Package: recruitlag 0.1.0

Raymond L. Tremblay

recruitlag: Can Episodic Recruitment be a Delayed Consequence of Continuous Reproduction?

Tests whether an episodic recruitment record can be the delayed consequence of a reproductive record, under any distributed lag. A delay is a convolution, and a convolution is a weighted average, so the concentration in time of expected recruitment can never exceed that of reproduction: reproduction's own concentration is a ceiling. The package computes that ceiling by searching families of lag weights (pure delays, windows, geometric decay and Dirichlet draws), calibrates the pooled comparison against negative-binomial counts to show what it can and cannot refute, and runs the host-level (replicate-unit) test in which the null is the lag hypothesis exactly as it is asserted: expected recruitment on each unit is that unit's own lagged reproduction, scaled to its own total. Uncertainty on the exceedance comes by three routes, a cluster bootstrap over units, a Bayesian bootstrap (Rubin 1981 <doi:10.1214/aos/1176345338>) and a negative-binomial model of the counts fitted with 'Stan' through 'cmdstanr'; recruit_triage() asks whether a first sighting is a recruit or a plant returning from dormancy. Plotting functions draw the ceiling strip, the lag profiles against the observed counts, the calibration and a forest plot of the intervals. The census data on the epiphytic orchid Lepanthes eltoroensis analysed in the companion paper are included.

Authors:Raymond L. Tremblay [aut, cre, cph]

recruitlag_0.1.0.tar.gz
recruitlag_0.1.0.zip(r-4.7-any)recruitlag_0.1.0.zip(r-4.6-any)
recruitlag_0.1.0.tar.gz(r-4.7-any)recruitlag_0.1.0.tar.gz(r-4.6-any)
recruitlag_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
recruitlag/json (API)

# Install 'recruitlag' in R:
install.packages('recruitlag', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/raymondltremblay/recruitlag/issues

Datasets:
  • caladenia_dormancy - Published dormancy, survival and detection for nine _Caladenia_ species
  • lepanthes_census - Census records of the epiphytic orchid _Lepanthes eltoroensis_
  • lepanthes_hosts - Census records of the epiphytic orchid _Lepanthes eltoroensis_
  • lepanthes_monthly - Census records of the epiphytic orchid _Lepanthes eltoroensis_
  • lepanthes_profile - Census records of the epiphytic orchid _Lepanthes eltoroensis_
  • regimes - Six invented census records spanning the cases the test separates
  • regimes_truth - Six invented census records spanning the cases the test separates

On CRAN:

Conda:

2.70 score 7 scripts 29 exports 22 dependencies

Last updated from:f070438670. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK159
source / vignettesOK282
linux-releaseOK152
windows-develOK114
windows-releaseOK130
wasm-releaseOK134

Exports:ceiling_calibrationceiling_draws_tableconcentrationconvolve_lagexpected_recruitsflat_kernelhost_lag_testhost_matriceslag_ceilinglag_ceiling_bayesbootlag_ceiling_bootlag_ceiling_bylag_ceiling_stanlag_kernelsphi_momentrain_cvrain_expectedrain_forestrain_ginirain_indicesrain_intervalsrain_profilesrain_seriesrain_sightingsrain_striprain_stripsrain_unitsrecruit_triageseries_from

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigR6RColorBrewerrlangS7scalestibbleutf8vctrsviridisLitewithr

Introduction to recruitlag: a worked analysis, step by step
Step 1. Load the packages | Step 2. Look at a data set | Step 3. Add up over units | Step 4. Measure how "bursty" each series is | Step 5. Ask the key question | Step 6. Draw it | Step 7. See what a delay would actually predict | Step 8. The careful version of the test | Step 9. A check with a record where a delay is the truth | Step 10. The other way round: a seasonal plant | Step 11. What the four cases teach | Step 12. Your own data

Last update: 2026-10-15
Started: 2026-10-15

Invented records: where the test has power and where it does not
The six records | The ceiling | Why the pooled comparison has no power | The host-level test | Is the host-level test calibrated? | What to take from the set

Last update: 2026-10-15
Started: 2026-10-15

Reading the intervals: confidence, credible, and the four ways to cut one
The one distinction that matters | The three routes | The cluster bootstrap: a confidence interval | The Bayesian bootstrap: a credible interval, same quantity | The negative-binomial model: a credible interval, different quantity | The four ways to cut an interval from a set of draws | The two probability statements, side by side | Choosing, and reporting | References

Last update: 2026-10-15
Started: 2026-10-15

The Lepanthes eltoroensis analysis
The two records | Concentration and the ceiling | What any lag profile predicts | How firm the exceedance is | Why the pooled comparison cannot decide | The host-level test | The verdict, keyed on labels

Last update: 2026-10-15
Started: 2026-10-15

The mathematics behind the test, and the functions that implement it
1. The hypothesis as a convolution | 2. The ceiling: averaging cannot concentrate | 3. The second diagnosis: the lag is unidentifiable | 4. Calibrating the pooled comparison | 5. The host-level null, stated as the hypothesis is asserted | 6. What the test does and does not say | Function map | References

Last update: 2026-10-15
Started: 2026-10-15

Readme and manuals

Help Manual

Help pageTopics
Published dormancy, survival and detection for nine _Caladenia_ speciescaladenia_dormancy
Calibrate the pooled ceiling comparison against realised countsceiling_calibration
One table for several records and routesceiling_draws_table
Apply a lag profile to a reproductive recordconvolve_lag
Expected recruitment per replicate unit under a lag profileexpected_recruits
The flat reference: every bin weighted equallyflat_kernel
The host-level test of the lag hypothesishost_lag_test
Build the unit-by-period matrices from a long data framehost_matrices
The ceiling that any delay places on the concentration of recruitmentlag_ceiling
A posterior for the exceedance, by the Bayesian bootstrap over unitslag_ceiling_bayesboot
A confidence interval for the exceedance, by resampling unitslag_ceiling_boot
The ceiling for every unit in a long data framelag_ceiling_by
A posterior for the exceedance of the expected series, from a model of the countslag_ceiling_stan
Families of lag weightslag_kernels
Census records of the epiphytic orchid _Lepanthes eltoroensis_lepanthes lepanthes_census lepanthes_hosts lepanthes_monthly lepanthes_profile
Moment estimate of negative-binomial clumping under a heterogeneous meanphi_moment
Plot a calibration or a host-level testplot.ceiling_calibration plot.host_lag_test
The exceedance and its interval, for several records and routes on one axisrain_forest
Concentration of a series in timeconcentration rain_cv rain_gini
Compare the ceiling across candidate reproductive measuresrain_indices
Check that the census intervals are what the analysis assumesrain_intervals
Lag profiles, and what they predict on the real recordrain_expected rain_profiles
Plot the two series on a common time axisrain_series
First sightings by period, against what dormancy alone would producerain_sightings
The ceiling strip: observed recruitment against the boundrain_strip
Several strip figures instead of one unreadable onerain_strips
Every unit at once: its ceiling against what it recordedrain_units
Are the first sightings recruits? Dormancy, detection and the discovery seriesrecruit_triage
Six invented census records spanning the cases the test separatesregimes regimes_truth
Pull the two system-wide series from a data frameseries_from