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DESCRIPTION — Description field now cites the
three core methods using the authors (year) <doi:...>
format required by CRAN: Efron & Tibshirani (1993,
ISBN:9780412042317), Meinshausen & Bühlmann (2010)
<doi:10.1111/j.1467-9868.2010.00740.x>, and Peng
(2011) <doi:10.1126/science.1213847>.
Examples — \dontrun{} replaced with
\donttest{} in plot_stability_gg.Rd and
plot_cv_stability_gg.Rd; optional-package examples are now
guarded with a requireNamespace() check inside
\donttest{}.
par() save/restore — all calls to
par(mfrow = ...) in demo/reprostat.R and
vignettes/ReproStat-intro.Rmd now follow the
oldpar <- par(...); on.exit(par(oldpar)) pattern so that
global graphics settings are restored after each code block.
run_diagnostics(): main entry point supporting
"lm", "glm", "rlm" (via
MASS), and "glmnet" (via
glmnet) backends; three perturbation methods
("bootstrap", "subsample",
"noise"). New argument perturb_response
(default FALSE) controls whether the response column is
perturbed under the noise method.perturb_data(): standalone data perturbation with
bootstrap, subsampling, and Gaussian noise injection. New argument
response_col allows the response column to be excluded from
noise perturbation.coef_stability(): variance of coefficient estimates
across perturbation iterations.pvalue_stability(): proportion of iterations in which
each predictor is significant; intercept excluded from output.selection_stability(): sign consistency of estimated
coefficients for "lm" / "glm" /
"rlm" backends; non-zero selection frequency for the
"glmnet" backend. Intercept excluded. This is a genuinely
distinct measure from pvalue_stability().prediction_stability(): pointwise prediction variance
across perturbation iterations.reproducibility_index(): composite 0–100
Reproducibility Index.
c_beta) now uses a global scale
reference (median(|base_coef|)) instead of a hard-coded
epsilon, preventing the score from collapsing for near-zero
coefficients.c_p (p-value stability) and c_sel
(selection stability) are now genuinely distinct components; they
previously computed the same quantity.backend = "glmnet", the selection component
(c_sel) is now the mean non-zero selection frequency and is
always available (previously it was NA). The RI for glmnet
is therefore based on three components instead of two.ri_confidence_interval(): bootstrap confidence interval
for the RI. The seed argument now defaults to
NULL, leaving the caller’s global RNG state undisturbed.
Pass an integer to fix the seed explicitly.cv_ranking_stability(): repeated K-fold CV ranking
stability for model comparison across the same four backends.plot_stability(), plot_cv_stability():
base-graphics visualisations.plot_stability_gg(),
plot_cv_stability_gg(): optional
ggplot2-based equivalents (require
ggplot2).These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.