Infinite Mixtures of Infinite Factor Analysers
IMIFA v2.2.0 - (18th release [minor update]: 2023-12-12)
New Features
get_IMIFA_results
gains the arg. adapt
, allowing automatic, post-hoc truncation of
redundant factors in cases where mcmc_IMIFA
was called with adapt=FALSE
only
(provided relevant parameters were stored) for the "IFA"
, "MIFA"
, "OMIFA"
, & "IMIFA"
methods.
mgpControl
gains the active.crit
arg. to allow the criterion for determining the number of
active factors of Schiavon & Canale (2020) to be used (for "IFA"
models only); this is available
for both mcmc_IMIFA
with adapt=TRUE
directly and the aforementioned post-hoc adaptation using
get_IMIFA_results
, though the old criterion of Bhattacharya & Dunson (2011), active.crit="BD"
,
remains the default for all infinite factor models in each case. See documentation for details.
Improvements, Bug Fixes, & Miscellaneous Edits
- Models with
range.Q=0
now work again for the "FA"
, "MFA"
, "OMFA"
, & "IMFA"
methods.
(with thanks to @abcoxyzide for flagging the issue)
- The
mgpControl
arg. delta0g
now also governs beta.d1
, beta.d2
,
& sigma.hyper
, in addition to alpha.d1
& alpha.d2
.
- Improved documentation & checks related to the
Ledermann
bound + added various references to,
& warnings for, the stricter Q <= floor((P - 1)/2)
restriction throughout the package.
- Minor fixes for
"MFA"
/"MIFA"
models when mu0g
, psi0g
, &/or delta0g
is TRUE
, particularly when length(range.G) > 1
.
- Minor speed-up to
G_priorDensity
when discount
is non-zero.
- Extensive edits to avoid overheads introduced in
matrixStats (>= 1.0.0)
+ related minor speed-ups.
- Now using newer
CITATION
commands & updated License: GPL (>= 3)
.
IMIFA v2.1.10 - (17th release [patch update]: 2022-12-19)
Improvements, Bug Fixes, & Miscellaneous Edits
- Minor fix to adaptive Gibbs sampler for clusters with zero factors.
- Minor speed-ups to
Procrustes
when translate
&/or dilate
are TRUE
.
- Minor speed-ups to internal Cholesky decompositions in rare failure cases.
- Cosmetic changes to
param="alpha"
& param="discount"
plots.
- Minor speed-ups, documentation clarifications, & examples edits.
IMIFA v2.1.9 - (16th release [patch update]: 2022-08-12)
Improvements, Bug Fixes, & Miscellaneous Edits
storeControl
gains the update.mu
arg. to optionally circumvent updates of the
mean parameters to speed-up special case of (I)FA models with centered data.
- Minor fix to
param="means"
plots for uncentered (I)FA results.
- Minor fixes to account for (rare) uncentered data problems in means updates also.
- Minor fix to rare cases where Cholesky decompositions fail.
- Minor tidy-ups related to
exchange=TRUE
from previous update.
- Minor documentation edits for CRAN compliance.
IMIFA v2.1.8 - (15th release [patch update]: 2021-12-19)
Improvements, Bug Fixes, & Miscellaneous Edits
- Slight modifications to adaptive Gibbs sampling for all infinite factor methods:
- Adaptation now occurs before related parameter updates: cleaner, slightly faster code.
- Fixes rare bug re: storing factor scores when there are empty components.
- Associated new default behaviour(s) for
mgpControl
arg. start.AGS
.
bnpControl
gains the args. thresh
& exchange
, implementing the exchangeable/thresholded
slice sampler of Fall & Barat (2014): these are experimental features (both args. default to FALSE
).
- Fixed posterior predictive checking bug in
get_IMIFA_results
for
models for univariate data where some components have zero factors.
- Minor IM(I)FA speed-ups to updates of DP concentration parameter alpha.
sapply
replaced with vapply
, with other negligible speed-ups.
IMIFA v2.1.7 - (14th release [patch update]: 2021-10-07)
Improvements, Bug Fixes, & Miscellaneous Edits
mgpControl
gains the arg. truncated
(defaults to FALSE
):
- Allows version of MGP prior with gamma distributions left-truncated at 1
to be used for the column shrinkage parameters beyond the first column:
this has some more desirable shrinkage properties, at the expense of longer run times.
