Hardened proactive C cleanup paths by aligning LAPACK helper out-of-memory
cleanup with the serial package, clearing extended nearest-neighbor alias
state in the shared estimator cleanup helper, routing selected
bandwidth-constructor allocation and unsupported-method failures through
existing cleanup labels, and guarding large np_kernelsum() allocation-size
products before calling the legacy alloc_vecd(int) allocator.
Added nomad = "auto" for local-polynomial degree searches, preserving the
serial package policy while keeping MPI autodispatch and NOMAD shadow
protocols explicit. Small one-dimensional degree lattices use exhaustive
Powell-style search; larger or explicitly requested NOMAD surfaces continue
to use NOMAD.
Repaired npRmpi fit-wrapper NOMAD guards after normalized NOMAD control
handling so nomad = TRUE and nomad = "auto" routes stay on the intended
local/native path rather than being accidentally autodispatched.
Bandwidth and fit summaries now report cumulative search diagnostics more clearly. NOMAD cache output distinguishes repeated point lookups avoided by NOMAD from true objective computations; Powell summaries expose repeated objective lookups avoided by the package-side cache; hybrid NOMAD+Powell and exhaustive Powell timing labels are reported consistently.
Base-graphics plot scaling and legends have been hardened for multi-panel
displays. Plots now honor active mfrow/cex behavior more consistently,
use role-appropriate legend sizes, and draw factor legends with point glyphs
matching the plotted estimates.
Fixed-bandwidth bias-corrected bootstrap plot intervals have been reworked across the supported serial-equivalent and MPI-aware plot families. Bias-corrected centers and intervals now share a common centering contract for regression, unconditional density and distribution, conditional density and distribution, single-index, partially linear, and smooth-coefficient plots where supported.
Pair/block/geometric bootstrap intervals in regression-style routes now use
smooth-bootstrap bias correction when center = "bias-corrected" is
requested; wild-bootstrap regression intervals retain the standard
wild-bootstrap correction. Density and distribution routes use
perturbation-based smooth-bootstrap bias correction. Gaussian, uniform, and
second-order Epanechnikov perturbation kernels are supported; higher-order
signed perturbation kernels fail closed.
Bias-corrected plot support now covers mixed-data unconditional density and
distribution, mixed-data conditional density and distribution, and
conditional gradient displays. Non-fixed/adaptive/generalized bandwidth
bias correction and empirically unsupported npqreg bias correction remain
fail-closed with explicit messages.
Bias-corrected plot payloads returned by output = "data" and
output = "both" now consistently expose fitted values, bias-corrected
values, gradients, gradient bias corrections, and interval payloads with the
same centering contract used for rendering.
Derivative-order validation has been tightened across plot/gradient routes so unsupported derivative requests fail early or are represented consistently rather than silently plotting a lower-order derivative.
Single-index formula dispatch with explicit bandwidths has been repaired in MPI-aware routes, and single-index bias-corrected plot centers, output payloads, and legends have been tightened.
The native loadNamespace("crs") call construction used by CRS-backed
native search routes is now protected, resolving the RCHK protection finding
without changing the native NOMAD search contract.
Added MPI-aware nplsqreg()/nplsqregbw() support for location-scale
quantile regression, including formula/data and bandwidth-object workflows,
scalar/vector tau, prediction, residual extraction, summaries, and plot
routes built on the shared quantile plotting engine.
Supported MPI MADS/NOMAD-backed bandwidth-search routes now use the final
native crs NOMAD C API rather than the retired legacy snomadr()
fallback. The runtime dependency on crs is now declared in Imports,
while LinkingTo remains for the native header.
Native NOMAD routes now preserve progress best-record reporting, expose cache/evaluation diagnostics, honor explicit start and option controls, and reject unsupported or indeterminate cache-off settings before solver entry. Inadmissible GLP degree candidates are guarded before expensive evaluator work in serial-equivalent and MPI-dispatched routes.
npindexbw(..., method = "ichimura", regtype = c("ll", "lp")) now reuses
the established local-polynomial regression objective evaluator, and MPI
autodispatch uses a rank-0-driven objective service for the fixed-degree and
NOMAD degree-search Ichimura local-polynomial routes. Focused sentinel runs
preserved payloads while restoring useful scaling for the formerly flat
local-linear and local-polynomial single-index rows.
