Infinite Mixtures of Infinite Factor Analysers

IMIFA v1.3.1 - (5th release [patch update]: 2017-07-07)

Bug Fixes

• Fixed bug preventing M(I)FA models from being treated as (I)FA models when range.G contains 1.
• Fixed bug preventing get_IMIFA_results from working properly when true labels are NOT supplied.

IMIFA v1.3.0 - (4th release [minor update]: 2017-06-22)

New Features

• Added options "constrained" & "single" to mcmc_IMIFA’s uni.type argument:
  as well as being either diagonal or isotropic (UUU / UUC), uniquenesses can now further be
  constrained across clusters (UCU / UCC), with appropriate warnings, defaults, checks,
  initialisations, computation of model choice penalties, and plotting behaviour in all 4 cases.
• mcmc_IMIFA gains the tune.zeta argument, a list of heat, lambda & target parameters, to invoke
  diminishing adaptation for tuning the uniform proposal to achieve a target acceptance rate when alpha
  is learned via Metropolis-Hastings when the Pitman-Yor Process prior is employed for the IM(I)FA models.

Improvements

• (I)FA models sped up by considering uniquenesses under 1-cluster models as "constrained" or "single",
  rather than previously "unconstrained" or "isotropic", utilising pre-computation and empty assignment.
• Previously hidden functions improved, exported and documented with examples:
  is.cols, Ledermann, Procrustes & shift_GA.
• is.posi_def gains make argument, merging it with previously hidden function .make_posdef:
  Thus the ‘nearest’ positive-(semi)definite matrix and the usual check can be returned in a single call.
• Sped-up sampling IM(I)FA labels, esp. when ‘active’ G falls to 1, or the dependent slice-sampler is used:
  log.like arg. removed from gumbel_max; function stands alone, now only stored log-likelihoods computed.
• psi argument added to sim_IMIFA_data to allow supplying true uniqueness parameter values directly.

Bug Fixes

• Used bw="SJ" everywhere density is invoked for plotting (bw="nrd0" is invoked if this fails).
• Fixed initialisation of uniquenesses for isotropic (I)FA models.
• Fixed parallel coordinates plot axes and labels for all isotropic uniquenesses plots.
• Fixed adaptation for MIFA/OMIFA/IMIFA models when all clusters simultaneously have zero factors.
• Fixed storage bug in IM(I)FA models when learn.d is TRUE but learn.alpha is FALSE.
• Fixed density plot for discount when mutation rate is too low (i.e. too many zeros).
• Fixed simulation of loadings matrices for empty MIFA/OMIFA/IMIFA clusters using byrow=TRUE:
  loop to simulate loadings matrices now generally faster also for all models.
• Fixed silly error re: way in which (I)FA models are treated as 1-cluster models to ensure they run:
  Related bug fixed for OM(I)FA/IM(I)FA models when starting number of clusters is actually supplied.

IMIFA v1.2.1 - (3rd release [patch update]: 2017-05-29)

Improvements

• Posterior mean scores can now also be plotted in the form of a heat map (previously loadings only).
  load.meth argument replaced by logical heat.map in plot.Results_IMIFA.
• mat2cols gains compare argument to yield common palettes/breaks for heat maps of multiple matrices:
  Associated plot_cols function also fixed, and now unhidden.
• Removed certain dependencies with faster personal code: e.g. Procrustes rotation now quicker:
  IMIFA no longer depends on the corpcor, gclus, MASS, matrixcalc, or MCMCpack libraries.

Bug Fixes

• Used par()$bg (i.e. default "white") for plotting zero-valued entries of similarity matrix.
• Range of data for labelling in heat_legend calculated correctly.
• mcmc_IMIFA’s verbose argument now governs printing of message & cat calls, but not stop or warning.
• Fixed storage and plotting of loadings, particularly when some but not all clusters have zero factors.
• Added NEWS.md to build.