- Related function
rltrgamma
to draw from left-truncated gamma distributions provided.
exp_ltrgamma
for computing expectations of such distributions also provided, and used
internally by MGP_check
when its own new truncated
arg. is TRUE
(default: FALSE
).
- See
?ltrgamma
for further details on rltrgamma
and exp_ltrgamma
.
- Minor speed-ups to simulation of component mean parameters.
- Major speed-up to simulation of factor loadings parameters (especially when Q=1).
- Major speed-up to simulation of factor scores when Q=1.
- Minor speed-ups to simulation of means and loadings from priors for empty components.
- Minor fixes to adaptive Gibbs sampler for MIFA models when
delta0g=TRUE
.
- Improved checks on
range.G
& range.Q
in mcmc_IMIFA
.
- Minor fixes to returned attributes from
MGP_check
when invoked in vectorised fashion.
- Minor vignette styling edits and documentation clarifications.
IMIFA v2.1.6 - (13th release [patch update]: 2021-05-24)
Bug Fixes & Miscellaneous Edits
- Fixed breaking bugs associated with IM(I)FA slice samplers introduced in previous update.
G_calibrate
function exported to augment existing G_expected
& G_variance
functions.
G_variance
now computed more accurately and efficiently for the alpha=0
case.
- Major speed-up to
G_expected
for the alpha=0
case.
- Minor speed-ups to simulation of local/column/cluster shrinkage parameters + scores & loadings.
- Minor speed-up to
G_priorDensity
for non-zero discount
.
- Minor speed-up to
psi_hyper
.
IMIFA v2.1.5 - (12th release [patch update]: 2020-12-29)
Bug Fixes & Miscellaneous Edits
- Fixed
mcmc_IMIFA
initialisation issues for univariate data sets.
error.metrics=TRUE
now works for univariate data sets in get_IMIFA_results
.
- Slight speed-ups to slice samplers for IM(I)FA methods.
- Prettier axis labels for first two plots produced by
plot.meth="zlabels"
.
- Added ORCID iDs to DESCRIPTION.
- Minor CRAN compliance edits to the vignette.
IMIFA v2.1.4 - (11th release [patch update]: 2020-11-18)
Bug Fixes & Miscellaneous Edits
- Stricter checking of permissible
alpha
values in the special case of negative discount
.
- Fixes when
plot.meth="density"
and param="alpha"
for fixed positive discount
.
- Cosmetic changes to
G_priorDensity
plots.
- Ensured
matrixStats (>= 0.53.1)
and mclust (>= 5.4)
in Imports:
.
- Ensured
gmp (>= 0.5-4)
in Suggests:
.
- Package startup message now checks if newer version of package is available from CRAN.
- Minor documentation & examples edits (esp.
mat2cols
).
- Replaced dependency on
viridis
with viridisLite
.
- Updated citation info after publication in Bayesian Analysis.
- Updated maintainer e-mail address.
IMIFA v2.1.3 - (10th release [patch update]: 2020-05-12)
Bug Fixes & Miscellaneous Edits
- Maintenance release for compatibility with R 4.0.0 - minor edits.
- Improved handling of suggested packages
Rmpfr
& gmp
in G_expected
, G_variance
, & G_priorDensity
.
summary.Results_IMIFA
gains the printing-related argument MAP=TRUE
.
- Edited printed details when
plot.meth="zlabels"
with unsupplied zlabels
.
- Minor fixes for fixed negative
discount
(an experimental feature).
- Minor speed-up to
Procrustes
when dilate=TRUE
(never used internally).
- Minor efficiency gains in slice samplers for IM(I)FA methods.
- Documentation, vignette, examples, and references improvements.
IMIFA v2.1.2 - (9th release [patch update]: 2020-03-30)
Bug Fixes
- Fixes and speed-ups to MGP updates and adaptive Gibbs sampler for IMIFA/OMIFA/MIFA models:
- Fixes and speed-ups to MGP parameter updates when some clusters have zero factors.
- Additional speed-ups to simulation of column-shrinkage parameters when some clusters are empty.
- Properly accounted for the cluster-shrinkage parameters when the number of factors increases.
- Minor bug fixes for padding scores when the maximum number of factors increases.
