Package: pcvr 1.4.0

Josh Sumner

pcvr: Plant Phenotyping and Bayesian Statistics

Analyse common types of plant phenotyping data, provide a simplified interface to longitudinal growth modeling and select Bayesian statistics, and streamline use of 'PlantCV' output. Several Bayesian methods and reporting guidelines for Bayesian methods are described in Kruschke (2018) <doi:10.1177/2515245918771304>, Kruschke (2013) <doi:10.1037/a0029146>, and Kruschke (2021) <doi:10.1038/s41562-021-01177-7>.

Authors:Josh Sumner [aut, cre], Jeffrey Berry [aut], Noah Fahlgren [rev], Donald Danforth Plant Science Center [cph]

pcvr_1.4.0.tar.gz
pcvr_1.4.0.zip(r-4.7)pcvr_1.4.0.zip(r-4.6)pcvr_1.4.0.zip(r-4.5)
pcvr_1.4.0.tgz(r-4.6-any)pcvr_1.4.0.tgz(r-4.5-any)
pcvr_1.4.0.tar.gz(r-4.7-any)pcvr_1.4.0.tar.gz(r-4.6-any)
pcvr_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
pcvr/json (API)
NEWS

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

Bug tracker:https://github.com/danforthcenter/pcvr/issues

Pkgdown/docs site:https://danforthcenter.github.io

On CRAN:

Conda:

6.47 score 5 stars 33 scripts 495 downloads 64 exports 119 dependencies

Last updated from:4bca312f97. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK366
source / vignettesOK437
linux-release-x86_64OK363
macos-release-arm64OK226
macos-oldrel-arm64OK370
windows-develOK321
windows-releaseOK345
windows-oldrelOK309
wasm-releaseOK200

Exports:awkHelperbargbrmPlotbrmSurvPlotbrmViolincheckGroupscombineDrawsconjugatecumulativePhenodistributionPlotfitGrowthfitGrowthbrmsfitGrowthbrmsgamfitGrowthflexsurvfitGrowthlmfitGrowthmgcvgamfitGrowthnlmefitGrowthnlmegamfitGrowthnlrqfitGrowthnlrqgamfitGrowthnlsfitGrowthnlsgamfitGrowthrqfitGrowthsurvregflexsurvregPlotfremgam_diffgamPlotgrowthPlotgrowthSimgrowthSSlmPlotmv_agmvSimmvSSnet.plotnlmePlotnlrqPlotnlsPlotpcadfpcv_themepcv.emdpcv.eucpcv.joyplotpcv.netpcv.outlierspcv.plsrpcv.timepcv.waterplotPriorplotVIPpwueread.pcvread.pcv.3relativeTolerancerqPlotstat_brms_modelstat_growthssstat_lme_modelstat_nlme_modelstat_nlrq_modelstat_nls_modelsurvregPlottestGrowth

Dependencies:abindbackportsbase64encbayestestRbootbroombslibcachemcarcarDatacliclustercolorspacecowplotcpp11crosstalkdata.tabledatawizardDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluateextraDistrFactoMineRfarverfastmapflashClustfontawesomeforecastFormulafracdifffsgenericsggplot2ggrepelggridgesgluegridExtragtablehighrhtmltoolshtmlwidgetsigraphinsightisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmeSplineslmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmvtnormnlmenloptrnnetnumDerivotelpatchworkpbkrtestpillarpkgconfigpromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownS7sassscalesscatterplot3dSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisviridisLitewithrxfunyamlzoo

Longitudinal Growth Modeling Options

Josh Sumner, DDPSC Data Science Core Facility

Rendered fromlongitudinal.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2025-06-03
Started: 2023-08-09

pcvr

Josh Sumner, DDPSC Data Science Core Facility

Rendered frompcvr.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2025-06-03
Started: 2023-02-21

Root Traits

Josh Sumner, DDPSC Data Science Core Facility

Rendered fromroots.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2025-06-03
Started: 2024-04-29

