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galamm: Generalized Additive Latent and Mixed Models #615
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Thanks for submitting to rOpenSci, our editors and @ropensci-review-bot will reply soon. Type |
🚀 Editor check started 👋 |
Checks for galamm (v0.1.1.9000)git hash: 26cfad15
(Checks marked with 👀 may be optionally addressed.) Package License: GPL (>= 3) 1. rOpenSci Statistical Standards (
|
type | package | ncalls |
---|---|---|
internal | base | 439 |
internal | galamm | 76 |
internal | utils | 30 |
internal | graphics | 6 |
imports | stats | 79 |
imports | lme4 | 11 |
imports | Matrix | 11 |
imports | mgcv | 8 |
imports | methods | 3 |
imports | nlme | 3 |
imports | memoise | 1 |
imports | Rcpp | NA |
imports | Rdpack | NA |
suggests | covr | NA |
suggests | gamm4 | NA |
suggests | knitr | NA |
suggests | PLmixed | NA |
suggests | rmarkdown | NA |
suggests | testthat | NA |
linking_to | Rcpp | NA |
linking_to | RcppEigen | NA |
Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table.
base
list (31), seq_along (22), for (19), lapply (19), length (18), c (17), names (15), ncol (15), attr (14), seq_len (14), vapply (14), if (13), drop (11), rep (11), as.numeric (10), is.null (9), nrow (9), integer (8), unlist (8), factor (7), paste (7), qr (7), diff (6), max (6), seq (6), all.vars (5), any (5), matrix (5), numeric (5), cbind (4), colnames (4), logical (4), sqrt (4), beta (3), eval (3), grepl (3), levels (3), Map (3), match.call (3), Reduce (3), return (3), row.names (3), scale (3), unique (3), by (2), col (2), data.frame (2), diag (2), do.call (2), ifelse (2), lengths (2), order (2), parent.frame (2), qr.R (2), rank (2), rbind (2), abs (1), array (1), as.character (1), as.integer (1), as.logical (1), as.matrix (1), assign (1), backsolve (1), deparse (1), deparse1 (1), dim (1), environment (1), getOption (1), inherits (1), intersect (1), is.infinite (1), is.nan (1), min (1), parse (1), pmax (1), qr.qty (1), regexpr (1), rep.int (1), rowSums (1), setdiff (1), split (1), sum (1), t (1), tabulate (1), which (1)
stats
deviance (9), pf (8), formula (6), as.formula (4), BIC (4), family (4), logLik (4), model.matrix (4), weights (4), quantile (3), terms (3), AIC (2), nobs (2), rf (2), terms.formula (2), contrasts (1), D (1), delete.response (1), df (1), gaussian (1), getCall (1), model.frame (1), model.response (1), na.action (1), optim (1), pchisq (1), pnorm (1), qnorm (1), reformulate (1), smooth (1), start (1), update (1), vcov (1)
galamm
extractor (3), factor_finder (3), find_parm_inds (3), fn (3), gr (3), mlwrapper (3), define_factor_mappings (2), extend_lambda (2), extract_name (2), find_k (2), gam.setup (2), gamm4 (2), gamm4.setup (2), interpret.gam0 (2), set_initial_values (2), setup_factor (2), anova.galamm (1), coef.galamm (1), confint.galamm (1), deviance.galamm (1), extract_optim_parameters (1), extract_optim_parameters.galamm (1), factor_loadings (1), factor_loadings.galamm (1), family.galamm (1), fitted.galamm (1), fixef.galamm (1), formula.galamm (1), galamm (1), galamm_control (1), gam.side (1), gamm4.wrapup (1), llikAIC (1), logLik.galamm (1), mappingunwrapping (1), marginal_likelihood (1), new_galamm_control (1), nobs.galamm (1), plot_smooth (1), plot_smooth.galamm (1), plot.galamm (1), predict.galamm (1), print.summary.galamm (1), print.VarCorr.galamm (1), ranef.galamm (1), release_questions (1), residuals.galamm (1), setup_family (1), setup_response_object (1), sl (1), squeeze_mappings (1), t2l (1), VarCorr.galamm (1), variable.summary (1)
utils
data (30)
lme4
findbars (3), nobars (3), lFormula (2), mkReTrms (2), .prt.VC (1)
Matrix
t (4), chol (2), Matrix (2), solve (2), Diagonal (1)
mgcv
new.name (2), smooth2random (2), Rrank (1), s (1), smoothCon (1), t2 (1)
graphics
par (3), abline (2), text (1)
methods
as (3)
nlme
fixef (1), ranef (1), VarCorr (1)
memoise
memoise (1)
NOTE: Some imported packages appear to have no associated function calls; please ensure with author that these 'Imports' are listed appropriately.