- Variable-specific communalities (
x$Error$Var.Exps
) now returned by get_IMIFA_results
in addition
to proportion of explained variance per cluster (x$Error$Clust.Exps
; previously x$Error$Var.Exps
).
G_expected
& G_variance
gain the arg. MPFR
to control use of suggested packages.
- Minor speed-up to
rDirichlet
for the symmetric uniform case.
- Ensured compatibility with latest version of
Rfast
package (w/ minor speed-ups).
- Removed
methods
package from Suggests:
.
- Spell-checking of documentation and fixes to
donttest
examples.
IMIFA v2.1.1 - (8th release [patch update]: 2019-12-11)
Improvements
discount
can now be fixed at a negative value when learn.d=FALSE
,
provided alpha
is supplied as a positive integer multiple of abs(discount)
and learn.alpha=TRUE
.
- Other types of
norm
(beyond Frobenius) can now be specified, by passing the arg. type
,
via the ...
construct, for calculating the PPRE within get_IMIFA_results
.
- The breaks used to construct the bins for the PPRE calculation can now also be specified,
by passing the dbreaks
arg. through the ...
construct. This is an experimental feature; caution is advised.
- The settings
discount<0
& alpha=0
now accommodated by G_expected
, G_variance
, & G_priorDensity
:
G_expected
no longer requires the Rmpfr
or gmp
libraries for non-zero discount
unless alpha=0
.
mgpControl
gains the arg. forceQg
(defaults to FALSE
, i.e. retains old behaviour - see documentation for details).
G_priorDensity
gains type
arg. and now works again in non-vectorised form.
- Minor speed-up to
Procrustes
function and hence the identifiability corrections within get_IMIFA_results
.
- Minor speed-ups to
post_conf_mat
function and "parallel.coords"
plots.
- Updated citation info after online publication in Bayesian Analysis.
Bug fixes
- Fixes to
sim_IMIFA_data
to allow empty clusters and related fix for nonempty
arg. to get_IMIFA_results
.
- Fixed bug when initial
alpha
value is 0
when learn.alpha=TRUE
.
- Minor fix for handling optional args. to
mixfaControl
and plot.Results_IMIFA
functions.
- Admissible
rho
values in bnpControl
corrected to [0,1) from (0,1].
- Fixed bug related to Procrustes rotation of the factor scores for (I)/FA models in
get_IMIFA_results
.
- Fixed handling of colour palettes in
plot.Results_IMIFA
& G_priorDensity
.
- Documentation and warning message fixes.
- Anti-aliasing of vignette images.
IMIFA v2.1.0 - (7th release [minor update]: 2019-02-04)
New Features
mgpControl
gains the arguments cluster.shrink
and sigma.hyper
:
cluster.shrink
governs invocation of cluster shrinkage MGP hyperparameter for MIFA/OMIFA/IMIFA methods.
sigma.hyper
controls the gamma hyperprior on this parameter. The posterior mean is reported, where applicable.
- Full conditionals for loadings and local/column shrinkage MGP hyperparameters edited accordingly.
- Allowed the Dirichlet concentration parameter
alpha
to be learned via MH steps for the OM(I)FA models.
- Also allowed diminishing adaptation to tune the log-normal proposal to achieve a target acceptance rate.
- Thus
bnpControl
args. learn.alpha
, alpha.hyper
, zeta
, & tune.zeta
become relevant for OM(I)FA models.
- New posterior predictive model checking approach added to
get_IMIFA_results
(with associated plots):
Posterior Predictive Reconstruction Error (PPRE) compares bin counts of the original data with corresponding
counts for replicate draws from the posterior predictive distribution using a standardised Frobenius norm.
- Added new function
scores_MAP
to decompose factor scores summaries
from get_IMIFA_resuls
into submatrices corresponding to the MAP partition.
- Added new wrapper function
sim_IMIFA_model
to call sim_IMIFA_data
using
the estimated parameters from fitted Results_IMIFA
objects.
- New
get_IMIFA_results
arg. vari.rot
allows loadings templates to be varimax rotated,
prior to Procrustes rotation, for more interpretable solutions (defaults to FALSE
).
- New
plot.Results_IMIFA
argument common
governing plot.meth="means"
plots (details in documentation).
