Package index • pcvr

Bayesian Statistics

Functions for Bayesian statistics.

conjugate(): Bayesian testing using conjugate priors and method of moments for single or multi value traits.

growthSS(): Ease of use growth model helper function.

fitGrowth(): Ease of use wrapper function for fitting various growth models specified by growthSS

growthPlot(): Function to visualize models made by fitGrowth.

testGrowth(): Hypothesis testing for fitGrowth models.

barg(): Function to help fulfill elements of the Bayesian Analysis Reporting Guidelines.

combineDraws(): Combine Draws From brms Models

plotPrior(): Check priors used in ease of use brms functions

distributionPlot(): Function for plotting iterations of posterior distributions

brmViolin(): Function to visualize hypotheses tested on brms models similar to those made using growthSS outputs.

Modeling

Functions for Bayesian or Frequentist Longitudinal (and other) Modeling

growthSS(): Ease of use growth model helper function.

fitGrowth(): Ease of use wrapper function for fitting various growth models specified by growthSS

growthPlot(): Function to visualize models made by fitGrowth.

testGrowth(): Hypothesis testing for fitGrowth models.

Lemnatech System Support

Functions for use with Lemnatech style data.

bw.outliers(): Remove outliers from bellwether data using cook's distance

bw.time(): Time conversion and plotting for bellwether data

bw.water(): Read in lemnatech watering data from metadata.json files

pwue(): Calculate pseudo water use efficiency from phenotype and watering data

Single-Value Traits

Functions suited for use with single-value trait data (Height, Area, etc)

conjugate(): Bayesian testing using conjugate priors and method of moments for single or multi value traits.

growthSS(): Ease of use growth model helper function.

frem(): Variance partitioning using Full Random Effects Models

relativeTolerance(): Calculate relative tolerance of some phenotype(s) relative to control

cumulativePheno(): Reduce phenotypes in longitudinal data to cumulative sums of phenotypes.

Multi-Value Traits

Functions suited for use with multi-value trait data (spectral indices, colorspaces, CropReporter, etc)

conjugate(): Bayesian testing using conjugate priors and method of moments for single or multi value traits.

mv_ag(): Multi Value Trait Aggregation function

pcv.emd() pcv.euc(): Earth Mover's Distance between spectral histograms

pcv.joyplot(): Make Joyplots for multi value trait plantCV data

pcadf(): Function to run a PCA, plot and optionally return the data with PCA coordinates and pca object

mvSS(): Ease of use multi-value trait model helper function.

pcv.net(): Network analysis of a distance matrix

pcv.plsr(): Run Partial Least Squares Regression on spectral data

Reading PlantCV output

Functions for reading different formats of PlantCV output (note for PlantCV >= 4.1) data.table::fread or utils::read.csv are perfectly adequate.

read.pcv.3(): Read in plantCV csv from bellwether phenotyper style experiments analyzed with plantCV versions <4.

read.pcv(): Read in plantCV csv output in wide or long format