3. Statistical Properties
This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.
Details of statistical properties (click to open)
The package has:
- code in C++ (4% in 2 files), C/C++ Header (66% in 18 files) and R (29% in 30 files)
- 1 authors
- 9 vignettes
- 8 internal data files
- 9 imported packages
- 31 exported functions (median 6 lines of code)
- 81 non-exported functions in R (median 16 lines of code)
- 618 C/C++ functions (median 4 lines of code)
Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:
loc
= "Lines of Code"fn
= "function"exp
/not_exp
= exported / not exported
All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown()
function
The final measure (fn_call_network_size
) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.
measure | value | percentile | noteworthy |
---|---|---|---|
files_R | 30 | 89.3 | |
files_src | 2 | 79.1 | |
files_inst | 18 | 99.6 | |
files_vignettes | 9 | 99.2 | |
files_tests | 10 | 90.7 | |
loc_R | 1777 | 81.8 | |
loc_src | 252 | 31.9 | |
loc_inst | 4014 | 86.1 | |
loc_vignettes | 1732 | 96.3 | TRUE |
loc_tests | 2479 | 95.4 | TRUE |
num_vignettes | 9 | 99.6 | TRUE |
data_size_total | 265405 | 88.8 | |
data_size_median | 13688 | 80.9 | |
n_fns_r | 112 | 79.1 | |
n_fns_r_exported | 31 | 79.2 | |
n_fns_r_not_exported | 81 | 79.5 | |
n_fns_src | 618 | 96.1 | TRUE |
n_fns_per_file_r | 2 | 39.7 | |
n_fns_per_file_src | 24 | 95.1 | TRUE |
num_params_per_fn | 2 | 11.9 | |
loc_per_fn_r | 12 | 36.1 | |
loc_per_fn_r_exp | 6 | 10.5 | |
loc_per_fn_r_not_exp | 16 | 52.7 | |
loc_per_fn_src | 4 | 2.0 | TRUE |
rel_whitespace_R | 18 | 80.9 | |
rel_whitespace_src | 14 | 29.1 | |
rel_whitespace_inst | 24 | 85.7 | |
rel_whitespace_vignettes | 51 | 99.2 | TRUE |
rel_whitespace_tests | 11 | 88.9 | |
doclines_per_fn_exp | 42 | 52.8 | |
doclines_per_fn_not_exp | 0 | 0.0 | TRUE |
fn_call_network_size | 1302 | 98.5 | TRUE |
3a. Network visualisation
Click to see the interactive network visualisation of calls between objects in package
4. goodpractice
and other checks
Details of goodpractice checks (click to open)
3a. Continuous Integration Badges
GitHub Workflow Results
id | name | conclusion | sha | run_number | date |
---|---|---|---|---|---|
6584930507 | lint | success | 26cfad | 495 | 2023-10-20 |
6584967181 | pages build and deployment | success | 2fba91 | 144 | 2023-10-20 |
6584930514 | pkgdown | success | 26cfad | 350 | 2023-10-20 |
6584930510 | R-CMD-check | success | 26cfad | 558 | 2023-10-20 |
6584930523 | test-coverage | success | 26cfad | 248 | 2023-10-20 |
3b. goodpractice
results
R CMD check
with rcmdcheck
R CMD check generated the following note:
- checking installed package size ... NOTE
installed size is 34.0Mb
sub-directories of 1Mb or more:
doc 2.0Mb
libs 30.7Mb
R CMD check generated the following check_fail:
- rcmdcheck_reasonable_installed_size
Test coverage with covr
Package coverage: 98.35
Cyclocomplexity with cyclocomp
The following functions have cyclocomplexity >= 15:
function | cyclocomplexity |
---|---|
galamm | 45 |
gam.setup | 44 |
gamm4.wrapup | 44 |
interpret.gam0 | 29 |
define_factor_mappings | 17 |
galamm_control | 17 |
Static code analyses with lintr
lintr found the following 296 potential issues:
message | number of times |
---|---|
Avoid library() and require() calls in packages | 10 |
Lines should not be more than 80 characters. | 286 |
5. Other Checks
Details of other checks (click to open)
✖️ The following 2 function names are duplicated in other packages:
-
plot_smooth
from itsadug
-
sl
from reinsureR
Package Versions
package | version |
---|---|
pkgstats | 0.1.3.9 |
pkgcheck | 0.1.2.10 |
srr | 0.0.1.194 |
Editor-in-Chief Instructions:
This package is in top shape and may be passed on to a handling editor
👋 @noamross, I just wanted to ask: what's the status of this submission? Is rOpenSci interested in reviewing it? |