Improvements
- New hyperparameter/argument defaults:
sigma.mu
defaults to 1
s.t. the hypercovariance is the identity for the prior on the means;
old behaviour (using the diagonal of the sample covariance matrix) recoverable by specifying sigma.mu=NULL
.
prec.mu
defaults to 0.01
s.t. the prior on the cluster means is flat by default.
learn.d
defaults to TRUE
s.t. a PYP prior is assumed for IM(I)FA models by default.
alpha.hyper
now has a larger hyper-rate by default, to better encourage clustering.
alpha.d1
& alpha.d2
now set to 2.1
/3.1
rather than 2
/6
to discourage exponentially fast shrinkage.
z.init
now defaults to "hc"
: model-based agglomerative hierarchical clustering.
- Overhauled
psi_hyper
(details in documentation) for:
N <= P
data where the sample covariance matrix is not invertible.
type="isotropic"
uniquenesses.
- Args.
scores
& loadings
can now be supplied to sim_IMIFA_data
directly;
new arg. non.zero
controls the # effective factors (per column & cluster) when loadings
are instead simulated.
- Sped-up 2nd label-switching move for IM(I)FA models (accounting for empty clusters).
- Args. for
hc
can now be passed when init.z="mclust"
also
(previously only "hc"
), thus controlling how Mclust
is itself initialised.
- Allowed
criterion
to be passed via ...
in mixfaControl
to choose between
mclustBIC
/mclustICL
to determine optimum model to initialise with when
z.init="mclust"
& also sped-up mclust
initialisation in the process.
- Added
stop.AGS
arg. to mgpControl
: renamed adapt.at
to start.AGS
for consistency.
- Added
start.zeta
& stop.zeta
options to tune.zeta
argument in bnpControl
.
- Allowed user-supplied
breaks
in the plotting functions mat2cols
& heat_legend
.
- Initial cluster sizes are now shown in order to alert users to potentially bad starting values.
- Added utility function
pareto_scale()
.
Bug Fixes
- Fixed factor scores & error metrics issues in
get_IMIFA_results
for clustering methods:
- Fixed storage of scores for infinite factor methods - now corresponds to samples where the
largest cluster-specific number of factors is >=
the max of the modal estimates of the same
(previously samples where any cluster has >=
the corresponding modal estimate were used):
thus, valid samples for computing error metrics also fixed and Procrustes rotation also sped-up.
- Other Procrustes rotation fixes to account for label-switching.
- Other Procrustes rotation fixes specific to the IMFA/OMFA methods.
range.G
and trunc.G
defaults fixed, especially for small sample size settings.
- Slight label-switching fixes when
zlabels
are supplied to get_IMIFA_results
;
posterior confusion matrix, cluster sizes vector, and the sampled labels themselves effected.
- Prevented unnecessary Procrustes rotation for single-factor components, thus fixing some bugs.
- Fixed initialisation of uniquenesses to account for all four settings of
uni.type
.
- Allowed conditioning on iterations with all components populated for M(I)FA models in
get_IMIFA_results
.
- Accounted for 1-component IM(I)FA/OM(I)FA models in
get_IMIFA_results
.
- Fixed handling of empty components when simulating cluster labels from priors in
mcmc_IMIFA
& sim_IMIFA_data
.
- Ensured no. of factors
Q
cannot exceed no. of observations in the corresponding cluster in sim_IMIFA_data
.
- Slight speed-up to updating MGP hyperparameters in the presence of empty MIFA/OMIFA/IMIFA components.
- Slight speed-up to sampling cluster labels with slice indicators for IM(I)FA models.
- Explicitly allowed Pitman-Yor special case where
alpha=0
for IM(I)FA models;
added related controls on spike-and-slab prior for discount
when fixing alpha<=0
.
- Allowed full range of
hc
model types for initialisation purposes via ...
in mixfaControl
.
- Clarified
dimnames
of get_IMIFA_results
output in x$Loadings
& x$Scores
.
- Fixed storage switches & iteration indices to better account for
burnin=0
.
- Fixed plotting of exact zeros in posterior confusion matrix.
- Fixed plotting posterior mean loadings heatmap when one or more clusters have zero factors.
- Fixed plotting scores for (I)FA models due to bug in previous update, esp. with
zlabels
supplied.
- Fixed
show_IMIFA_digit
to better account for missing pixels &/or the data having been centered/scaled.
- Fixed simulation of
psi
when not supplied to sim_IMIFA_data
to IG rather than GA.
