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Adaptive Estimation for Weakly Dependent Functional Time Series

This repository contains real data and R code for reproducing the numerical study in the paper Adaptive Estimation for Weakly Dependent Functional Time Series available on arXiv.

The real data supporting the results of the study is the Individual Household Electric Power Consumption which is publicly available and also copied in the folder real_data_application.

The data for the Monte Carlo study can be generated using the code provided in the simulations folder.

Contents

The numerical study is divided into two main parts:

  • Simulation: The scripts to reproduce the simulation results are in the simulations folder.
  • Real Data Application: The scripts to reproduce the real data analysis are in the real_data_application folder.

Installation

Install using devtools

#. Make sure you have devtools package installed :

install.packages("devtools")

Then using devtools install the package :

devtools::install_github(
    repo = "hmaissoro/Adaptive_Estimation_for_Weakly_Dependent_FTS", # the repo
    ref = "HEAD", # use the latest commit
    subdir = "adaptiveFTS", # the package is not at the main root but inside the directory adaptiveFTS
    build = TRUE,
    build_manual = FALSE,
    build_vignettes = FALSE
)

Build manually

If you are using UNIX system, using z-shell :

zsh build.zsh

The compiled package should be available in

...
┣ out
┃ ┗ adaptiveFTS_0.1.0_arm64.tar.gz
                        △
                os and architecure

else RUN

cd adaptiveFTS
R CMD check .
R CMD build .
R CMD INSTALL .
Rscript -e "devtools::build_manual()"
#                             put the actual name of the compiled file
#                                             ▽
Rscript -e 'install.packages( "./adaptiveFTS_[...].tar.gz"  ,repos = NULL, type = "source")'
#               put the actual name of the compiled file
#                               ▽
install.packages( "./adaptiveFTS_[...].tar.gz"  ,repos = NULL, type = "source")

Important Information

Each script in both folders is numbered from 01 to 07 and must be run in sequence.

At the beginning of each script, the functions from the R folder need to be loaded. You will see the line:

all_func <- list.files("../R/")

You may need to adjust this line to match your working directory.

Results

The results produced by the scripts are stored in the following folders:

  • paper_graphs: Contains the graphs used in the paper.
  • paper_tables: Contains the tables used in the paper.