IMIFA v1.2.0 - (2nd release [minor update]: 2017-05-09)

New Features

• Learning the Pitman-Yor discount & alpha parameters via Metropolis-Hastings now implemented.
  Plotting function’s param argument gains the option discount for posterior inference.
• Sped up simulating cluster labels from unnormalised log probabilities using the Gumbel-Max trick (Yellott, 1977):
  gumbel_max replaces earlier function to sample cluster labels and is now unhidden/exported/documented.
• Added new plot when plot.meth=GQ for OM(I)FA/IM(I)FA models depicting trace of #s of active/non-empty clusters.
• Added function Zsimilarity to summarise posterior clustering by the sampled labels with minimum
  squared distance to a sparse similarity matrix constructed by averaging the adjacency matrices:
  when optionally called inside get_IMIFA_results, the similarity matrix can be plotted via plot.meth="zlabels".

Improvements

• Metropolis-Hastings updates implemented for alpha when discount is non-zero, rather than usual Gibbs.
  Mutation rate monitored rather than acceptance rate for Metropolis-Hastings updates of discount parameter.
• Fixed calculation of # ‘free’ parameters for aic.mcmc & bic.mcmc criteria when uniquenesses are isotropic:
  PGMM_dfree, which calculates # ‘free’ parameters for finite factor analytic mixture models is exported/documented.
  This function is also used to add checks on the Dirichlet hyperparameter for OM(I)FA methods.
• DIC model selection criterion now also available for infinite factor models (previously finite only).
• G_priorDensity now better reflects discrete nature of the density, and plots for non-zero PY discount values.
• Posterior mean loadings heatmaps now also display a colour key legend via new function heat_legend.
• Avoided redundant simulation of stick-breaking/mixing proportions under both types of IM(I)FA slice sampler.
• Simulated (finite) mixing proportions w/ Gamma(alpha, 1) trick (Devroye 1986, p.594) instead of MCMCpack:rdirichlet:
  rDirichlet replaces earlier function to sample mixing proportions and is now unhidden/exported/documented.
• Deferred setting dimnames attributes in mcmc_IMIFA to get_IMIFA_results: lower memory burden/faster simulations.
• Jettisoned superfluous duplicate material in object outputted from get_IMIFA_results to reduce size/simplify access.
• IMFA/IMIFA trunc.G arg, the max allowable # active clusters, defaults to range.G and # active clusters now stored.
• Code sped up when active G=1 by not simulating labels for IM(I)FA models.
• Reduced chance of crash by exceeding memory capacity; score.switch defaults to FALSE if # models ran is large.

Bug Fixes

• 2^nd IM(I)FA label switching move sped up/properly weighted to ensure uniform sampling of neighbouring cluster pairs.
• Offline label switching square assignment correction now permutes properly.
• Fixed factor score trace plots by extracting indices of stored samples using Rfast::sort_unique and rotating properly.
• Fixed adding of rnorm columns to scores matrix during adaptation, esp. when widest loadings matrix grows/shrinks.
• Fixed initialisation (and upper limit) of number of clusters for OM(I)FA/IM(I)FA, esp. when N < P.
• Updates of DP/PY alpha parameter now correctly depend on current # non-empty rather than active clusters.
• Fixed density plots for parameters with bounded support, accounting for spike at zero for discount.
• Slightly rearranged order Gibbs updates take place, esp. to ensure means enter simulation of uniquenesses properly.
• Edited/robustified subsetting of large objects when storing mcmc_IMIFA output.
• Tightened controls for when certain parameters are not stored for posterior inference.
• Edited Ledermann upper bound stop(...) for finite factor models to warning(...).
• Geometric rather than arithmetic mean used to derive single rate hyperparameter for PPCA’s isotropic uniquenesses.
• Uniquenesses now stored correctly for all clustering methods.
• Indices of uncertain obs. returned (get_IMIFA_results)/printed (plot.Results_IMIFA) even when zlabels not supplied.
• Fixed behaviour of progress bar when verbose=FALSE.
• Fixed typos and expanded/clarified help documentation/vignette.

IMIFA v1.1.0 - (1st release: 2017-02-02)