- Fixed bug preventing
Q
to be supplied to get_IMIFA_results
for infinite factor methods.
- Fixed y-axis labelling in uncertainty type plots when
plot.meth="zlabels"
.
- Small fixes to function
show_digit
.
- Better handling of tied model-selection criteria in
get_IMIFA_results
.
Procrustes
now works when X
has fewer columns than Xstar
.
- Minor cosmetic change for overplotting
scores
& loadings
in trace
& density
plots.
- Edited
Ledermann
and related warnings to account for case of isotropic uniquenesses.
- Tidied indentation/line-breaks for
cat
/message
/warning
calls for printing clarity.
- Corrected
IMIFA-package
help file (formerly just IMIFA
).
- Edited
CITATION
file and authorship.
IMIFA v2.0.0 - (6th release [major update]: 2018-05-01)
Major Changes
- Simplified
mcmc_IMIFA
by consolidating arguments using new helper functions (with defaults):
- Args. common to all factor-analytic mixture methods & MCMC settings supplied via
mixfaControl
.
- MGP & AGS args. supplied via
mgpControl
for infinite factor models.
- Pitman-Yor/Dirichlet Process args. supplied via
bnpControl
for infinite mixture models.
- Storage switch args. supplied via
storeControl
.
- New functions also inherit the old documentation for their arguments.
New Features
- Posterior predictive checking overhauled: now MSE, RMSE etc. between empirical & estimated covariance
matrices are computed for every retained iteration so uncertainty in these estimates can be quantified:
- Can be switched on/off via the
error.metrics
argument to get_IMIFA_results
.
- Can be visualised by supplying
plot.meth="errors"
to plot.Results_IMIFA
.
- For methods which achieve clustering, the ‘overall’ covariance matrix
is now properly computed from the cluster-specific covariance matrices.
- Same metrics also evaluated at posterior mean parameter estimates & for final sample where possible.
mixfaControl
gains the arg. prec.mu
to control the degree of flatness of the prior for the means.
- Posterior confusion matrix now returned (
get_IMIFA_results
) & visualisable (plot.Results_IMIFA
,
when plot.meth="zlabels"
), via new function post_conf_mat
, to further assess clustering uncertainty.
- Added new type of clustering uncertainty profile plot in
plot.Results_IMIFA
when plot.meth="zlabels"
.
- For convenience,
get_IMIFA_results
now also returns the last valid samples for parameters of interest,
after conditioning on the modal G & Q values and accounting for label switching and Procrustes rotation.
plot.Results_IMIFA
gains new arg. show.last
that replaces any instance of showing the posterior mean
with the last valid sample instead (i.e. when plot.meth="means"
or plot.meth="parallel.coords")
.
- Added ability to constrain mixing proportions across clusters using
equal.pro
argument for M(I)FA models:
Modified PGMM_dfree
accordingly and forced non-storage of mixing proportions when equal.pro
is TRUE
.
- All methods now work for univariate data also (with apt. edits to plots & uniqueness defaults etc.).
sim_IMIFA_data
also extended to work for univariate data, as well as sped-up.
Improvements
- Retired args.
nu
& nuplus1
to mgpControl
, replaced by ability to specify more general gamma prior,
via new phi.hyper
arg. specifying shape and rate - MGP_check
has also been modified accordingly.
Zsimilarity
sped-up via the comp.psm
& cltoSim
functions s.t. when # observations < 1000.
- Matrix of posterior cluster membership probabilities now returned by
get_IMIFA_results
.
- Modified AGS to better account for when the number of group-specific latent factors shrinks to zero.
psi.alpha
no longer needs to be strictly greater than 1, unless the default psi.beta
is invoked;
thus flatter inverse gamma priors can now be specified for the uniquenesses via mixfaControl
.
- Added “
hc
” option to z.init
to initialise allocations via hierarchical clustering (using mclust::hc
).
- Allowed optional args. for functions used to initialise allocations via
...
in mixfaControl
.
- Added
mu
argument to sim_IMIFA_data
to allow supplying true mean parameter values directly.
- Standard deviation of
aicm
/bicm
model selection criteria now computed and returned.
- Speed-ups due to new
Rfast
utility functions: colTabulate
& matrnorm
.
- Speed-ups due to utility functions from
matrixStats
, on which IMIFA
already depends.
