the code is located and run:

$ python main.py

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The code to replicate the experiments in the paper "Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization"

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