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hdtsa

https://github.com/linc2021/hdtsa

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 30 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (14.8%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: Linc2021
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 1.75 MB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 3
  • Open Issues: 0
  • Releases: 0
Created about 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme

README.Rmd 

---
title: "An introduction to `HDTSA`"
# output: rmarkdown::html_vignette
output: rmarkdown::github_document
vignette: >
  %\VignetteIndexEntry{An introduction to HDTSA}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
  %\VignetteDepends{HCmodelSets}
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%",
  warning = F,
  message = F
)
```

# HDTSA





An implementation for high-dimensional time series analysis methods, including: factor model for vector time series proposed by Lam and Yao (2012) [](https://doi.org/10.1214/12-AOS970) and Chang, Guo and Yao (2015) [](https://doi.org/10.1016/j.jeconom.2015.03.024), martingale difference test proposed by Chang, Jiang and Shao (2022) [](https://doi.org/10.1016/j.jeconom.2022.09.001), principal component analysis for vector time series proposed by Chang, Guo and Yao (2018) [](https://doi.org/10.1214/17-AOS1613), cointegration analysis proposed by Zhang, Robinson and Yao (2019) [](https://doi.org/10.1080/01621459.2018.1458620), unit root test proposed by Chang, Cheng and Yao (2021) [](https://doi.org/10.1093/biomet/asab034), white noise test proposed by Chang, Yao and Zhou (2017) [](https://doi.org/10.1093/biomet/asw066), CP-decomposition for high-dimensional matrix time series proposed by Chang, He, Yang and Yao (2023) [](https://doi.org/10.1093/jrsssb/qkac011) and Chang, Du, Huang and Yao (2024) [](https://doi.org/10.48550/arXiv.2410.05634), and Statistical inference for high-dimensional spectral density matrix porposed by Chang, Jiang, McElroy and Shao (2023) [](https://doi.org/10.48550/arXiv.2212.13686).

## Installation

You can install the released version of `HDTSA` from [CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("HDTSA")
```

Or try the development version on GitHub:

``` r
# install.packages("devtools")
devtools::install_github("Linc2021/HDTSA")
```

## Example

This is a basic example which shows you how to solve a unit root test problem :

```{r example}
library(HDTSA)
N=100
Y=arima.sim(list(ar=c(0.9)), n = 2*N, sd=sqrt(1))
con_vec=c(0.45,0.55,0.65)
lagk.vec=c(0,1,2)
UR_test(Y,lagk.vec=lagk.vec, con_vec=con_vec,alpha=0.05)
UR_test(Y,alpha=0.05)
```

Here, we have provided just one example. You can use functions within the package `HDTSA` to solve other problems. For details, please refer to

``` r
help("HDTSA")
```

## Bug report

Please send an email to Chen Lin([linchen\@smail.swufe.edu.cn](mailto:linchen@smail.swufe.edu.cn){.email}).

Owner

  • Login: Linc2021
  • Kind: user

GitHub Events

Total
  • Watch event: 1
  • Push event: 11
Last Year
  • Watch event: 1
  • Push event: 11

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 29
  • Total Committers: 3
  • Avg Commits per committer: 9.667
  • Development Distribution Score (DDS): 0.31
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Linc2021 l****n@s****n 20
linc2021 l****n@l****l 8
Dirk Eddelbuettel e****d@d****g 1
Committer Domains (Top 20 + Academic)
debian.org: 1 smail.swufe.edu.cn: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 0
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 16 days
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • eddelbuettel (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 676 last-month
  • Total docker downloads: 20,358
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
cran.r-project.org: HDTSA

High Dimensional Time Series Analysis Tools

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 676 Last month
  • Docker Downloads: 20,358
Rankings
Forks count: 17.8%
Dependent packages count: 29.8%
Average: 32.2%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Downloads: 43.0%
Maintainers (1)
linchen@smail.swufe.edu.cn
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • Rcpp * imports
  • clime * imports
  • methods * imports
  • sandwich * imports
  • stats * imports
  • knitr * suggests