@osorensen, thanks for following up. My apologies, I think this package fell between cracks in our editor hand-off. I'll follow up later today. |
@osorensen Apologies once again, with recent organisational changes this once again fell through the cracks. We are now finally on it. How are you positioned if we finally get the process started now? |
@mpadge, a paper describing the package is currently under review for a journal, so I think my best option now is the withdraw the submission to ropensci. I can maybe just to that by closing this issue? |
@osorensen We'd still like to work with you to get this through our review process. How about one of the following options:
Note that if your submission is to Journal of Statistical Software, then our system has been developed in collaboration with their processes, and they would likely welcome you using the results of a review here to support their own process. |
Thanks @mpadge, I go for option 1 then, and will ping you here once I've got a final decision on the paper. |
@mpadge, I just stumbled upon this notification. Thank you for mentioning my package review case. The peer review process has significantly enhanced the package's quality in a very short period of time, and I also believe this has expedited its review for publication in the Journal of Statistical Software. |
@mpadge, the software paper is now published in Multivariate Behavioral Research, https://doi.org/10.1080/00273171.2024.2385336. We can therefore start this review now. |
@ropensci-review-bot check srr |
1 similar comment
@ropensci-review-bot check srr |
@ropensci-review-bot check srr |
@ropensci-review-bot check srr |
@adamhsparks @osorensen Sorry for any inconvenience. The non-responsive bot was a bug on our side that has now been fixed. It should all work now when you call |
@ropensci-review-bot check srr |
✖️ Error: Package documents compliance only with general standards. Statistical packages must document compliance with at least one set of category-specific standards as well. The following standards are missing: General standards: G5.2, G5.2a, G5.2b, G5.3, G5.4a, G5.4b, G5.5, G5.6 All standards must be documented prior to submission |
@maelle, the above seems to be a false positive. The mentioned standards are documented here: |
@osorensen, unfortunately, that's not a false positive. They are not properly documented so that the bot can find the standards. The documentation for ROxygen2 needs to be in /R, not /tests for it to be valid, e.g., https://github.com/giovsaraceno/QuadratiK-package/blob/master/R/srr-stats-standards.R If you just move it, and redocument it should be fine. |
@ropensci-review-bot check srr |
@osorensen Sorry, bot's not quite ready for your case. Yours is the first package we've had with standards in (And FYI @adamhsparks, "srrstats" tags can go pretty much anywhere at all, including README, tests, src, and R code.) |
✖️ Error: Package documents compliance only with general standards. Statistical packages must document compliance with at least one set of category-specific standards as well. 'srr' standards compliance:
✔️ This package complies with > 50% of all standads and may be submitted. |
@mpadge, I moved the documentation to |
Sorry, my bad. I was just trying to help based on previous cases. |
@adamhsparks and @osorensen The system has now been rebuilt, and the bot comment above that "This package ... may be submitted" would no longer appear. The first "Error:" would first have to be addressed. |
@mpadge, this seemed to be fine when I submitted the package, see the |
@osorensen The standards haven't changed, but since that time we've added additional checks to identify packages which only document general standards, with no category-specific ones. The general package checks also now generate and link to the full report on stats standards compliance, like in this example here, so we'd explicitly see there also that compliance statements with regression standards were missing. So before proceeding, we'd need you to comply with our Regression Standards. Previous experience suggests that'll require around one day's work or so. As always, please let us know if you've got any questions, and in particular, feel free to comment in any way you like regarding the standards, ideally in the stats-devguide repo, linked directly from the book. Thanks! |
