Skip to content

tobiaskley/quantspec

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Build Status Coverage Status CRAN RStudio mirror downloads CRAN_Status_Badge

quantspec: Quantile-Based Spectral Analysis with R

The aim of the quantspec package is to make methods for quantile-based spectral analysis of time series available to data analysts and researchers in statistics.

You can track (and contribute to) the development of quantspec at https://github.com/tobiaskley/quantspec. If you encounter unexpected behavior while using quantspec, please write an email or file an issue.

Getting started with quantspec

First, if you have not done so already, install R from http://www.r-project.org (click on download R, select a location close to you, and download R for your platform). Once you have the latest version of R installed and started execute the following commands on the R shell:

install.packages("devtools")
devtools::install_github("tobiaskley/quantspec", ref="develop")

This will first install the R package devtools and then use it to install the latest (development) version of quantspec from the GitHub repository. In case you do not have LaTeX installed on your computer you may want to use

devtools::install_github("tobiaskley/quantspec", ref="develop", build_vignette = FALSE)

to skip building the vignette.

Now that you have R and quantspec installed you can access all the functions available. To load the package and access the help files:

library(quantspec)
help("quantspec")

Three demos are available. They can be started by

demo("sp500")
demo("wheatprices")
demo("qar-simulation")

At the bottom of the online help page to the package you will find an index to all the help files available. If you did not skip building the vignette (a preprint of a paper including a tutorial and two worked examples) you can access it via

vignette("quantspec")

About

Quantile-based Spectral Analysis of Time Series

Resources

Stars

Watchers

Forks

Packages

No packages published