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Changelog

vasicekreg 1.3.0 (2026-09-20)

Datasets

  • Added please_microbiome, a long-format data frame of genus-level relative abundances from the pediatric study of Lewis et al. (2015), reconstructed from the public chvlyl/PLEASE repository following the filtering and recoding conventions of the ZIBR R package (Chen and Li, 2016, https://CRAN.R-project.org/package=ZIBR). The data cover 3186 post-baseline observations from 59 subjects (47 anti-TNF, 12 EEN) and 18 bacterial genera, with the week-0 abundance of each genus stored as a subject-level covariate. The dataset is documented in R/please_microbiome.R and reproduced by data-raw/please_microbiome.R.

Longitudinal two-part mixed models

  • Reject simultaneous formula and legacy arguments for either component or for the subject grouping variable, with explicit error messages.

  • Removed the unused internal model_name argument and the redundant NA in the random-effect boundary check.

  • Clarified that separate component optimization maximizes the joint likelihood under independent random effects and no shared parameters.

  • Removed installation and export checks for the package itself from zavr(). The positive density now calls dNVASIM() directly, and dependency checks and version reporting cover external packages only.

  • Standardized longitudinal fixed-effect notation as gamma for the discrete component and beta for the continuous component. Renamed the discrete coefficient prefix from alpha_ to gamma_ in coef() and vcov() and aligned printed headings and documentation. Code that selects discrete coefficients by name must use gamma_.

  • Added zavr(), a zero-augmented normal-kernel Vasicek regression for longitudinal responses in [0, 1). A logistic component models presence, a Vasicek component models the conditional mean of positive responses, and each component has an independent subject-specific Gaussian random intercept.

  • Added zabr(), a zero-augmented beta random-intercept model following Chen and Li (2016), to provide a directly comparable beta positive component under the same computational interface.

  • Added one-sided formula interfaces for the presence and positive components and a random = ~ 1 | subject interface. The earlier character-vector arguments remain temporarily available with deprecation warnings.

  • Added non-adaptive Gauss–Hermite integration, multiple starting values, component-wise and joint likelihood-ratio tests, Hessian-based covariance estimates, optimization diagnostics, and print(), coef(), vcov(), logLik(), nobs(), and BIC() methods.

  • Joint AIC and BIC are calculated from the complete two-part likelihood. BIC uses the number of subjects in its penalty, following the PROC NLMIXED convention. Component-wise criteria are retained as diagnostics: AIC values are additive, whereas BIC values are not generally additive because the positive component uses only subjects with at least one positive response.

  • Added documentation, references, examples, dependency declarations, S3 registrations, and integration tests for the new longitudinal interfaces.

vasicekreg 1.2.0 (2026-09-03)

Self-contained quantile families

  • Renamed the fixed quantile-level argument from tau to quantile in NVASIQ, LVASIQ, and HVASIQ, including their d, p, q, and r functions and compiled interfaces.
  • Removed the dependency of the three quantile-family constructors on a global tau object. The fixed level is now passed directly, for example as NVASIQ(quantile = 0.25), stored in the family definition, and embedded as a numeric literal in the derivative, deviance, initial-value, residual, and conditional-moment components of the family object.
  • Updated vasicek_envelope() to recover the fixed level from the fitted model and use it in bootstrap simulation and refitting. Models fitted at different quantile levels can therefore coexist safely in one session.
  • Added tests for independence from global variables, simultaneous fits at different levels, serialization, automatic refitting, and fixed-level envelope simulation.
  • Retained tau unchanged as the estimated conditional probability at one among nonzero observations in ZOANVASIM.