Readme and manuals

Help Manual

Help pageTopics
Plant Phenotyping and Bayesian Statisticspcvr-package pcvr
subset helper function for use reading in large data, called in pcv.sub.readawkHelper
Function to help fulfill elements of the Bayesian Analysis Reporting Guidelines.barg
Function to visualize brms models similar to those made using growthSS outputs.brmPlot
Function to visualize brms survival models specified using growthSS.brmSurvPlot
Function to visualize hypotheses tested on brms models similar to those made using growthSS outputs.brmViolin
Helper function to check groups in data.checkGroups
Combine Draws From brms ModelscombineDraws
Bayesian testing using conjugate priors and method of moments for single or multi value traits.conjugate
Class 'conjugate' for output from the 'pcvr::conjugate' function.conjugate-class
Reduce phenotypes in longitudinal data to cumulative sums of phenotypes.cumulativePheno
Function for plotting iterations of posterior distributionsdistributionPlot
Ease of use wrapper function for fitting various growth models specified by growthSSfitGrowth
Ease of use brms wrapper function for fitting growth models specified by 'growthSS'fitGrowthbrms fitGrowthbrmsgam
Ease of use wrapper function for fitting growth models specified by 'growthSS'fitGrowthflexsurv
Ease of use lm wrapper function for fitting growth models specified by 'mvSS'fitGrowthlm
Ease of use mgcv wrapper function for fitting gams specified by 'growthSS'fitGrowthmgcvgam
Ease of use nlme wrapper function for fitting growth models specified by 'growthSS'fitGrowthnlme
Ease of use lme wrapper function for fitting gams specified by 'growthSS'fitGrowthnlmegam
Ease of use nlrq wrapper function for fitting growth models specified by 'growthSS'fitGrowthnlrq
Ease of use rq wrapper function for fitting gams specified by 'growthSS'fitGrowthnlrqgam
Ease of use nls wrapper function for fitting growth models specified by 'growthSS'fitGrowthnls
Ease of use lm wrapper function for fitting gams specified by 'growthSS'fitGrowthnlsgam
Ease of use rq wrapper function for fitting models specified by 'mvSS'fitGrowthrq
Ease of use wrapper function for fitting growth models specified by 'growthSS'fitGrowthsurvreg
Function to visualize 'flexsurv::flexsurvreg' models fit by 'fitGrowth'.flexsurvregPlot
Variance partitioning using Full Random Effects Modelsfrem
Helper function for visualizing differences in GAMs fit with 'mgcv::gam'gam_diff
Function to visualize models made by fitGrowth.growthPlot
Growth data simulating functiongrowthSim
Ease of use growth model helper function.growthSS
Multi Value Trait Aggregation functionmv_ag
Multi Value Trait simulating functionmvSim
Ease of use multi-value trait model helper function.mvSS
Visualizing igraph networksnet.plot
Function to visualize common 'nlme::nlme' growth models.nlmePlot
Function to visualize common 'quantreg::nlrq' growth models.nlrqPlot
Function to visualize common 'stats::nls' growth models.gamPlot lmPlot nlsPlot
Function to run a PCA, plot and optionally return the data with PCA coordinates and pca objectpcadf
Default theme for ggplots made by pcvr functions.pcv_theme
Earth Mover's Distance between spectral histogramspcv.emd pcv.euc
Make Joyplots for multi value trait plantCV datapcv.joyplot
Network analysis of a distance matrixpcv.net
Remove outliers from bellwether data using cook's distancepcv.outliers
Run Partial Least Squares Regression on spectral datapcv.plsr
Time conversion and plotting for bellwether datapcv.time
Read in lemnatech watering data from metadata.json filespcv.water
Class 'pcvrss' for models specified in 'pcvr'.pcvrss pcvrss-class
Plot a 'conjugate' object.plot.conjugate
Check priors used in ease of use brms functionsplotPrior
Plot Variable Influence on ProjectionplotVIP
Print a 'conjugate' object.print.conjugate
Print a 'conjugatesummary' object.print.conjugatesummary
Print a 'pcvrss' object.print.pcvrss
Print a 'pcvrsssummary' object.print.pcvrsssummary
Calculate pseudo water use efficiency from phenotype and watering datapwue
Read in plantCV csv output in wide or long formatread.pcv
Read in plantCV csv from bellwether phenotyper style experiments analyzed with plantCV versions <4.read.pcv.3
Calculate relative tolerance of some phenotype(s) relative to controlrelativeTolerance
Function to visualize 'quantreg::rq' general additive growth models.rqPlot
Show a model fit with pcvr in a ggplot layerstat_brms_model stat_growthss stat_lme_model stat_nlme_model stat_nlrq_model stat_nls_model
possible that ss is not a pcvrss object for compatibility with other brms models if "df" is part of it then work with that otherwise use general data. NOTE ggplot2:::Stat$compute_layer can use the default from ggproto `make plot within a given panel of the ggplot (a facet)` this is mostly the same as the default ggproto compute_panel function, but it takes more named args and passes them to compute_group and avoids warning about individual/time columns. `make data out of model per a given aes-group, should only be 1 per panel` this is the heavily customized component which makes data for ribbons from the model and ss objects.statBrmsMod
leaving the same as statBrmsMod for now. NOTE I think this can stay the same from brms version `make data out of model per a given aes-group, should only be 1 per panel` this is the heavily customized component which makes data for ribbons from the model and ss objects.statNlsMod
Summarize a 'conjugate' object.summary.conjugate
Summarize a 'pcvrss' object.summary.pcvrss
Function to visualize 'survival::survreg' models fit by 'fitGrowth'.survregPlot
Hypothesis testing for fitGrowth models.testGrowth