paper_cpsplines_1d

paper_cpsplines_1d is a GitHub repository containing all the figures and simulations results shown in the paper

@article{NAVARROGARCIA2023,
title = {On constrained smoothing and out-of-range prediction using P-splines: A conic optimization approach},
journal = {Applied Mathematics and Computation},
volume = {441},
pages = {127679},
year = {2023},
issn = {0096-3003},
doi = {https://doi.org/10.1016/j.amc.2022.127679},
url = {https://www.sciencedirect.com/science/article/pii/S0096300322007470},
author = {Manuel Navarro-García and Vanesa Guerrero and María Durban},
keywords = {Data science, Penalized splines, Conic optimization, Smoothing, Prediction},
}

All the simulation studies carried out in this work use the routines implemented in cpsplines, which requires a MOSEK license to solve the optimization problems.

Project structure

The current version of the project is structured as follows:

• paper_cpsplines_1d: the main directory of the project, which consist of:
  • figures.ipynb: A Jupyter notebook containing the code used to generate the figures and the tables of the paper.
  • aux_func.py: constituted by a collection of auxiliary functions to generate the figures and tables.
  • multiple_curves.py: contains the code to fit simultaneously multiple curves using the methodology proposed in Section 4.3 of the paper.
• data: a folder containing CSV files with simulated and real data sets.
• img: a folder containing the figures shown in the paper.

Package dependencies

paper_cpsplines_1d mainly depends on the following packages:

• cpsplines.
• Matplotlib.
• MOSEK. License Required
• Numpy.
• Pandas.

Installation

1. To clone the repository on your own device, use

git clone https://github.com/ManuelNavarroGarcia/paper_cpsplines_1d.git
cd paper_cpsplines_1d

2. To install the dependencies, there are two options according to your installation preferences:

• Create and activate a virtual environment with conda (recommended)

conda env create -f env.yml
conda activate paper_cpsplines_1d

• Install the setuptools dependencies via pip

pip install -r requirements.txt
pip install -e .[dev]

3. If neccessary, add version requirements to existing dependencies or add new ones on setup.py. Then, update requirements.txt file using

pip-compile --extra dev > requirements.txt

and update the environment with pip-sync.

Contact Information and Citation

If you have encountered any problem or doubt while using paper_cpsplines_1d, please feel free to let me know by sending me an email:

• Name: Manuel Navarro García (he/his)
• Email: manuelnavarrogithub@gmail.com

If you find paper_cpsplines_1d or cpsplines useful, please cite it in your publications.