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Simulate Time Series Diagnostics

0packages depend
2.5Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

These are tools that allow users to do time series diagnostics, primarily tests of unit root, by way of simulation. While there is nothing necessarily wrong with the received wisdom of critical values generated decades ago, simulation provides its own perks. Not only is simulation broadly informative as to what these various test statistics do and what are their plausible values, simulation provides more flexibility for assessing unit root by way of different thresholds or different hypothesized distributions.

Changes in 0.2.0

Updates across the board, including:

  • Clarified/updated functionality to spp_test().
  • skpss_test() performs the KPSS test with simulated critical values.
  • sim_ts() is a function for simulating time series, mostly used internally.
  • sim_df_mod() is a function for simulating Dickey-Fuller statistics, mostly used internally.
  • sadf_test() does the (Augmented) Dickey-Fuller test with simulated critical values.
  • adf_lag_select() helps the user identify potentially optimal lag selection for (Augmented) Dickey-Fuller tests.
  • ur_summary() provides a more straightforward function to summarize unit root tests produced in this package.
  • USDICE, tbills, exCopdab, lag_suggests, and money_demand are toy data sets now included in this package.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 52 s · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.2.0
READMEYes · 158 wordsVignettesNoNEWSYes · 100% structured · mentions 0.2.0Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
13
Examples that run
100%7 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
31%

Downloads

2.5K
CRAN downloads in the past year
Rank #21,183 · ~7/day · ~207/mo
Daily download trend is not available in this view yet.
21830 days
63390 days
2.5K1 year
Compare downloads with other packages →
Also on86 r2u5 autocran

Dependencies

Declared dependencies
0 external dependencies (excludes base and recommended)

Installing sTSD adds no packages beyond those that come with R.

Depends (1)
R >= 3.6.0
Imports (0)
none
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (1)
Author, Maintainer since 0.1.0 (2024)
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 0.2.0Latest
    record
    2025-01-27 · current release · diff ↗ ·
    added 5 exports
    adf_lag_select, sadf_test, sim_df_mod, sim_ts, skpss_test
  • 0.1.0
    record
    2024-12-20
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-12-20
Total releases
2 / 2 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.6.0
Bundled data
159 KB / 6 files
Download size
168 KB
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("sTSD")
Miller, S. (2025). sTSD: Simulate Time Series Diagnostics (Version 0.2.0) [Computer software]. https://doi.org/10.32614/CRAN.package.sTSD

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for sTSD version 0.2.0 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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