- Slight improvements when
adapt=FALSE
for infinite factor models with fixed high truncation level.
- Misclassified observations now highlighted in 1st type of uncertainty plot in
Plot.Results_IMIFA
,
when plot.meth="zlabels"
and the true zlabels
are supplied.
mixfaControl
gains arg. drop0sd
to control removal of zero-variance features (defaults to TRUE
).
heat_legend
gains cex.lab
argument to control magnification of legend text.
mat2cols
gains the transparency
argument.
- Edited
PGMM_dfree
to include the 4 extra models from the EPGMM family.
Bug Fixes
- Supplying
zlabels
to get_IMIFA_results
will now match the cluster labels and parameters to
the true labels even if there is a mismatch between the number of clusters in both.
- Similarly, supplying
zlabels
to plot.Results_IMIFA
when plot.meth="zlabels"
no longer does
any matching when printing performance metrics to the screen - previously this caused confusion
as associated parameters were not also permuted as they are within get_IMIFA_results
: now
plot(get_IMIFA_results(sim), plot.meth="zlabels", zlabels=z)
gives different results from
plot(get_IMIFA_results(sim, zlabels=z), plot.meth="zlabels")
as only the latter will permute.
- Accounted for errors in covariance matrix when deriving default
sigma.mu
& psi.beta
values.
- Accounted for missing empirical covariance entries within
get_IMIFA_results
.
- Fixed model selection in
get_IMIFA_results
for IMFA/OMFA models when range.Q
is a range.
- Fixed calculation of
aicm
, bicm
and dic
criteria: all results remain the same.
- Fixed support of Ga(a, b) prior on
alpha
when discount
is being learned.
- Fixed bug preventing
uni.prior="isotropic"
when uni.type
is (un)constrained
.
- Fixed treatment of exact zeros when plotting average clustering similarity matrix.
- Fixed tiny bug when neither centering nor scaling (of any kind) are applied to data within
mcmc_IMIFA
.
- Fixed plotting of posterior mean scores when one or more clusters are empty.
- Fixed bug with default plotting palette for data sets with >1024 variables.
- Fixed bug with label switching permutations in
get_IMIFA_results
when there are empty clusters.
- Fixed
print
and summary
functions for objects of class IMIFA
and Results_IMIFA
.
- Fixed calculating posterior mean
zeta
when adaptively targeting alpha
’s optimal MH acceptance rate.
- Allowed
alpha
be tiny for (O)M(I)FA models (provided z.init != "priors"
for overfitted models).
- Normalised mixing proportions in
get_IMIFA_results
when conditioning on G
for IM(I)FA/OM(I)FA models.
- New controls/warnings for excessively small Gamma hyperparemeters for uniqueness/local shrinkage priors.
- Clarified recommendation in
MGP_check
that alpha.d2
be moderately large relative to alpha.d1
.
- Ensured
sigma.mu
hyperparameter arg. is always coerced to diagonal entries of a covariance matrix.
- Transparency default in
plot.Results_IMIFA
now depends on device’s support of semi-transparency.
- Replaced certain instances of
is.list(x)
with inherits(x, "list")
for stricter checking.
- Added
check.margin=FALSE
to calls to sweep
.
Ledermann
, MGP_check
, & PGMM_dfree
are now properly vectorised.
Miscellaneous Edits
- Added
USPSdigits
data set (training and test),
with associated utility functions show_digit
and show_IMIFA_digit
.
- Optimised compression of
olive
, coffee
and vignette data and used LazyData: true
.
- Added
call.=FALSE
to stop()
messages and immediate.=TRUE
to certain warning()
calls.
- Removed dependency on
adrop
, e1071
, graphics
, grDevices
, plotrix
, stats
& utils
libraries.
- Reduced dependency on
Rfast
w/ own version of standardise
.
- Added utility function
IMIFA_news
for accessing this NEWS
file.
- Added
CITATION
file.
- Extensively improved package documentation:
- Added
Collate:
field to DESCRIPTION
file.
- Added line-breaks to
usage
sections of multi-argument functions.
- Consolidated help files for
G_expected
& G_variance
.
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.
- Spike-and-slab prior specified for
discount
: size of spike controlled by arg. kappa
.
- 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.
- Restored the IMFA/IMIFA arg.
trunc.G
, the max allowable # active clusters, 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
- 2nd 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)