R Observatory: Metrics for tsissm version 1.0.3

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

tsissm needs flextable, which CRAN will archive unless its check problems are fixed by Oct 22.

tsissm

1.0.3Package record

Linear Innovations State Space Unobserved Components Model

0packages depend

3.4Kdownloads / year

46.8%test coverage

13/13flavors OK

Overview

About

Maintained by Alexios GalanosCRAN page ↗GitHub ↗Website ↗

Unobserved components time series model using the linear innovations state space representation (single source of error) with choice of error distributions and option for dynamic variance. Methods for estimation using automatic differentiation, automatic model selection and ensembling, prediction, filtering, simulation and backtesting. Based on the model described in Hyndman et al (2012) doi:10.1198/jasa.2011.tm09771.

Changes in 1.0.3

Work around RTMB AD eigen failures on M1 macOS. CRAN M1MAC/R-devel checks fail

while taping RTMB's AD overload for non-symmetric eigen decompositions, with an

invalid advector error inside the complex eigenvector normalization path.

This appears to be platform and toolchain sensitive: Apple silicon, especially M1 (but not M3),

does not provide the same extended precision behavior as some x86 paths, and the

reduced floating-point headroom can expose fragile complex eigen/AD calculations.

Added a lazy runtime capability check for RTMB AD eigen support. Normal platforms

continue to use RTMB's AD eigen constraints. If the capability check fails, the

package falls back only for eigenvalue constraints: constraint values are

computed with numeric base::eigen() and constraint Jacobians are computed by

central finite differences. The likelihood, scores, and other TMB/RTMB AD paths

remain unchanged.

Show all changes in 1.0.3Hide the rest of the changes in 1.0.3

Exposed tsissm_capabilities() to report the detected RTMB AD eigen capability,

source of the decision, RTMB/TMB versions, and platform details.

Documented the tsissm.rtmb_ad_eigen option under estimate() so users can force RTMB AD

eigen constraints or force the finite-difference fallback for diagnostics.

Also avoided a fragile vignette conversion through as_flextable() by printing

the model summary directly.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("tsissm", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("tsmodels/tsissm")

Development version from tsmodels/tsissm. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-tsissm

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-tsissm

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-tsissm

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 15.4 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-07-22
ERROR12 OK, 1 ERROR2026-05-02
OK12 OK2026-04-25

Show 3 earlier changesHide 3 earlier changes

NOTE11 OK, 3 NOTE2026-04-22
ERROR10 OK, 3 NOTE, 1 ERROR2026-04-18
NOTE11 OK, 3 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.0.3

README· In the repository, left out of the releaseVignettesYes · 5 · dynamicNEWSYes · 100% structured · mentions 1.0.3Citation fileNoWebsiteYes

Help pages: 38 (2 internal)includes a package overview page
Examples that run: 100%1 run in a plain check
Exported functions with examples: 20%
Documented parameters: 100%
Return-value docs: 80%
Help pages citing references: 3%

Vignettes (5)

How these are measured

Downloads

3.4K

CRAN downloads in the past year

Rank #9,798 · ~9/day · ~287/mo

Releases R versions

Daily download trend is not available in this view yet.

38730 days

99990 days

3.4K1 year

Compare downloads with other packages →

Also on392 r2u3 autocran

How downloads are counted

Repository

tsmodels/tsissm ↗Organization: tsmodels

3Stars

1Forks

1Open issues

0Open PRs

0Releases

82Commits

4Commit identities

forecastingtime-series

82 commits · Last activity 2026-10-09 · 0% stars, 30d · Default branch at 1.0.4, ahead of CRAN 1.0.3 (checked 2026-10-11)

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: not measured
Median days to close, 50 most recently updated closed PRs: 8

Stars over time

2025-04-30 · 32026-07-07 · 3

How these are measured

PracticesBeta

3 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/tsmodels/tsissm on 2026-10-11.

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)

README.Rmd

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

24 external dependencies (excludes base and recommended)

Installing tsissm adds 129 packages (73 with compiled code, 103 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (3)

R >= 4.1.0Rcpp tsmethods

Imports (16)

TMBmethodstsaux tsdistributions zoo xts copula flextable data.table sandwich nloptr RTMB viridisLite future future.apply progressr

LinkingTo (3)

Rcpp TMB RcppEigen

Suggests (4)

rmarkdown tstests knitr testthat

Enhances (0)

none

Dependencies facing archival

CRAN will archive these unless their check problems are fixed by the date shown. This package needs each one to install.

flextablefix by Oct 22

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (1)

Alexios Galanos

Author, Maintainer since 1.0.1 (2025)

Releases (3)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
1.0.3Latest
record
2025-07-12 · current release · diff ↗ ·
added 1 export
tsissm_capabilities
1.0.2
record
2025-07-12 · diff ↗ ·
added 1 export
issm_control
1.0.1
record
2025-04-28
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2025-04-28
Total releases: 3 / 1 yrs
License: GPL-2 OSI
Minimum R: ≥ 4.1.0
Bundled data: 70 KB / 3 files
Download size: 763 KB

Appears in task views

Time Series Analysis

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("tsissm")

Format

Galanos, A. (2026). tsissm: Linear Innovations State Space Unobserved Components Model (Version 1.0.3) [Computer software]. https://doi.org/10.32614/CRAN.package.tsissm

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.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for tsissm version 1.0.3 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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