MPI fanout coverage has been extended for computationally heavy bootstrap workloads in specification, dependence, distribution-equality, quantile, and symmetry tests, and plot-bootstrap RNG streams now restore the serial-equivalent final state after MPI fanout.
The shipped npplreg attach-mode demo now explicitly finalizes the master
rank after successful attach shutdown, hardening release-sentinel teardown
without changing estimator or runtime defaults.
MPI auto-dispatch for nplsqreg() now materializes named method-level
... arguments before worker fanout, preserving user-supplied scale and
option values that arrive through S3 ..n placeholders.
options(np.tree = "auto") is now the default tree mode. In auto mode,
continuous kd-tree routes are enabled only for bounded-support continuous
kernels ("epanechnikov" and "uniform"); np.tree = TRUE remains the
explicit force-on override and np.tree = FALSE remains the force-off
diagnostic path.
Powell bandwidth searches now expose package-side repeated-candidate
objective caching through options(np.objective.cache = TRUE/FALSE). The
cache remains enabled by default and is scoped to one bandwidth solve, so it
can reuse exact candidates across Powell restarts without carrying state
across datasets or later calls. Continuous-only generalized/adaptive
nearest-neighbor routes also retain their integer nearest-neighbor objective
cache under the same switch. The option is synchronized to MPI workers in
autodispatch sessions; NOMAD solver caching and extended-NN distance reuse
remain separate mechanisms.
Continuous large-bandwidth shortcut evaluations can now be disabled with
options(np.largeh = FALSE), and discrete near-upper-bandwidth shortcut
evaluations can now be disabled with options(np.largelambda = FALSE).
Both remain enabled by default and are synchronized to MPI workers in
autodispatch sessions. These switches are intended for diagnostic timing and
reproducibility studies that need to separate tree effects from
large-bandwidth and large-lambda fast paths without changing the canonical
dense/tree objective machinery.
Local-polynomial regression cross-validation now uses a leaner hot
symmetric weighted-sum loop. Fixed-bandwidth npregbw(..., regtype = "lp", bwmethod = "cv.ls") objective probes in active MPI sessions match serial
np objective values to numerical precision while substantially reducing
local-polynomial CV evaluation time.
Shared weighted outer-product accumulation in npksum() now uses a guarded
BLAS dgemm route when the operation is dense, non-permuted, and
memory-bounded. Focused fixed-bandwidth probes preserve serial/MPI objective
parity while substantially accelerating high-basis local-polynomial
regression and smooth-coefficient objective rows; small and scalar routes
remain on the established loop path.
Unconditional density least-squares cross-validation now uses a leaner
fixed-bandwidth Gaussian convolution loop. Fixed-bandwidth
npudensbw(..., bwmethod = "cv.ls") objective probes preserve objective
values exactly in the focused validation rows while materially reducing the
convolution portion of the objective calculation. Conditional-density
least-squares objective probes inherit the same fixed-bandwidth Gaussian
convolution improvement.
Non-Gaussian scalar-bandwidth convolution helpers now hoist the response bandwidth power outside the inner loop, improving fixed-bandwidth least-squares density cross-validation with compact-support kernels while preserving objective values exactly in focused probes.
Continuous-kernel vector helpers now reuse the loop-invariant signed inverse bandwidth scale inside their inner loops. Focused density, conditional density, and regression objective probes preserve serial/MPI objective parity while reducing repeated scaling work in shared C hot paths.
Conditional density and conditional distribution least-squares cross-validation now use a size-aware row-block policy for local-polynomial objective evaluation. The accepted route keeps the bounded-quadrature cap unchanged, bounds transient memory by sample size, and preserves objective values to numerical precision while materially reducing evaluator overhead for fixed-bandwidth CVLS probes in serial and MPI sessions.
Local-polynomial conditional density maximum-likelihood cross-validation now
uses the same bounded-memory block machinery for fixed and generalized
nearest-neighbor bandwidths. Focused npcdensbw(..., bwmethod = "cv.ml", regtype = "lp") probes preserve objective values and selected bandwidths to
numerical precision in serial and MPI sessions while reducing objective and
full-search runtime.
