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Mixed Data Sampling Regression

0packages depend
8Kdownloads / year
49.2%test coverage
13/13flavors OK

Overview

About

Methods and tools for mixed frequency time series data analysis. Allows estimation, model selection and forecasting for MIDAS regressions.

Changes in 0.9
  • Bugfix release to accomodate links in help pages

From NEWS in the release

Install

Health

CRAN checks
13OK
Slowest check: 5.4 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.9
READMEYes · 181 wordsVignettesNoNEWSYes · 33% structured · mentions 0.9Citation fileYes · cites a publicationWebsiteYes
Cites a JSS article
Help pages
94 (1 internal)includes a package overview page
Examples that run
90%36 run in a plain check · 4 hold no code
Exported functions with examples
48%
Documented parameters
98%
Return-value docs
100%
Help pages citing references
12%

Also includes 8 demo scripts (run with demo())

Downloads

8K
CRAN downloads in the past year
Rank #4,636 · ~22/day · ~666/mo
Daily download trend is not available in this view yet.
62730 days
1.8K90 days
8K1 year
Compare downloads with other packages →
Also on100 r2u6 autocran150 c2d4u

Repository

82Stars
32Forks
21Open issues
0Open PRs
1Releases
522Commits
2Commit identities
522 commits · Last activity 2025-04-07 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
91%
Median days to close, 50 most recently updated closed issues
15
Median days to close, 50 most recently updated closed PRs
1

Stars over time

2025-10-23 · 792026-07-07 · 82
PracticesBeta

8 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/mpiktas/midasr on 2026-10-21.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (1)

GitHub Pages site last deployed 2019-01-02

Coverage (1)
Coverage reporting
Automation and maintenance (1)
pre-commit
Show all practicesHide 1 practice
Lint, format, editor (3)
lintrLint workflowRStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
11 external dependencies (excludes base and recommended)

Installing midasr adds 45 packages (25 with compiled code, 32 MB of source tarballs). Heaviest: ggplot2 6.0 MB, optimx 2.2 MB, nloptr 2.1 MB.

Depends (4)
Imports (11)
MASSnumDerivMatrixforecastzoostatsgraphicsutilsFormulatexregmethods
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Maintainer, Author · added in 0.7

Maintainer since 0.1 (2013)

Listed in earlier versions (2)
Vaidotas Zemlys
no longer listed · 0.1 to 0.6
Vaidotas Zemlys-Balevicius
no longer listed · 0.8
Releases (9)

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
  • 0.9Latest
    record
    2025-04-07 · current release · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 0.8
    record
    2021-02-23 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 0.7
    record
    2019-03-05 · diff ↗ ·
    removed 1 export
    midas_r_simple
    added 18 exports
    extract.midas_r, lstr, midas_lstr_plain, midas_lstr_sim, midas_mmm_plain, midas_mmm_sim, midas_nlpr, midas_pl_plain, midas_pl_sim, midas_qr, midas_r_plain, midas_si_plain, midas_si_sim, midas_sp, mlsd, mmm, plot_lstr, plot_sp
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • 0.6
    record
    2016-08-08 · diff ↗
  • R
    R 3.3.0 released · 2016-05-03
  • 0.5
    record
    2015-07-16 · diff ↗ ·
    added 2 exports
    genexp, genexp_gradient
Show 7 earlier eventsHide 7 earlier events
  • R
    R 3.2.0 released · 2015-04-16
  • 0.4
    record
    2015-03-10 · diff ↗ ·
    removed 20 exports
    almonp.gradient, forecast.midas_r, gompertzp.gradient, hAh.test, hAhr.test, harstep.gradient, lcauchyp.gradient, midas.auto.sim, midas.sim, midas_coef, mls_coef, nakagamip.gradient, nbeta.gradient, nbetaMT.gradient, nealmon.gradient, polystep.gradient, simplearma.sim, weight_coef, weight_names, weight_param
    added 16 exports
    almonp_gradient, gompertzp_gradient, hAh_test, hAhr_test, harstep_gradient, lcauchyp_gradient, midas_auto_sim, midas_sim, nakagamip_gradient, nbetaMT_gradient, nbeta_gradient, nealmon_gradient, plot_midas_coef, polystep_gradient, simulate, update_weights
  • 0.3
    record
    2014-04-30 · diff ↗ ·
    added 4 exports
    harstep, harstep.gradient, midas_r_np, midas_r_simple
  • R
    R 3.1.0 released · 2014-04-10
  • 0.2
    record
    2014-01-07 · diff ↗
  • 0.1
    record
    2013-10-10
  • R
    R 3.0.0 released · 2013-04-03

Package metadata

First published
2013-10-10
Total releases
9 / 13 yrs
License
GPL-2 | MIT + file LICENCE OSI · relicensed from MIT + file LICENCE in 0.3
Minimum R
≥ 2.11.0
Bundled data
71 KB / 8 files
Download size
172 KB
Appears in task views

Cite

Cite this package

Run in R for the authors' entry:

citation("midasr")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.18637/jss.v072.i04.

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 midasr version 0.9 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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