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gmfamm

0.1.1Package record

Generalized Multivariate Functional Additive Models

0packages depend
4.4Kdownloads / year
4.0%test coverage
12/13flavors OK

Overview

About

Supply implementation to model generalized multivariate functional data using Bayesian additive mixed models of R package 'bamlss' via a latent Gaussian process (see Umlauf, Klein, Zeileis (2018) doi:10.1080/10618600.2017.1407325).

Changes in 0.1.1
  • Resubmission as suggested package 'registr' was temporarily removed from CRAN.

From NEWS.md in the release

Install

Health

CRAN checks
1ERROR12OK
Check messages
ERRORexamplesr-devel-linux-x86_64-debian-gcc
Running examples in ‘gmfamm-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: trafficfam3
> ### Title: Draft of family for traffic example
> ### Aliases: trafficfam3
> 
> ### ** Examples
> 
> # Construct data
> set.seed(123)
> # Number of subjects
> n <- 10
> 
> # Number of observations
> ni <- 3
> 
> # Covariate vector
> x <- rep(rnorm(n), each = ni)
> t <- rep(c(0, 0.5, 1), times = n)
> 
> # Additive predictor
> eta_1 <- eta_2 <- eta_3 <- eta_4 <- t + 0.5*x
> 
> # Outcomes
> y1 <- rnbinom(n*ni, exp(eta_1), 0.3)
> y2 <- rnbinom(n*ni, exp(eta_2), 0.4)
> y3 <- rgamma(n*ni, shape = 0.3, scale = exp(eta_3) / 0.3)
> y4 <- rgamma(n*ni, shape = 0.4, scale = exp(eta_4) / 0.4)
> 
> # Data format
> dat <- data.frame(
+    id = factor(rep(seq_len(n), each = ni)),
+    y = c(y1, y2, y3, y4),
+    dim = factor(rep(c(1:4), each = n*ni)),
+    t = t,
+    x = x,
+    fpc = 1
+ )
> 
> # Specify formula
> f <- list(
+   gm(y, dim) ~ t + x,
+   sigma1 ~ 1,
+   mu2 ~ t + x,
+   sigma2 ~ 1,
+   mu3 ~ t + x,
+   sigma3 ~ 1,
+   mu4 ~ t + x,
+   sigma4 ~ 1,
+   Lambda ~ -1 + s(id, by = fpc, bs = "re")
+ )
> 
> # Model
> b <- bamlss(f, family = trafficfam3, n.iter = 20, burnin = 10,
+             data = dat)
Error in a$specials[[i]] : subscript out of bounds
Calls: bamlss ... assign.design -> drop.terms.bamlss -> delete.response -> off
Execution halted
ERRORtestsr-devel-linux-x86_64-debian-gcc
Running ‘testthat.R’ [5s/5s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
  > # * https://testthat.r-lib.org/articles/special-files.html
  > 
  > library(testthat)
  > library(gmfamm)
  Loading required package: bamlss
  Loading required package: coda
  Loading required package: colorspace
  Loading required package: distributions3
  
  Attaching package: 'distributions3'
  
  The following object is masked from 'package:stats':
  
      Gamma
  
  The following object is masked from 'package:grDevices':
  
      pdf
  
  Loading required package: mgcv
  Loading required package: nlme
  This is mgcv 1.9-4. For overview type '?mgcv'.
  -
  For citation info, use citation("
...[truncated]...
mlss:::predict.bamlss(...) at gmfamm/R/predict.R:93:5
   5.       └─bamlss:::term.labels2(...)
   6.         └─bamlss:::drop.terms.bamlss(...)
   7.           └─stats::delete.response(tx)
   8.             └─stats (local) off(a$specials[[i]])
  ── Error ('test-predict.R:184:3'): prediction for single model terms works ─────
  <subscriptOutOfBoundsError/error/condition>
  Error in `a$specials[[i]]`: subscript out of bounds
  Backtrace:
      ▆
   1. ├─stats::predict(b, term = "x1", type = "link", intercept = TRUE) at test-predict.R:184:3
   2. └─bamlss:::predict.bamlss(b, term = "x1", type = "link", intercept = TRUE)
   3.   └─family$predict(...)
   4.     └─bamlss:::predict.bamlss(...) at gmfamm/R/predict.R:93:5
   5.       └─bamlss:::term.labels2(...)
   6.         └─bamlss:::drop.terms.bamlss(...)
   7.           └─stats::delete.response(tx)
   8.             └─stats (local) off(a$specials[[i]])
  
  [ FAIL 4 | WARN 0 | SKIP 0 | PASS 3 ]
  Error:
  ! Test failures.
  Execution halted

CRAN check page ↗

Slowest check: 3.6 min · r-oldrel-windows-x86_64
Status changes
  • ERROR12 OK, 1 ERROR2026-10-24
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
Show 1 earlier changeHide 1 earlier change
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.1
READMEYes · 66 wordsVignettesNoNEWSYes · 67% structured · mentions 0.1.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
17
Examples that run
100%5 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
18%

Downloads

4.4K
CRAN downloads in the past year
Rank #17,123 · ~12/day · ~371/mo
Daily download trend is not available in this view yet.
34030 days
74790 days
4.4K1 year
Compare downloads with other packages →
Also on73 r2u2 autocran

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)

Installing gmfamm adds 10 packages (7 with compiled code, 27 MB of source tarballs). Heaviest: BH 14 MB, sp 4.3 MB, MBA 3.3 MB.

Depends (2)
R >= 3.5bamlss
Imports (5)
mgcvstatsMASSsplinesMatrix
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
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
  • 0.1.1Latest
    record
    2026-03-24 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 0.1.0
    record
    2024-06-18
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-06-18
Total releases
2 / 2 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5
Bundled data
15 KB / 1 file
Download size
2.8 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("gmfamm")
Volkmann, A., & Umlauf, N. (2026). gmfamm: Generalized Multivariate Functional Additive Models (Version 0.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.gmfamm

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 gmfamm version 0.1.1 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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