Large-sample categorical-only regression now uses the MPI-safe
profile-compressed route under options(np.categorical.compress = TRUE),
which is enabled by default. This categorical route is independent of
options(np.tree). Repeated predictor profiles are compressed before
bandwidth search, fitting, prediction/evaluation, standard errors,
hat-helper use, and plot bootstrap helpers, preserving the established
dense-route numerical contract while reducing repeated work.
Categorical-only unconditional density routes now use the same
profile-compression idea when options(np.categorical.compress = TRUE) is
enabled. The fixed-bandwidth fit/evaluation route preserves dense-route
fitted/evaluation values while avoiding repeated computation over identical
categorical profiles, and the bandwidth-search route now uses the same
compressed support representation for all-categorical data. As with other
flat categorical search surfaces, selected smoothing parameters may drift by
optimizer-path amounts while preserving the objective scale. Very fast
compressed routes may remain overhead-floor limited, so MPI acceleration is
most useful once the uncompressed work would be genuinely long-running.
Categorical-only conditional density and conditional distribution bandwidth
searches now honor options(np.categorical.compress = TRUE). The promoted
route preserves the objective value to numerical precision while allowing
harmless optimizer-path drift in selected smoothing parameters, especially
near upper-bound or large-bandwidth regions where the objective is flat.
Ordered-only unconditional distribution bandwidth search and fit/evaluation
routes also use profile compression when
options(np.categorical.compress = TRUE) is enabled. The bandwidth-search
route preserves the objective value to numerical precision while allowing
harmless optimizer-path drift in selected smoothing parameters; fitted
distribution values and standard errors are preserved while avoiding repeated
computation over identical ordered profiles.
Fixed-bandwidth local-constant npscoef() fits now use categorical-profile
compression when all Z variables are categorical and
options(np.categorical.compress = TRUE) is enabled. The route preserves
fitted means, coefficient surfaces, asymptotic mean standard errors, and
coefficient/gradient standard errors for training and evaluation fits while
avoiding repeated work over duplicate Z profiles. The corresponding
npscoefhat(output = "apply") path and count-based plot-bootstrap helper
use the same profile compression without changing the explicit full-matrix
output = "matrix" contract.
Internal categorical-profile and large-bandwidth caches are now cleared at
the relevant top-level density, distribution, conditional-density,
conditional-distribution, and regression cleanup points. These caches are
keyed by call-local row pointers, so clearing them per .Call prevents stale
same-process state from leaking across unrelated data sets or MPI dispatch
modes.
Fixed npcdens() and npcdist() formula calls with explicit numeric
smoothing parameters, such as npcdist(y ~ x, data = dat, bws = c(.25,.25)),
so npRmpi preserves the established formula-to-bandwidth-object rewrite
before MPI autodispatch.
Hardened the npudist() formula route so formula calls are handled before
MPI autodispatch.
npplreg() now activates the already validated categorical regression
compression path for its internal all-categorical Z regressions when
options(np.categorical.compress = TRUE) is enabled, without requiring users
to request continuous kd-tree acceleration through options(np.tree).
Formula variables whose names contain dots, such as y.irr ~ x, are no
longer mistaken for the formula wildcard . in conditional density and
conditional distribution bandwidth routes. The conditional-density bandwidth
formula route also now expands the actual wildcard form y ~ . using the
supplied data frame, matching the conditional-distribution route.
Fixed MPI conditional-density and conditional-distribution NOMAD degree-search
routes so Powell refinement and promoted wrappers such as npconmode() reach
the intended bandwidth-object construction path rather than the pre-search
autodispatch preflight used by non-degree-search routes.
npqreg() is now a fully fledged MPI-aware quantile-regression front
end. It supports the formula/data workflow, internally computes
npcdistbw() bandwidths when a bandwidth object is not supplied,
accepts scalar or vector tau, reuses selected bandwidths for
additional quantiles in plot(), and exposes the usual S3 surface:
fitted(), predict(), predict(..., se.fit=TRUE), se(),
gradients(), summary(), print(), quantile(), and plot().
npqreg() prediction now honors the standard newdata workflow while
preserving native exdat precedence for compatibility with existing
npRmpi call surfaces. Formula-based prediction validates that new
data contain the required right-hand-side variables.
npqreg() plotting has been expanded for vector quantiles,
level/gradient displays, ordered predictors, user-specified legends,
and object-fed plotting of additional tau values without recomputing
cross-validation. The fixed-bandwidth gradient path now uses the
MPI-aware helper route.
