Package index • inferno

Main functions

E(): Calculate means and standard deviations

flexiplot(): Plot numeric or character values

hist(<probability>): Plot the variability of an object of class "probability" as a histogram

write.csvi() read.csvi(): Write and read data in inferno

learn(): Monte Carlo computation of posterior probability distribution

metadatatemplate(): Metadata and helper function for metadata

mutualinfo(): Calculate mutual information between groups of joint variates

plot(<probability>): Plot an object of class "probability"

plotFsamples(): Plot one-dimensional posterior probabilities

plotquantiles(): Plot pairs of quantiles

Pr(): Calculate posterior probabilities

rPr(): Generate datapoints

subset(<probability>): Subset variates of an object of class probability

vrtgrid(): Create a grid of values for a variate

oldtailPr(): (Obsolete) Calculate cumulative posterior probabilities

oldPr(): (Obsolete) Calculate posterior probabilities

Internal functions

For developers.

buildauxmetadata(): Build preliminary metadata flie

createQfunction(): Calculate and save transformation function for ordinal variates

fftNGS(): Find optimal FFT size

funAC(): Compute autocovariance

funESS3(): Compute ESS

funESSLD(): Calculate MC effective sample size using LaplacesDemon's algorithm

funMCEI(): Calculate quantile width through batches

funMCEQ(): Calculate credibility quantiles on estimated quantile

funMCSELD(): Calculate MC standard error using LaplacesDemon's batch means

inferno inferno-package: inferno: Inference in R with Bayesian nonparametrics

util_Pcheckpoints(): Calculate joint frequencies for checkpoints in learn()

util_lprob(): Calculate collection of log-probabilities for different components and samples

util_lprobs(): Calculate collection of log-probabilities for different components and samples

util_lprobsargs(): Prepare arguments for util_lprobs from data

util_lprobsargsmi(): Prepare arguments for util_lprobs from data

util_ltailprob(): Calculate collection of log-probabilities for different components and samples

util_prepPcheckpoints(): Format datapoints for testing of MCMC progress

vtransform(): Transforms variates to different representations