@ropensci-review-bot check srr |
@mpadge @adamhsparks, I'm not sure if I'm allowed to run |
@osorensen Sorry, that was a wee 🐛 on our side. Should work now, but note that result will currently indicate that RE4.15 is missing, so maybe add that standard first before calling? |
@ropensci-review-bot check srr |
Thanks @mpadge, there was a typo in there, which should be fixed now. I tried running |
@ropensci-review-bot check srr |
1 similar comment
@ropensci-review-bot check srr |
'srr' standards compliance:
✔️ This package complies with > 50% of all standards and may be submitted. |
@osorensen @adamhsparks The previous calls seem to have issued during our weekly system rebuild. Just rotten timing, but all should work fine from here on. And nice work @osorensen - 100% compliance!! |
@ropensci-review-bot assign @noamross as editor |
Assigned! @noamross is now the editor |
@ropensci-review-bot seeking reviewers |
Please add this badge to the README of your package repository: [![Status at rOpenSci Software Peer Review](https://badges.ropensci.org/615_status.svg)](https://github.com/ropensci/software-review/issues/615) Furthermore, if your package does not have a NEWS.md file yet, please create one to capture the changes made during the review process. See https://devguide.ropensci.org/releasing.html#news |
Submitting Author Name: Øystein Sørensen
Submitting Author Github Handle: @osorensen
Repository: https://github.com/LCBC-UiO/galamm
Version submitted: 0.1.1.9000
Submission type: Stats
Badge grade: gold
Editor: @noamross
Reviewers: TBD
Archive: TBD
Version accepted: TBD
Language: en
Scope
Please indicate which of our statistical package categories this package falls under. (Please check one appropriate box below):
Statistical Packages
Pre-submission Inquiry
General Information
Who is the target audience and what are scientific applications of this package?
The target audience is applied statisticians and quantitative scientists, particularly those working on the social sciences. The package is motivated by longitudinal studies in cognitive neuroscience, but it is applicable wherever a measurement model (of factor analysis type) needs to be combined with hierarchical modeling.
Paste your responses to our General Standard G1.1 here, describing whether your software is:
This is the first implementation of the algorithm developed in Sørensen, Fjell, and Walhovd (2023).
Not applicable.
Badging
What grade of badge are you aiming for? (bronze, silver, gold)
gold
If aiming for silver or gold, describe which of the four aspects listed in the Guide for Authors chapter the package fulfils (at least one aspect for silver; three for gold)
Technical checks
Confirm each of the following by checking the box.
autotest
checks on the package, and ensured no tests fail.Running
autotest
gives some errors, but they were waived in the pre-review issue.srr_stats_pre_submit()
function confirms this package may be submitted.pkgcheck()
function confirms this package may be submitted - alternatively, please explain reasons for any checks which your package is unable to pass.This package:
Publication options
The package is on CRAN. I am aware that rOpenSci recommends waiting with submitting to CRAN, but the package has some users already, and having pre-compiled binaries on CRAN makes it easier for them to install it, rather than having to set up a toolchain required for install from source. I hence opted to send it to CRAN.
Code of conduct
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