npconmode() is now a first-class conditional-mode estimator. It
supports formula/data and bandwidth-object workflows, forwards
bandwidth-selection options to npcdensbw(), propagates local
polynomial and NOMAD metadata, and exposes fitted(), predict(),
summary(), print(), gradients(), and plot() methods.
npconmode() now supports optional class-probability matrices and
level-specific probability gradients. For non-local-constant fits,
probabilities are normalized to be non-negative and to sum to one
across the discrete response support before modal classification.
npconmode() now fails early for non-categorical responses and
validates formula-based newdata against the original right-hand-side
variables.
npconmode() plotting now supports object-fed class-probability slices
and two-dimensional probability surfaces, optional rgl rendering, and
probability-level asymptotic intervals where defined. Surface bootstrap
intervals for class probabilities remain intentionally deferred.
npcopula() is now a first-class copula estimator. It supports
formula/data and bandwidth-object workflows, automatic two-dimensional
probability grids, explicit u evaluation grids, and ordinary
extractable object components including $bws.
npcopula() now provides fitted(), predict(), predict(..., se.fit=TRUE), se(), summary(), print(), as.data.frame(), and
richer plot() methods. Plotting supports base persp, image, and
optional rgl rendering, with asymptotic and MPI-fanned bootstrap
intervals for copula surfaces where defined.
npcopula() explicit-grid evaluation now uses the direct estimator
route, preserving numerical results while avoiding the severe runtime
growth of the previous expanded-grid path when users request larger
probability grids.
The automatic local-polynomial NOMAD controls have been split into
explicit restart toggles: powell.remin for Powell restarts and
nomad.remin for the second NOMAD hot start. This preserves the
Powell Numerical Recipes restart default while allowing NOMAD hot
starts to be controlled separately.
Deprecated legacy remin remains accepted by npregbw() and npreg()
with a warning and is mapped to the modern powell.remin/nomad.remin
controls where appropriate, preserving downstream compatibility while
documenting the new spelling.
Hat-operator helpers now support an additional constraint-oriented output route for objects needed by shape-constrained quadratic programming workflows, avoiding reimplementation of local-polynomial hat-matrix construction in user examples.
Local-polynomial derivative support has been broadened across the
conditional estimator family. npreg(), npcdens(), and npcdist()
now honor gradient.order more consistently for fitted, evaluated,
predicted, and plotted objects when the selected polynomial degree is
high enough, including vector derivative orders over continuous
predictors and tensor/additive/Bernstein local-polynomial bases. The
MPI implementation dispatches the corresponding conditional hat-apply
helper work across the active worker pool where applicable.
Core and semiparametric S3 prediction paths have been hardened around
newdata, native evaluation-argument precedence, formula RHS
validation, and se.fit handling while preserving npRmpi route
independence.
Front-end/bandwidth argument hygiene has been tightened so
estimator-only controls such as proper are not forwarded into
bandwidth selectors that do not accept them.
MPI lifecycle and plotting routes received additional hardening,
including soft npRmpi.quit() behavior, local object-fed plot
computation where required, and explicit fanout of applicable
bootstrap workloads.
Documentation has been refreshed for the promoted npqreg(),
npconmode(), and npcopula() workflows, including the
local-polynomial NOMAD route, probability/gradient outputs, plot
controls, and examples that use the streamlined interfaces.
The pre-release validation suite was expanded with focused hostile argument tests, S3 contract tests, installed/tarball proof scripts, route-aware MPI probes, and serial/MPI parity checks for the newly promoted estimator families.
The default multistart cap for bandwidth selection now follows
min(2, p) across the mirrored estimator families, replacing the
older min(5, p) cap. This includes automatic LP degree-search calls
when search.engine="nomad" or "nomad+powell" and nmulti is not
supplied explicitly.
The univariate boundary density helper npuniden.boundary() now
defaults to nmulti=1.
The empirical studies supporting this mirror change are documented in
np-master/benchmarks/validation/, with a summary note kept in this
repository's benchmarks/validation/ folder.
LP-capable front ends now accept nomad=TRUE as a documented
convenience preset for the recommended automatic NOMAD
local-polynomial route, mirroring the serial package defaults and
help-page guidance.