Interface and documentation review

  • Added an application-oriented vignette, replacing the obsolete draft and covering all four included data sets. It fits the five bodyfat responses, compares the three quantile kernels, illustrates the zero-, one-, and zero-and-one-augmented families with transport, trees, and aep, and documents conditional and marginal fitted quantities and simulated residual envelopes.
  • Updated the package title and description to cover distribution functions, Vasicek-type models, and the hyperbolic-secant kernel and HVASIQ family.
  • Standardized boundary terminology as “augmented” and kernel terminology as “Vasicek-type” throughout the current documentation.
  • Corrected the bodyfat documentation: it contains 10 variables, and its five response variables are proportions in (0, 1), not values on a 0–100 scale.
  • Replaced generic quantile notation tau by p in the NVASIM quantile formula and corrected the description of the bivariate-normal CDF.
  • Added a real-data ZOANVASIM example based on the boundary-valued inappropriate-stay proportion in aep.
  • Extended the numerical derivative checks for all three quantile families to a grid of response, quantile, shape, and fixed-quantile values.
  • Added the documented print.vasicek_envelope() S3 method and tests for the print and plot interfaces.
  • Clarified that the reductions of ZOANVASIM at nu = 0 or tau = 0 are nested limiting cases in the closure of its open parameter space.
  • Aligned the documented endpoint domains of the base d, p, and q functions with their implemented behavior.
  • Corrected bibliographic page ranges, added the logistic-kernel reference to LVASIQ, expanded the package-level references, and documented all four included datasets in the package overview and README.
  • Added direct distribution-identity and normalization tests for all three boundary-augmented models.

Hyperbolic-secant-kernel quantile regression

  • Added the HVASIQ() GAMLSS family for conditional quantile regression with a hyperbolic-secant kernel and a user-specified fixed quantile level.
  • Added compiled dHVASIQ(), pHVASIQ(), qHVASIQ(), and rHVASIQ() functions, including stable log-probability and tail calculations.
  • Implemented closed-form first, second, and cross log-likelihood derivatives with respect to mu and sigma.
  • Added randomized quantile residual support and numerical conditional-moment functions for the GAMLSS family.
  • Extended vasicek_envelope() to fitted HVASIQ models.
  • Corrected parametric-envelope simulation for quantile families so the fixed level stored in the fitted model is passed to their random generators.
  • Added documentation and tests for distribution identities, normalization, fixed-quantile preservation, vectorization, analytical derivatives, conditional moments, random generation, and GAMLSS fitting.

Boundary-augmented mean regression

  • Added the GAMLSS-conventional aliases d/p/q/rZANVASIM(), d/p/q/rOANVASIM(), and d/p/q/rZOANVASIM(). The established numbered names remain available. This correspondence allows likelihood-based methods such as vcov.gamlss() to locate each family’s density function.
  • Added ZANVASIM(), a zero-augmented normal-kernel Vasicek mean family, with nu modeling the probability at zero.
  • Added OANVASIM(), a one-augmented normal-kernel Vasicek mean family, with nu modeling the probability at one.
  • Added ZOANVASIM(), a zero-and-one-augmented normal-kernel Vasicek mean family. In this family, nu is the probability at zero and tau is the conditional probability at one among nonzero observations.
  • Added the corresponding d0NVASIM(), p0NVASIM(), q0NVASIM(), r0NVASIM(), d1NVASIM(), p1NVASIM(), q1NVASIM(), r1NVASIM(), d01NVASIM(), p01NVASIM(), q01NVASIM(), and r01NVASIM() functions.
  • Added analytical derivatives, randomized quantile residuals, marginal moments, and GAMLSS fitting support for all three boundary-augmented families.

Simulated residual envelopes

  • Added vasicek_envelope() for parametric-bootstrap simulated envelopes based on fitted gamlss objects.
  • Added support for normalized randomized quantile residuals and generalized Cox–Snell residuals, with the latter defined from the same fitted probability integral transform and evaluated on the log-survival scale for numerical stability in the upper tail.
  • Added pointwise percentile and pointwise minimum–maximum envelopes.
  • Each accepted bootstrap sample is simulated from the fitted model, refitted, and used to recalculate and order the requested residuals.
  • Added print and plot methods for vasicek_envelope objects. The documentation now distinguishes these full quantile–quantile plots from half-normal plots and explains the finite-sample simulated mean curve.
  • Added a row-count check to automatic bootstrap refitting so data altered by missing-value removal or subset must be supplied explicitly or handled by a custom refit function.

