Package index • inferno

Main functions

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

qPr(): Calculate quantiles

rPr(): Generate datapoints

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

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

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

learnbind(): Bind 3D arrays by first dimension

mcjoin(): Concatenate mcsample objects

mcsubset(): Eliminate samples from a 'learnt' object

rowcumsum(): Cumulative sum along first dimension

rowinvcumsum(): Inverse cumulative sum along first dimension

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

util_combineYX(): Calculate probabilities, quantiles, etc, for all Y and X combinations

util_denorm(): Utility function to avoid finite-precision accuracys

util_joinPtraces(): Join '____tempPtraces-' files

util_learntvar2sd(): Convert learnt with R/C/Dvar to learnt with R/C/Dsd

util_lprobsargsyx(): Prepare arguments for util_lprobsyx from data

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

util_lprobsmi(): Calculate pairs of log-probabilities for mutualinfo()

util_prepPcheckpoints(): Format datapoints for testing of MCMC progress

util_qYXcont(): Calculate quantiles for continuous Y by bisection

util_qYXdiscr(): Calculate quantiles for discrete Y by bisection

vtransform(): Transforms variates to different representations

workerfun(): Worker function called by learn()