Documentation and tests

  • Standardized the R source filenames as dpqr-0NvasicekM.R, dpqr-1NvasicekM.R, and dpqr-01NvasicekM.R.
  • Added numerical verification of all first, second, and cross derivatives for ZANVASIM, OANVASIM, and ZOANVASIM.
  • Added tests of the randomized quantile residual expressions for the zero-augmented, one-augmented, and zero-and-one-augmented families, including the CDF jump intervals, interior observations, reproducibility, and simulation from the fitted family.
  • Added tests for simulated residual envelopes, including argument validation, reproducibility, returned components, plotting, stable Cox–Snell upper-tail calculations, and incompatible refit data.
  • Clarified the roles of x and q and distinguished the boundary behavior of the zero-augmented, one-augmented, and zero-and-one-augmented distributions.
  • Updated the package overview to describe the boundary-augmented families and to distinguish the tau parameter in ZOANVASIM from the fixed quantile level used by NVASIQ and LVASIQ.
  • Added a package-level example comparing OANVASIM and BEOI using the one-inflated accuracy1 response from the ReadingSkills data.
  • Expanded the README references for the Vasicek distributions, GAMLSS, boundary-augmented models, randomized quantile and Cox–Snell residuals, simulated envelopes, and Rcpp.

vasicekreg 1.1.0 (2026-07-28)

CRAN release: 2026-08-20

Interface reorganization

  • Renamed the normal-kernel mean family and distribution functions from VASIM to NVASIM.
  • Renamed the normal-kernel quantile family and distribution functions from VASIQ to NVASIQ.
  • Retained LVASIQ for the logistic-kernel quantile distribution functions.
  • Renamed the corresponding R and C++ source files to identify the kernel (N or L) and parameterization (M or Q) explicitly.
  • Renamed the internal Rcpp routines and regenerated their registration interfaces.
  • Updated the namespace, documentation, examples, package overview, and tests for the new interface.

GAMLSS quantile level

  • NVASIQ() does not accept tau as an argument. For GAMLSS fitting, tau must be defined as a scalar variable in the global environment.
  • The distribution functions dNVASIQ(), pNVASIQ(), qNVASIQ(), and rNVASIQ() continue to accept tau explicitly.

Logistic-kernel quantile regression

  • Added the LVASIQ() GAMLSS family for conditional quantile regression with the logistic-kernel Vasicek distribution.
  • Implemented closed-form first, second, and cross derivatives with respect to mu and sigma; model fitting does not use numerical differentiation.
  • Added quantile residual support and numerical moment functions for the family object.

vasicekreg 1.0.3 (2026-07-28)

Bug fixes

  • Restored the missing implementation of qVASIM().
  • Corrected log.p handling in all quantile functions.
  • Corrected the bivariate-normal calculation used by the variance components of VASIM() and VASIQ().
  • Made the fixed quantile level an explicit argument of VASIQ() and removed dependence on a global tau object.
  • Corrected the second derivative with respect to mu in VASIQ().
  • Added stable upper-tail calculations and consistent parameter-length checks to the C++ routines.

Documentation and tests

  • Clarified that the logistic-kernel implementation currently provides distribution functions but not a GAMLSS family.
  • Added executable tests for distribution identities, moments, derivatives, vectorization, and fixed-quantile handling.

vasicekreg 1.0.2 (2026-01-12)

CRAN release: 2026-01-12

Improvements

  • Performance optimizations in dpqr-vasicekmean.R and dpqr-vasicekquant.R.

vasicekreg 1.0.1 (2021-12-05)

CRAN release: 2021-05-27

Bug fixes

  • Corrected the term variance = function(mu, sigma) in the VASIM family.
  • Corrected the term variance = function(mu, sigma) in the VASIQ family.

vasicekreg 1.0.0 (2021-07-05)

CRAN release: 2021-05-07

Initial release

  • First release of the vasicekreg package on CRAN.